Behind every early warning system is a community that knows where it floods, who is vulnerable, and what needs to be done. In this talk, we will share how OpenMap Development Tanzania (OMDTZ) has placed local communities, especially youth, elders, and local leaders, at the heart of anticipatory action using OpenStreetMap (OSM).
We’ll spotlight how trained community mappers contributed to flood preparedness in Dar es Salaam, not just by mapping hazards but by shaping how risk is understood and acted upon. From identifying safe zones to guiding rescue teams, their knowledge became the backbone of local planning.
This session explores how open tools and inclusive engagement can turn vulnerable communities into resilient ones, and first responders, especially in contexts with limited formal warning systems.

Traditional humanitarian responses often occur after disasters, resulting in loss of life and significant resource expenditure. Anticipatory Action (AA) presents a paradigm shift by enabling early interventions based on forecasts and risk analysis. In Malawi, the Malawi Red Cross Society (MRCS) piloted an anticipatory approach ahead of a forecasted cyclone, demonstrating that timely action can save lives and reduce response costs by at least 15%.

A critical element of the AA process was the pre identification of at risk and vulnerable populations. Using OpenStreetMap (OSM) basemaps overlaid with historical flood extents from 2015 to present, maps were generated and printed for community validation. Recognizing the limitations of satellite data, particularly in capturing flash floods, Participatory GIS (PGIS) was employed. Communities mapped flood prone zones based on their lived experience from the past decade. These hand drawn maps were digitized, returned for verification, and finalized.

Due to limited resources, MRCS could only support 1,034 households. While Unified Beneficiary Registry (UBR) data was initially considered, gaps in coverage led to the adoption of the Joint Emergency Food Assistance Programme (JEFAP) approach. Communities identified the most vulnerable individuals through participatory methods. These individuals were registered using KoboToolbox, and a secondary door to door georeferenced verification exercise was conducted to refine the beneficiary list and confirm household locations in flood risk zones.

With the beneficiaries identified, MRCS worked with financial service providers to preposition cash resources. Once a formal trigger was issued by the Department of Climate Change and Meteorological Services (DCCMS), funds were disbursed in advance of the cyclone.

Post distribution monitoring revealed that recipients used the cash to relocate, strengthen shelters, and protect key belongings. Many credited the assistance with saving their lives and property, underscoring the value of early action driven by community led mapping and data-informed targeting.

Self-Paced Open Mapping Learning Pathway for Youth Leadership and Community-Driven Development in LearnWorld
This self-paced learning program equips youth with practical skills in open mapping tools to strengthen their capacity to address local challenges through data. By offering modular, flexible training on a range of open mapping tools such as OpenStreetMap (OSM), iD Editor, JOSM, Tasking Manager, MapRoulette, StreetComplete, and KoboToolbox—this curriculum enables young people to become not just contributors, but local mapping leaders, driving change within their own communities.
The courses emphasizes experiential learning, community engagement, and leadership development. Beginning with an introduction to open mapping and the Humanitarian OpenStreetMap Team (HOT), learners explore the ecosystem of Open Mapping Hubs and understand how open mapping contributes to humanitarian response, sustainable development, and climate action. Structured in progressive modules, the curriculum takes learners from beginner-friendly tools like iD Editor and mobile mapping apps, to advanced techniques in field data collection, validation, and AI-assisted mapping.
At the heart of this initiative is the principle of Learning to create impact by taking on leadership roles within their communities, guiding locally-driven mapping efforts that address real challenges and reflect community priorities. Learners are encouraged to work with local communities to identify shared challenges such as access to healthcare, disaster preparedness, or transportation planning and to map these priorities using the tools introduced in the course. This ensures that data generated through mapping reflects real, lived experiences and supports effective local decision-making.
Project-based learning units guide youth to apply their new skills in mapping initiatives that respond directly to community needs. By learning to plan and manage field mapping campaigns, use offline tools in low-connectivity settings, and support collaborative workflows via Tasking Manager and MapRoulette, learners gain practical experience aligned with real-world humanitarian and development scenarios.
Modules on tools like Mapillary and Mapswipe also provide inclusive, low-barrier entry points for those who may not be able to engage in traditional editing but still want to contribute meaningfully to data improvement.
Throughout the pathway, youth are encouraged to take on peer-mentorship and training roles within their communities, ultimately becoming open mapping trainers. A dedicated unit on training facilitation and leadership development supports this goal. Learners are introduced to techniques for guiding local mapping sessions, supporting quality control, and mentoring new contributors. This leadership aspect not only reinforces technical skills but also fosters soft skills in communication, planning, and community engagement.
By the end of the courses, participants will have:
Gained practical proficiency in open mapping tools gain valuable experience for open mapping mapping skills and experience and leverage them in the development of their professional and civic lives.

Learned to plan, manage, and evaluate field data collection activities;

Understood how to align mapping initiatives with humanitarian, development, and climate goals;

Engaged with local communities to ensure that mapping reflects their lived realities;

Grown into local leaders capable of training others and sustaining community-based open mapping efforts.

Introduction/Contexte
Madagascar, quatrième plus grande île du monde avec ses 587 000 km², présente des défis cartographiques uniques en raison de sa géographie complexe, de sa biodiversité exceptionnelle et de ses infrastructures en développement. Dans le contexte africain, où la cartographie ouverte joue un rôle crucial pour le développement durable et la résilience face aux catastrophes naturelles, OpenStreetMap (OSM) représente une ressource cartographique essentielle pour les communautés malgaches. Cependant, la qualité hétérogène des données OSM et les patterns de contribution inégaux constituent des obstacles majeurs à l'utilisation optimale de ces données pour la planification territoriale, la gestion des risques et le développement socio-économique. L'archipel des Comores et les autres îles de l'océan Indien occidental partagent des défis similaires, notamment en termes de couverture cartographique limitée des zones rurales, de représentation insuffisante des infrastructures locales traditionnelles, et de participation communautaire restreinte aux initiatives de cartographie collaborative. Cette problématique s'inscrit dans le contexte plus large de la fracture numérique en Afrique australe et de la nécessité de développer des approches méthodologiques adaptées aux spécificités insulaires pour garantir une cartographie participative inclusive et durable.
Objectif Principal de l'Étude
Cette recherche vise à analyser de manière systématique la qualité des données OpenStreetMap à Madagascar et à identifier les patterns de contribution pour développer des stratégies d'amélioration de la participation communautaire à la cartographie ouverte. L'objectif spécifique est triple : premièrement, évaluer la complétude, la précision géométrique et la cohérence sémantique des données OSM sur l'ensemble du territoire malgache en utilisant des métriques intrinsèques et extrinsèques ; deuxièmement, analyser les dynamiques spatiales et temporelles des contributions pour identifier les zones sous-cartographiées et les communautés de contributeurs actifs ; troisièmement, proposer un cadre méthodologique reproductible pour l'amélioration continue de la qualité des données cartographiques ouvertes dans les contextes insulaires africains. Cette approche intégrée permettra de formuler des recommandations pratiques pour renforcer l'écosystème OSM dans la région de l'océan Indien occidental et de contribuer aux objectifs de développement durable par une meilleure accessibilité de l'information géospatiale.
Méthodologie et Résultats Obtenus
La méthodologie adoptée combine l'analyse quantitative des données OSM avec des approches qualitatives d'évaluation communautaire. L'évaluation de la qualité intrinsèque a été réalisée en utilisant des indicateurs de complétude (densité des nœuds par km², couverture des types d'objets géographiques), de précision géométrique (analyse des incohérences topologiques), et de cohérence sémantique (validation des tags selon les standards OSM). Les données de référence proviennent de l'Institut National de la Statistique de Madagascar, des images satellites haute résolution, et des relevés GPS effectués sur le terrain dans six régions représentatives. L'analyse des patterns de contribution a été menée sur une période de dix ans (2014-2024) en utilisant des techniques de clustering spatial et d'analyse de séries temporelles pour identifier les tendances de participation. L'étude a également intégré une composante socio-technique par le biais d'enquêtes auprès de 150 contributeurs OSM malgaches et d'entretiens semi-directifs avec 25 acteurs clés du secteur géospatial.
Les résultats révèlent une couverture OSM hétérogène avec une densité de données élevée dans les centres urbains (Antananarivo, Antsirabe, Mahajanga) contrastant avec une sous-représentation significative des zones rurales et des régions reculées. La précision géométrique moyenne des données routières atteint 85% de conformité avec les standards cartographiques internationaux, mais chute à 45% pour les infrastructures rurales traditionnelles. L'analyse temporelle montre une croissance exponentielle des contributions entre 2018 et 2022, principalement liée aux initiatives de cartographie humanitaire, suivie d'une stabilisation en 2023-2024. Les patterns de contribution révèlent une concentration de 70% des éditions par seulement 15% des contributeurs actifs, suggérant des opportunités d'élargissement de la base participative. L'évaluation qualitative met en évidence les barrières linguistiques, technologiques et culturelles qui limitent l'engagement communautaire, particulièrement dans les communautés rurales où les connaissances géographiques locales restent largement inexploitées.
Discussion et Contribution Scientifique
Cette recherche apporte plusieurs contributions significatives au domaine des sciences géospatiales et de la cartographie participative en contexte africain. Premièrement, elle propose une méthodologie intégrée d'évaluation de la qualité OSM adaptée aux spécificités insulaires, combinant métriques quantitatives automatisées et validation communautaire participative. Cette approche méthodologique est reproductible et transférable vers d'autres territoires insulaires africains, notamment l'archipel des Comores, les Seychelles, et Maurice. Deuxièmement, l'étude établit pour la première fois un diagnostic complet de l'écosystème OSM malgache, fournissant des données de référence essentielles pour les futures recherches et interventions de développement. La caractérisation des patterns de contribution permet d'identifier les leviers d'action prioritaires pour renforcer la participation communautaire et améliorer la représentativité géographique des données.
L'analyse comparative avec d'autres contextes africains révèle des similitudes dans les défis de fracture numérique et de participation inégale, mais aussi des spécificités insulaires qui nécessitent des approches adaptées. La recherche contribue également à la compréhension des dynamiques socio-techniques de la cartographie collaborative en démontrant l'importance des facteurs culturels et linguistiques dans l'adoption des technologies de cartographie participative. Les résultats questionnent les modèles de développement technologique uniformes et plaident pour des approches contextualisées respectueuses des savoirs géographiques traditionnels.
Implications Pratiques pour la Communauté OpenStreetMap
Les implications pratiques de cette recherche sont multiples et directement applicables pour renforcer l'écosystème OSM en Afrique. Les recommandations incluent le développement d'interfaces utilisateur multilingues intégrant le malgache et les langues locales, la création de programmes de formation communautaire adaptés aux contextes ruraux, et l'établissement de partenariats avec les institutions éducatives locales pour intégrer OSM dans les curricula géographiques. La recherche propose également un protocole de validation collaborative des données impliquant les communautés locales comme garantes de la précision et de la pertinence culturelle des informations cartographiques.
Pour la communauté OSM globale, cette étude fournit des outils méthodologiques d'évaluation de la qualité reproductibles dans d'autres contextes géographiques, particulièrement utiles pour les initiatives de cartographie humanitaire en Afrique. Les indicateurs développés peuvent être intégrés dans les outils de monitoring existants pour améliorer le suivi de la qualité des données en temps réel. La recherche souligne également l'importance de développer des mécanismes de reconnaissance et d'incitation adaptés aux contextes socio-économiques locaux pour maintenir l'engagement communautaire à long terme.
Les résultats encouragent la création de communautés OSM régionales dans l'océan Indien occidental, facilitant le partage d'expériences et de bonnes pratiques entre Madagascar, les Comores, Maurice et les Seychelles. Cette approche régionale pourrait catalyser le développement d'une cartographie ouverte insulaire africaine plus robuste et culturellement ancrée, contribuant significativement aux objectifs de connectivité communautaire et de collaboration du thème de la conférence State of the Map Africa 2025.

Africa's digital transformation demands localized, affordable and sustainable geospatial services. AmbaLay Maps is a homegrown African mapping service provider that builds on OpenStreetMap data to power APIs and geospatial tools tailored to the continent’s unique needs. This presentation will showcase how AmbaLay Maps bridges the gap between open mapping communities and commercial users, from logistics and delivery platforms to urban planners and humanitarian responders.

We will demonstrate our routing, geocoding, and tile services—all built using PostGIS, Node.js, and Docker, and optimized for low-bandwidth and offline environments. We will share case studies of how AmbaLay Maps APIs have supported projects in digital addressing, public transport, and crisis response in Ethiopia, especially in underserved regions where global services are less effective.

This talk aims to inspire African developers, OSM contributors, and decision-makers to think beyond just mapping and build a full-fledged open geospatial infrastructure that is owned and shaped by Africans, for Africans. We’ll also share our open roadmap and current challenges and invite collaborators across Africa to co-develop and deploy local mapping platforms that reflect our languages, landmarks, and lived experiences.

Learning Outcomes:
- Discover how OpenStreetMap data can power African-led geospatial platforms
- Understand the technical and strategic steps to build local map APIs and services.
- Explore models for integrating community mapping with scalable tech infrastructure.
- Learn how localized mapping supports sustainable development, logistics, and emergency services.

Description de la Présentation
L'idée est de présenter la nouvelle GeoPlateforme (GeOSm )comme un hub fédérateur pour les communautés OpenStreetMap d'Afrique et d'ailleurs. Elle rassemble les territoires, les acteurs, les projets et les ressources documentaires utiles, tout en offrant un espace cartographique puissant, enrichi d'indicateurs spatialisés très pertinents.

Conception et Planification
La phase initiale a consisté à définir des fondations solides pour le projet. La première étape a été de clarifier les objectifs : quel problème la GeoPlateforme résoudra-t-elle et qui sont ses utilisateurs cibles ? À partir de là, nous avons établi une liste détaillée des fonctionnalités requises, allant de la visualisation de cartes interactives et la recherche de lieux, jusqu'à des outils plus avancés comme les requêtes spatiales et l'exportation de données (GeoJSON, etc.).

Parallèlement, un travail essentiel a été mené sur l'expérience utilisateur (UX) et l'interface (UI). L'objectif est de créer des parcours utilisateurs intuitifs et de concevoir des maquettes visuelles pour une interface à la fois puissante, simple et agréable à utiliser, centrée sur une interaction fluide avec la carte.

Architecture Technique
Pour la flexibilité et la capacité à évoluer, la GeoPlateforme est bâtie sur une architecture de microservices. Cette approche permet de découpler les différentes composantes de l'application (par exemple : gestion des données, affichage des cartes, authentification), facilitant les mises à jour et la maintenance.

Développement et Tests
Le développement s'est déroulé en sprints agiles, permettant des livraisons rapides et des ajustements continus. L'équipe backend met en place la base de données, développe les scripts d'importation des données OSM et construit les API. En parallèle, l'équipe frontend développe l'interface utilisateur, en intégrant la carte et en la connectant aux API pour afficher les données. Tout au long du processus, des tests unitaires et d'intégration sont automatisés pour garantir la qualité et la stabilité du code.

Déploiement et Maintenance
Une fois développée, l'application a été déployée sur une infrastructure cloud pour assurer une haute disponibilité et une scalabilité optimale. Des mises à jour régulières assureront l'amélioration continue des fonctionnalités et de la sécurité de la GeoPlateforme.

Chaque communauté OpenStreetMap aura la pleine autonomie pour gérer et personnaliser sa propre plateforme.

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Presentation Description
The idea is to present the new GeoPlatform (GeOsm) as a unifying hub for OpenStreetMap communities in Africa and beyond. It brings together territories, stakeholders, projects, useful documentation resources, and, crucially, a powerful mapping space enriched with highly relevant spatialized indicators.

Design and Planning
The initial phase involved laying a solid foundation for the project. The first step was to clarify the objectives: what problem will the GeoPlatform solve, and who are its target users? From there, we established a detailed list of required functionalities, ranging from interactive map visualization and place search to more advanced tools like spatial queries and data export (GeoJSON, etc.).

In parallel, essential work was carried out on user experience (UX) and user interface (UI). The goal is to create intuitive user journeys and design visual mock-ups for an interface that is powerful, simple, and pleasant to use, centered on fluid interaction with the map.

Technical Architecture
For flexibility and scalability, the GeoPlatform is built on a microservices architecture. This approach allows for decoupling the different components of the application (e.g., data management, map display, authentication), facilitating updates and maintenance.

Development and Testing
Development proceeded in agile sprints, allowing for rapid deliveries and continuous adjustments. The backend team sets up the database, develops OSM data import scripts, and builds the APIs. Simultaneously, the frontend team develops the user interface, integrating the map and connecting it to the APIs to display the data. Throughout the process, unit and integration tests are automated to ensure code quality and stability.

Deployment and Maintenance
Once developed, the application has been deployed on a cloud infrastructure to ensure high availability and optimal scalability. Regular updates will ensure continuous improvement of the GeoPlatform's functionalities and security.

Each OpenStreetMap community will have full autonomy to manage and customize its own platform.

Community engagement is one of the most powerful and often underestimated elements of successful mapping. In this talk, I will share my journey and lessons from working directly with local communities in Tanzania on a range of mapping projects each driven not just by data, but by people.

From the litter assessment project in Dar es Salaam to school feeding mapping and infrastructure digitization in over 15 regions, I’ve seen firsthand how mapping becomes more meaningful when communities are fully involved. My role often included training local volunteers, many of whom had never interacted with digital tools like OpenStreetMap, ODK, or QGIS to map their own surroundings. We didn’t just collect data, we built relationships, encouraged curiosity, and created opportunities for people to take part in shaping their environment.

The process starts with trust, listening to the community, understanding their needs, and respecting their knowledge. This ensures that the data collected reflects lived realities not assumptions. In many cases, community members pointed out features or issues that would have otherwise gone unnoticed. Whether it was identifying informal waste dumping sites, mapping roads that never appeared on digital maps, or recording school locations accurately, the local input made the map more complete, more honest, and more useful.

We’ll also discuss the importance of building capacity. Training sessions were not just about teaching tools, but also about showing the value of open data and helping people to see themselves as part of something bigger. This kind of engagement leads to long-term impact participants often continue mapping, advocating, and teaching others long after the project ends.

In 2024, Malawi hosted its first-ever State of the Map Malawi (SoTMM) conference; an important milestone for the country’s growing open mapping ecosystem. The event was organized by OpenStreetMap Malawi, a Community of Practice (CoP) comprising GIS professionals, remote sensing experts, open-source advocates, university students, and researchers from across the country.

Bringing such a national conference to life for the first time came with valuable lessons, key challenges, and promising opportunities. Beyond SoTMM, the OSM Malawi community has continued to implement a wide range of initiatives aimed at expanding the geospatial community, promoting open mapping practices, and fostering collaboration across sectors.

This talk will reflect on the journey of organizing the inaugural SoTMM, the strategies we’ve employed to build and sustain community networks, and the ongoing activities driving engagement and capacity building in Malawi. It will also explore the broader implications for emerging OSM communities across Africa; offering practical insights, sparking dialogue, and encouraging peer learning among communities navigating similar paths.

Open mapping is a powerful tool for inclusion, yet women remain underrepresented—particularly in Central Africa. In the Democratic Republic of Congo, our community has committed to addressing gender imbalance by embedding gender-sensitive approaches into participatory mapping projects.

This talk highlights our concrete efforts to promote women's participation: women-focused training workshops, mentorship programs, and campaigns that map issues like reproductive health, safety, and access to essential services. We will share key lessons learned from working within cultural and social constraints, as well as strategies for creating inclusive environments, including university-based outreach, peer support networks, and leadership development.

We will also present measurable results: a growing number of active female mappers, the emergence of women leaders in our local OSM networks, and the positive impact on data quality and diversity. The session concludes with actionable recommendations for other African mapping communities aiming to improve gender balance and community resilience.

Cycling is increasingly recognized as one of the most environmentally friendly, affordable, and inclusive modes of transport. In the African context, it holds great potential to address challenges such as urban congestion, air pollution, rising fuel costs, and limited access to public transportation, especially for low-income populations. However, the adoption of cycling in many African cities and towns remains low due to inadequate infrastructure, poor safety conditions, and a general lack of data to inform planning and policy.
This talk explores how OpenStreetMap (OSM) data can be leveraged to support and promote cycling as a sustainable mode of transport across Africa. As a free, editable, and community-driven mapping platform, OSM provides a powerful tool for collecting and visualizing data on road networks, bike lanes, terrain, traffic conditions, and services such as bike shops or repair points. In many African contexts where government data is outdated, incomplete, or inaccessible, OSM offers an alternative source of geospatial information that can be used by a wide range of stakeholders, from urban planners to cycling advocacy groups.
Drawing from real-world experiences in African cities such as Accra, Dar es Salaam, and Nairobi. This presentation highlights how local mapping communities are using OSM to identify gaps in cycling infrastructure, map existing routes and conditions, and create open datasets for routing applications and transport planning. The session will also examine the role of youth-led and community-based mapping initiatives, which are not only contributing valuable data but also raising awareness about non-motorized transport and its environmental benefits.
The presentation will demonstrate how tools built on OSM, such as CyclOSM, Mapillary, etc., can be applied in African settings to support safe cycling navigation, infrastructure development, and public participation in transport decision-making. It will also address key challenges such as limited internet access, low mapping literacy, and data quality concerns, and propose strategies for building local capacity and fostering collaboration among cyclists, technologists, urban planners, and policymakers.
Ultimately, the talk will argue that enhancing cycling through open data is not just a transportation issue, but also a pathway to climate resilience, health equity, and inclusive urban development. By harnessing the potential of OSM, African communities can drive locally relevant solutions that promote sustainability, reduce emissions, and make cities more livable for all.

What happens when the world’s most powerful map meets the world’s largest encyclopedia? This talk dives into the dynamic intersection of Wikimedia and OpenStreetMap; two open knowledge giants reshaping how Africa maps, documents, and shares its stories. From linking Wikidata to mapped features, to showcasing cultural landmarks through Wikipedia and OSM, we’ll explore how communities are merging geospatial and encyclopedic data to build a richer, more connected digital continent.

Open mapping platforms such as OpenStreetMap (OSM) have revolutionized access to geographic data by offering a collaborative and open-source approach to map creation and maintenance. These platforms are especially valuable in regions where conventional mapping tools and data are either outdated, inaccessible, or prohibitively expensive. In underserved and resource-constrained communities, however, significant challenges persist in ensuring that the map data is current, detailed, and reflective of local realities. Limitations in infrastructure, digital skills, financial resources, and access to high-quality imagery all contribute to gaps in spatial data coverage, particularly in rapidly changing urban and peri urban environments
To address these challenges, this proposal introduces a cost-effective, scalable methodology that leverages street-level 360-degree imagery to enhance open mapping efforts in resource-limited contexts. By utilizing affordable consumer-grade 360° cameras, smartphones, and community-led data collection techniques, we propose a practical approach that can be deployed in diverse environments with minimal technical barriers. The use of Mapillary platforms as allows contributors to upload and share imagery openly, supporting global OSM editing and validation activities.
At the heart of this approach is the principle of community participation. Local volunteers, especially youth and members of existing mapping communities, can be trained to capture 360° imagery by walking, biking, or driving through their neighborhoods. These community members are uniquely positioned to access areas that might be unreachable or unsafe for outsiders, while also bringing contextual knowledge that enhances the interpretation and annotation of collected imagery. The combination of local insight and digital tools ensures that the resulting data is not only geographically accurate but also socially meaningful.

Abstract:
Access to affordable, nearby daycare is a pressing concern for many parents, particularly young mothers who seek to continue their education or participate in the workforce. Yet, in many parts of Africa, spatial data on childcare facilities remains sparse, outdated, or completely unavailable.
This talk will present a community mapping initiative that aims to address this data gap by identifying and mapping daycare facilities in a Nairobi neighbourhood using OpenStreetMap tools. Through a participatory process involving local youth and community groups, the project collects geolocated data on operational daycare centers, including their names, services, capacity, contact information, and safety features.
To achieve this, the project utilizes QGIS for planning, digitization, and visualization of the data layers, while QField is used for efficient, mobile-based field data collection. With the JOSM plugin in QGIS, the cleaned and verified datasets are uploaded directly to the OSM platform, ensuring that the information becomes globally accessible and contributes to the growing body of open data supporting African communities.
The use of these open-source tools enables community members, including those with limited technical backgrounds, to engage in the full mapping workflow. The project ultimately empowers local mappers, supports better decision-making for parents, and enables local leaders and planners to identify service gaps and allocate resources more effectively.
In alignment with the conference theme, this initiative showcases how grassroots open mapping can connect communities to essential services, promote gender equality, and foster sustainable collaboration among residents, developers, government officials, and open data advocates.

Key Learning Outcomes:
• How to use QGIS and QField to implement a local community mapping project
• Publishing collected data to OpenStreetMap using the JOSM plugin
• Engaging local stakeholders—especially women and youth—in a participatory mapping approach
• Practical lessons from mapping social infrastructure that serves vulnerable populations

Speaker Bio:
Maurine Oyugi is a Geomatics Engineer and GIS Consultant passionate about using geospatial data to address community needs. She was the Regional Ambassador for YouthMappers in Kenya and has led open mapping campaigns across universities and humanitarian contexts. Her work integrates spatial technology, grassroots engagement, and social impact, rooted in both technical expertise and lived experience as a young parent.

EduMap Bénin est une plateforme web conçue pour géolocaliser les écoles béninoises en situation de précarité : manque d’infrastructures, d’enseignants, ou d’accès à l’eau potable afin de faciliter leur visibilité et encourager des actions de solidarité (dons, partenariats, soutien institutionnel).
Ce projet est né dans le cadre du programme D-Clic de l’Organisation Internationale de la Francophonie (OIF), qui m’a permis d’acquérir des compétences en développement web et de les mettre au service d’une cause locale à fort impact social.
En combinant les données libres d’OpenStreetMap avec une interface simple et accessible, EduMap Bénin permet aux acteurs locaux, ONG et citoyens engagés d’identifier les établissements vulnérables et d’agir en connaissance de cause.
Cette présentation mettra en lumière la genèse du projet, les outils techniques mobilisés, les défis rencontrés sur le terrain, et les perspectives de développement. Elle vise à inspirer d’autres jeunes porteurs de projet en Afrique, en montrant comment les compétences numériques peuvent se transformer en solutions concrètes pour nos communautés.

How can open mapping transform the way local governments respond to disasters, plan for the future, and empower their communities? Join me as I share firsthand experiences from Namisindwa District, Uganda, where I serve as an IT Officer using GIS data to drive strategic decisions and improve service delivery.

I’ll take you on a journey through the frontline challenges of mapping climate-induced disasters—cracks forming in the earth, devastating floods, and winds that have uprooted crops, displaced families, and forced community relocations. Using powerful open-source tools like JOSM, QGIS, KoboToolbox, and Mapbox, we gather vital data, visualize it in intuitive ways, and turn it into actionable insights that save lives and strengthen resilience.

But this story is about more than just technology—it’s about people. I’ll share how we engage youth through digital education and GIS training in rural schools, building a new generation of mappers and problem-solvers. This community-driven approach fosters ownership and sustainability.

I’m excited to connect with fellow mappers, government officials, NGOs, and tech innovators who share a passion for harnessing open data to tackle complex challenges. Together, we can build stronger partnerships that expand these solutions across Africa and beyond.

Flooding remains one of the most pressing environmental challenges confronting coastal communities in Ghana, with significant implications for livelihoods, housing, public infrastructure, and human security. (Darko et al., 2021). Among these vulnerable communities is Dutch Komenda in the Central Region of Ghana, a town situated along the Sosu Lagoon and the Atlantic coastline.
In our ongoing commitment to leveraging open data for community resilience, the YouthMappers chapter at the University of Cape Coast spearheaded a project focused on mapping coastal vulnerability in Komenda, a coastal town in Ghana increasingly threatened by climate change-induced disasters such as sea-level rise, erosion, and tidal flooding. A proposal was submitted to the Open Knowledge Foundation as part of the activities marking the 2025 Open Data Day celebration and a grant was awarded, allowing the team to collaborate with residents, community elders, and key stakeholders at Dutch Komenda to gather indigenous knowledge about previous flood events, areas most affected, critical infrastructure, and vulnerable populations. Rooted in our academic training and community-centered approach, this initiative reflects our mission to give back through actionable geospatial solutions. Using open-source tools like OpenStreetMap and SWMaps, the team engaged local stakeholders and mapped at-risk infrastructure, enabling data-driven adaptation planning. This project underscores the critical role of youth-led, open-data initiatives in addressing climate vulnerabilities and building sustainable, locally informed resilience strategies—an effort we hope to share and expand through the State of the Map Tanzania platform.
As part of the participatory mapping methodology, a drone was used to acquire high-resolution aerial photographs of the neighbourhood, which were then used during focused group discussions and transect walks to enable community members to reference their experiences spatially. SW Maps, an open-source mapping platform, was also utilised to collect field-based geospatial data, including floodwater depths indicated by watermarks on buildings, the locations of critical community resources, and temporary flood shelters. According to qualitative data from the study, flooding in Dutch Komenda is mainly caused by prolonged rains, the Sosu Lagoon's insufficient drainage capacity, and choked waterways exacerbated by indiscriminate trash disposal. Floodwaters were reported to reach chest level in low-lying portions of the neighbourhood, particularly near the community centre and along key roadways, causing damage to homes, kitchens, fishing equipment, and food supplies. Women, children, and older people were among the most vulnerable demographic groups. The participation sessions also revealed the absence of a functional health facility, the inaccessibility of a new resettlement site, and the lack of institutional emergency preparedness procedures in the community.
One notable effect of participatory mapping was the creation of a composite flood risk and vulnerability map that combined qualitative insights with quantitative geospatial data. This map identifies flood-prone locations, vital community assets, and potential safe zones, making it a valuable tool for local planning and advocacy.
The project's outcomes aim to contribute to broader discussions on participatory disaster risk reduction, climate adaptation, and community resilience in Ghana's coastal context. The mapping exercise further raised awareness among the community members on the need to practice basic environmental management strategies. These include ensuring the cleanliness of the Sosu Lagoon and utilising communal labour exercises to expand the channel of the Lagoon. With this initiative, the chapter showcased its passion for using geospatial technologies to address environmental issues related to climate change. Apart from empowering the residents of Dutch Komenda, the project also provided evidence to make suggestions to NGOs in disaster management and government officials. The project's outcome highlights the importance of open data and the necessity of an inclusive approach in disaster management and adaptation planning, where the knowledge and skills of those who will be affected by the plans are taken into account.
In summary, the participatory mapping on flood hazard and vulnerability in Dutch Komenda serves as a perfect example of how indigenous knowledge, coupled with open geospatial tools, can help drive positive change in communities under constant pressure from climate change impacts. This approach is recommended to other YouthMappers chapters and geospatial associations in Ghana and beyond to collaboratively assist local communities in finding scalable means to analyse and address their environmental challenges. By fostering collaboration, community members appreciate their efforts and take ownership of the project's outcome, laying a solid foundation for future interventions aimed at protecting sustainable livelihoods and ultimately building resilience.
Keywords: Participatory Mapping, Sosu Lagoon, Flood Vulnerability, Geospatial Tools, and Community Resilience.

Humanitarian organizations often rely on open map data to understand the scale of disaster impact and to guide timely interventions. Our mapping journey (as Kenya Red Cross Society) didn't begin with the goal of building a community of mappers but to generate open data for specific events or projects. These initiatives - often in the form of mapathons and field mapping - brought together students, volunteers and communities around a shared goal: contributing to OpenStreetMap for humanitarian response.

While these project based efforts achieved their immediate objectives, a key realization emerged - project based mapping while impactful does not necessarily create long lasting communities.

This session reflects the learning and insights of holding ad hoc mapathons and trainings to a more structured intentional approach to community building. Well share our lessons from conducting mapathons with university students and coordinated field mapping with local communities. Through trial, iteration, and reflection, we are learning how to create continuity, foster deeper engagement, and align open mapping efforts with long-term impact.

OpenMap Development Tanzania (OMDTZ) undertook a participatory mapping initiative in the Weruweru River Catchment, Kilimanjaro region, to enhance sustainable water management through detailed GIS analysis. Collaborating with the Weruweru Water Users Association (WUA), the project aimed to develop comprehensive maps of the catchment's hydrological features, including irrigation furrows and water abstraction points. Utilizing Android-based GPS devices, satellite imagery, and traditional surveying methods, field teams collected data on furrow dimensions and infrastructure conditions. GIS software facilitated the analysis, revealing critical issues such as blockages, leaks, and erosion. This approach not only improved the accuracy of water resource data but also empowered local communities by enhancing their capacity to manage and make informed decisions about their water resources. The project's success underscores the importance of community engagement and accurate data in developing equitable and sustainable water distribution policies. It serves as a replicable model for other sub-catchments facing similar challenges, highlighting the value of participatory mapping in environmental management.

This session explores the challenges of adapting OSM for Southeast Asia and how the community can enhance map data to improve mobility and livelihoods for millions. Southeast Asia experiences many similar challenges in mobility an access as Africa does: How can these lessons be adapted to Africa and beyond?

GrabMaps uses OSM data, 360 cameras, LiDAR and our driver partners to walk, bike and drive to make better maps. This talk will also showcase our newest innovations like KartaVoice, an assistant you talk to to improve OSM data and more.

In humanitarian crises, rapidly changing conditions such as damaged infrastructure, weather hazards, or security threats significantly impact the efficiency and safety of aid delivery and logistics. Standard static routing methods, even those leveraging regularly updated OpenStreetMap (OSM) data, often fail to quickly adapt when a critical bridge collapses overnight or a newly flooded road blocks previously safe routes. Thus, lacking the flexibility to integrate rapidly evolving, mission-critical information from humanitarian organizations and local communities. Our approach addresses this gap by dynamically incorporating real-time, external operational data directly into mobility analysis.

OpenStreetMap provides a foundational role in disaster response, empowering local and remote volunteers to rapidly update map features like road accessibility, infrastructure status, and community resources. Active OSM mapping efforts, such as those coordinated by the Humanitarian OpenStreetMap Team (HOT), continuously enhance the accuracy and timeliness of geographic information available to humanitarian responders. Community-led mapping initiatives ensure that routes, landmarks, and hazard areas are promptly updated, directly benefiting routing decisions during crisis operations.

In this talk, you will learn about multiple aspects:

• How does your mapping in OSM directly influence humanitarian mobility analysis, and what can you do to enhance this during mapping.
• How do we close the gap between OSM data, which is updated at a slower but steady pace during disasters, and the need for current mission-critical ground truth within the mobility analysis.

The approach we are exploring allows integrating additional critical information such as precise flood extents, infrastructure damage assessments, or security conditions provided by humanitarian responders, satellites, or other data sources. This closes the gap between steady OSM changes and information that may not be suitable for OSM or just too temporary. The unique strength of our system lies in incorporating these external data sources into routing decisions in near real time, significantly improving the relevance and timeliness of route planning. You will discover how our innovative streaming method updates routing graphs rapidly, maintaining high performance and dynamically adapting to changing conditions without the need to do time expensive routing graph rebuilds.

Implemented within the open-source Openrouteservice (ORS) platform, this solution leverages a robust API that can be publicly accessed or self-hosted, ensuring broad interoperability and no technology lock-in. The development is in preview and access is still provided for humanitarian actors on demand only. This allows us to slowly roll out this functionality by still providing enough resources specifically for crisis-affected areas.

The practical humanitarian benefits are substantial. During major disasters such as Cyclone Idai in Mozambique (2019), and the 2023 Turkey–Syria earthquakes, which destroyed critical infrastructure impacting access for millions, responders urgently required flexible routing reflecting rapidly changing ground realities. Our dynamic routing system enables humanitarian organizations to adapt quickly, improving response speed, safety, and efficiency, thus optimizing limited resources.

Looking forward, the integration of predictive analytics based on accumulated operational data can further enhance humanitarian logistics. Such advancements could proactively identify routes at risk, enabling a shift from reactive to anticipatory routing.
This talk presents the state-of-the-art integration of dynamic mission-critical data and active OSM mapping efforts into humanitarian routing, highlighting its current implementation, practical impact, and future potential for proactive, resilient humanitarian logistics.

This study examines the spatio-temporal dynamics of land use/land cover (LULC) change and its impact on water quality in Ibadan North-West, Nigeria, using remote sensing techniques. Landsat-7 ETM+ (2014) and Landsat-8/9 OLI/TIRS (2023) imagery were analyzed to classify LULC and extract water indices. Water quality was indirectly assessed using the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI), Over the study period, water bodies declined from 89 to 9 hectares, and vegetation cover reduced from 1,315 to 359 hectares. In contrast, built-up areas expanded from 1,450 to 2,486 hectares, reflecting intensified urbanization. The MNDWI, values in 2014 ranged from -0.3687 to 0.0744, while in 2023 they declined to -0.2282 to -0.0129. NDWI values, already negative in 2014 (ranging from -0.3430 to -0.2812), declined further in 2023 (ranging from -0.0101 to -0.0612). These shifts reflect a diminishing presence of strong water signals across both years. Change detection further reveals that NDWI recorded a total water loss of 368.38 ha, while MNDWI showed a smaller loss of 77.21 ha. This contrast highlights that NDWI captured broader, more general water loss including turbid and mixed-pixel areas, while MNDWI, which is more sensitive in urban settings, detected more conservative changes, primarily in clearer water bodies. The combined analysis underscores a clear reduction in surface water extent and quality over time, driven by land conversion and urban encroachment.

Cartographic analysis of Cultural significance of toponyms, and positional accuracy of Openstreetmap data: A case study of Oyo State, South Western Nigeria.

Joseph Muyiwa Olumoyegun and David Olufemi

Department of Geography, Faculty of The Social Sciences, University of Ibadan, Nigeria.

Corresponding author’s email: joephine2011@gmail.com

Abstract
This study focuses on the cartographic analysis of cultural significance of toponym and level of positional accuracy of OpenStreetMap (OSM) data in Oyo State, Nigeria. The ever rapid rise and growth of the usage of OSM data in developing countries with diverse cultural and ethnic compositions has called for the need to give attention to the concerns that have been frequently raised about accuracy and reliability of its data culturally. Since OSM data is collected by volunteers with varying degrees of expertise and access to accurate data sources, data quality can vary widely across regions cultural peculiarities of settlements’ place names (toponyms) is inseparable. The purpose of this study is to cartographically analyse the cultural significance of toponyms, and positional accuracy of OSM data. Toponyms are peculiar to culture of people in a particular geographic environment which can be found in various forms such as Oronyms-name of mountain/hills; hydronyms-name of rivers, lakes or ocean; Urbanonyms-names of cities, towns, villages; and Geonyms- names of geographic features such as mountains, valley, or deserts. The study also paid attention to spatial pattern of settlements, and density of road network across the thirty-three Local Government Areas of Oyo State.
The study employed the use of mixed method approach to collect qualitative and quantitative data. To this effect, both primary and secondary were collected. Secondary data of OSM for Nigeria was downloaded from OpenStreetMap website, and clipped to the administrative boundary of the study area using Political boundary of Oyo State Local Government Areas (LGA) obtained from State Ministry of Lands and Urban development. Ground truthing of missing and misplaced settlements was obtained with Global Positioning System Garmin 76X device with random sampling of settlements through fieldwork constituted the primary data, and supported with Google Earth Pro map. Research work on Yoruba cultural name of settlements provided the compendium of correct spelling of settlements in Oyo State, as well as their changes overtime (toponymy). The various forms of toponyms as outlined above were verified, and those found to be inconsistent with OSM data were quantified and analysed for each LGAs in the study area. Cartographic visualization and mapping. Average Nearest Neighbour statistics was used to analyze the spatial pattern of OSM settlements (places) for each LGA. Similarly, Network analyst was used to analyze the density of road with the measured area dimension of each LGA using ArcMap 10.8 software. Pearson correlation technique was used in to examine the relationship between incorrect place name (toponyms), and positional inaccuracy of settlements (duplication, missing, and inaccurate locations). Observed duplicate Settlements vary across the LGAs.

This study observed that duplicated settlement locations exist which varies significantly across the LGAs. High percentage of settlement duplicated in the same location were found in Ibarapa North, Ona Ara, Ibarapa East, Ibarapa Central, and Saki East LGAs accounting for 33.65%, 28.38%, 27.95%, 25% and 25% respectively. This indicates that a significant portion of settlements in these areas are listed multiple times with different names or data points. In contrast, Ibadan South east, Ibadan North-East, and Ibadan North-West have 0% duplicate settlements, meaning that no duplicate settlement locations were recorded for these areas.

The findings of this study revealed that there is a statistically significant positive relationship (r = 0.704, p = 0.000) between the number of inaccurate settlement locations and incorrect spelling (toponym). This finding indicates that areas with poor positional accuracy are more likely to exhibit spelling errors, and vice versa. Average nearest neighbor analysis confirms that settlements in Oyo State are significantly clustered, as evidenced by the Nearest Neighbour Index (NNI) of 0.596139, highly negative Z-score (-41.556355), with extremely low p-value. Positional accuracy assessments also revealed that 69.6% of OSM settlement data aligns with ground-truth observations. However, overall positional inaccuracy rate of 30.37% was recorded across the thirty-three (33) LGAs of Oyo State. This points to the fact that, there is a notable variation in OSM data reliability. LGA such as Orelope recorded 100% positional inaccuracy, indicating severe mapping deficiencies. This has negative effects on geospatial mapping and analysis in such area. Similarly, LGAs such as Ibarapa North, Akinyele, and Orire exhibit high positional inaccuracies, while others show lower error rates indicating a high level of accuracy of OSM data.

To enhance OSM data quality, this study recommends increased local participation in data contributions, integration of authoritative sources, and the use of automated validation tools. These measures will improve data accuracy and usability, benefiting urban planning, disaster management, and infrastructure development for geospatial analysis as well as community development. The study contributes to the broader Volunteered Geographic Information (VGI) quality assessment field by providing a replicable framework for evaluating geospatial data accuracy and reliability in similar contexts.

Keywords: Toponym, GIS, OSM, Positional accuracy, Cartographic visualization, VGI

As climate change intensifies its impact on agriculture and food systems across Africa, open tools and technologies offer transformative potential for adaptation and resilience. This proposal highlights an innovative approach to enhancing food security in Tanzania by integrating artificial intelligence (AI), drone technology, and open tools such as the Nuru App and remote sensing techniques to support cassava production—a staple crop central to household nutrition and economic stability.

Led by Magnoverata Agriculture Farm in Mwanza, this initiative responds to persistent challenges faced in cassava farming, including infestations from cassava mosaic, brown streak disease, and mites. Traditional pest and disease control methods have proven labor-intensive and inefficient across the farm’s 100-hectare plot. While the Nuru App—an open AI tool developed using thousands of cassava leaf images—improved disease detection at the plant level, its use alone proved insufficient in terms of scale and speed.

To address these limitations, the proposed solution integrates AI-powered analysis from the Nuru App with drone technology. Drones equipped with multispectral and RGB imaging sensors autonomously scan cassava fields, collect real-time data, and transmit it for rapid analysis, enabling early detection and response to plant health threats. This open, scalable solution enhances the farm’s climate resilience by reducing crop losses, improving yields, and optimizing pesticide use and irrigation practices.

Additionally, the project embodies principles of climate justice and participatory innovation by involving local youth and agricultural communities in drone operation and data interpretation. It also supports inclusive knowledge systems by promoting the use of open-source tools that are adaptable to local contexts and accessible to smallholder farmers.

This approach exemplifies how open mapping and AI-integrated tools can be harnessed not only for real-time crop surveillance and decision-making but also as a platform for community-driven resilience strategies. As such, this proposal contributes to broader climate adaptation efforts and serves as a replicable model for other regions seeking sustainable, tech-enabled agricultural solutons

Climate Resilience and Mapping Innovation: Monitoring the Rising Waters of Lake Tanganyika
Lake Tanganyika, one of Africa's Great Lakes and the second-deepest freshwater lake in the world, has experienced unprecedented flooding in recent years—posing serious threats to communities, infrastructure, and ecosystems across Burundi and neighboring countries.
In April 2021, the lake's water level increased to 776.45 meters above sea level, far exceeding its average of 772.7 meters. This anomaly was driven by intense rainfall and extreme weather patterns linked to climate change. The resulting floods overwhelmed shoreline infrastructure, inundated homes and farmland, and displaced thousands of residents.
By April 2024, Lake Tanganyika reached a historic high of 777.2 meters, surpassing its previous record set in May 1964. Areas such as Gatumba and Kibenga in Burundi were particularly hard hit, with entire neighborhoods submerged. Nationwide, over 100,000 people have been forced to flee due to climate-related disasters—primarily floods and landslides triggered by the lake's rising waters.
In response to this escalating crisis, our project demonstrated how drone technology, combined with open mapping tools, can play a pivotal role in early warning systems, disaster preparedness, and emergency response. By rapidly capturing high-resolution aerial imagery and integrating it into spatial platforms, we were able to assess flood-prone zones, support evacuation planning, and aid in real-time disaster response coordination.
This initiative underscores the urgent need for climate adaptation strategies and highlights the power of open geospatial technologies in building resilience for vulnerable communities across Africa.

A practical project to demonstrates how to use the following tools to build lightweight interactive web-based maps: uMap, Overpass Turbo, and OSM data. The session is meant to explore creating story maps, thematic maps, or spatial data driven web portals using open-source tools and open data. Through the talk, we will explore writing a query on Overpass Turbo, based on custom tags and geographic boundaries, export & refine that data in various formats for use in web projects, visualizing the data using uMap, adding layers, custom styles, and user interaction and finally embed the map on a website or integrate it with other tools (like Leaflet.js) for added functionality. During the talk, we will also discuss real-world use cases and explore how these tools can support participatory mapping, civic tech, storytelling, and planning across African contexts.

Now in its third cohort, GeoTE Tanzania continues to scale its impact by integrating OpenStreetMap (OSM) into academic curricula through an immersive five-week Field Practical Training (FPT) program. These sessions, co-designed with educational partners, YouthMappers chapters, and stakeholders such as TomTom and OMDTZ, bring together interdisciplinary cohorts of students to apply geospatial technologies to real-world challenges.

The GeoTE model goes beyond technical instruction, emphasizing collaboration, problem-solving, and community engagement. Students from fields including agriculture, wildlife, forestry, environmental science, and urban planning use OSM data to analyze and address issues affecting Tanzanian communities while supporting sustainable development goals (SDGs). With strong institutional partnerships, such as with Sokoine University of Agriculture, the program embeds OSM training within academic calendars, offering students academic credit and practical experience.

What makes Cohort 3 stand out is its expanded network of stakeholders and professional mentors, creating a richer, more collaborative learning environment. Participants engage in project-based learning, where they receive mentorship on ideation, mapping, data analysis, and community presentations, preparing them to become the next generation of geospatial changemakers.

This presentation will explore the evolution of the GeoTE Tanzania model, share success stories and lessons learned from Cohort 3, and highlight strategies for scaling academic, community, and industry collaborations around open geospatial technologies. Attendees will walk away with practical insights into how OSM can transform education, foster civic engagement, and build resilient local solutions through youth-led innovation.

Current and context-specific geospatial data are critical to plan sustainable land use, establish resilient local food systems, and tackle environmental issues such as desertification, floods, and climate-induced displacement. In Nigeria's Middle Belt region, particularly Plateau State, intensified environmental degradation and conflict have forced thousands of rural farmers to abandon ancestral homelands, resettle in marginal lands, and practice unsustainable land use. These movements go unrecorded, making communities invisible to plan for infrastructure, humanitarian distribution, or climate change adaptation. This study presents a community-led agroecological mapping project that employs OpenStreetMap (OSM) and participatory GIS to map land use, identify restoration opportunities, and advocate for the concerns of displaced farming communities in Bassa and Riyom LGAs of Plateau State.

The general aim of this research was to integrate open geospatial technology and local knowledge in scaling up climate-resilient agricultural practices and improving marginalised rural citizens' visibility within formal development and planning processes. Under a youth-led community mapping process supported by Kitron Green Initiatives (KGI), over 30 young mappers were trained and mobilised in collecting data on degraded lands, existing farmlands, agroforestry fields, water points, and climatic hazards. Using Field Papers, OpenDataKit (ODK), iD Editor, and QGIS, the data was validated with the community and uploaded to OpenStreetMap. The mapping project also incorporated women farmer groups, traditional leaders, as well as displaced persons to ensure inclusivity and contextual relevance of mapped features.

Methodologically, the research employed a mixed-methods participatory research design. Baseline surveys were initially conducted using qualitative tools—focus group discussions, community transect walks, and semi-structured interviews—to attain a deeper understanding of the lived experience of land use change and food insecurity. This was complemented by hands-on mapping using mobile and satellite-assisted data capture. Data quality was assured through iterative feedback loops with local stakeholders and peer review with members of the YouthMappers chapter of the University of Jos.

It mapped a total of 19,200 hectares across five displacement-prone villages and detected 267 points of interest related to sustainable agriculture and community resilience. These included organic farms, community storage silos, animal pens, degraded gullies, and informal settlements. The resulting OSM datasets were converted into dynamic story maps, printed community atlases, and open-access web dashboards for stakeholders including the local government, NGOs, and research institutions. Additionally, the project used a digital agro-ecological vulnerability index based on mapped features, local climatic trends, and farmer interviews—guiding focused interventions such as tree planting, drip irrigation, and composting workshops.

The findings show that participatory open mapping not only improves data coverage in otherwise "invisible" rural areas but also builds agency and digital literacy among community members. Young people and women, who were previously excluded from decision-making, gained valuable skills in geospatial technologies and were able to identify previously unrecognized resources and hazards in their locality. Mapping products were also used in a municipal government climate roundtable to advocate for inclusive budgeting and farmer support. Significantly, integrating OSM data into post-displacement planning allowed humanitarian organizations to better map aid delivery to evolving community structures and risk zones.

Academically, the project contributes to nascent research on community-driven cartography, climate resilience, and data justice in geospatial science. The project demonstrates how the combination of high-resolution open-source mapping technologies and participatory action research can expose spatial inequalities and enable bottom-up climate adaptation. Furthermore, the project confirms that community data—when digitized and mapped—can be powerful evidence for humanitarian response and development planning. The model has replicable potential for other conflict-displaced or climate-stressed agricultural zones in sub-Saharan Africa.

The practical implications are numerous. For OSM communities, the project illustrates how intentional inclusion of displaced and marginalized communities can strengthen the mapping ecosystem and expand use cases beyond urban-focused projects. For scholars, it offers an empirically tested model for the integration of open data in climate resilience planning, particularly in resource-constrained settings. For government and NGOs, it provides a low-cost, scalable example of bottom-up geospatial data capture that can fill holes in national land-use and cadastral systems.

Reproducibility of the research is ensured through the publication of the complete mapping dataset on OSM under the Open Database License (ODbL), with supporting materials—like training manuals, map CSS stylesheets, and dashboard templates—published on GitHub under a Creative Commons Attribution-ShareAlike license. Mapping forms and backend ODK configurations are also shared to facilitate replication in similar settings.

Lastly, this study bridges the gap between geospatial science and community development, employing OSM as an empowering, documenting, and planning tool. The study highlights the role of open mapping in building agroecological resilience and enhancing the visibility of the hidden communities, who are typically marginalized by traditional mapping processes. Through the use of participatory methods and open technologies, the project amplifies voice, increases preparedness, and co-produces knowledge that is both locally embedded and globally reproducible. This paper encourages more collaboration between universities, grassroots movements, and the OSM community to continue to explore the nexus of open geodata, climate justice, and rural livelihoods in Africa.

OpenStreetMap relies on a wide variety of contributions in terms of mapped themes, covered areas, and completeness levels. This flexibility is key to its richness and success. However, it also generates a high degree of data heterogeneity, which is often cited by its detractors or those seeking to minimize its value.
Some services, such as dashboard.ohsome.org and github.com/hotosm/osm-analytics, have attempted to address these concerns about heterogeneity, but they seem to have been discontinued.
This presentation introduces a new approach that analyzes not territories as a whole or a particular theme, but rather the various components that comprise the backbone of homogeneous OpenStreetMap (OSM) data. These components include named places that are linked together and have a known extent. They are also provided with a road grid, essential points of interest, and main buildings. Finally, there are complementary points of interest.

To analyze cities and towns, this approach evaluates what defines their urban areas, such as land use zones and street networks, according to various indicators, such as age of update, geometric accuracy, and coverage. It also provides a quality or completeness index ranging from 1 to 10 with six colors ranging from red to dark green.
Based on these urban areas, the approach also provides a completeness index for the points of interest located there. This index is categorized by type (health, education, other amenities, shops, offices) and surface of the urban area.

These indices highlight significant contrasts between regions and between small towns in the same region. The visual approach to analysis is complemented by the ability to enhance data for objects that can be edited using imagery : a click on the map provides an opening link to JOSM. For objects that require completion in the field, we will present a workflow that uses these analysis layers and OSM applications for Android.

Technically, this approach does not use a dedicated backend served by a separate web service on the frontend. Instead, analyses are automatically produced and shared as thematic maps by country via a spatial data infrastructure (SDI) based on geOrchestra. Each produced analysis takes the form of freely accessible OGC layers (WMS/WFS) and can be used by any OGC client or downloaded in various GIS formats.

The Open Mapping Initiative in Nigeria, driven by Unique Mappers Network- the OpenStreetMap community in Nigeria is pivotal for creating freely and accessible geospatial data to enhance humanitarian aid, urban planning, and disaster response. With 17 YouthMappers chapters, Nigeria fosters geospatial expertise among students, yet volunteer mobilization faces significant hurdles. Limited funding creates a great barrier to effective volunteering, restricting access to essential tools like laptops and smartphones while high mobile internet data subscription cost and unreliable internet connectivity impede data collection and uploads, particularly as students’ upkeep does not cover cost of internet for volunteering projects. Low awareness of OSM’s societal impact, coupled with economic pressures and a weak volunteer culture, discourages consistent participation. Gender imbalances and insufficient leadership further challenge community engagement, limiting the initiative’s scalability. During Industrial Training with Unique Mappers Network in Port Harcourt, I experienced these obstacles firsthand. The prohibitive cost of mobile data curtailed contributions to OSM due to lack of funding and donation to provide free internet access at the mapathon center,where student volunteers mobilized to be engaged with various humanitarian response mapping projects. Mobilizing volunteers was daunting, as many prioritized income-generating opportunities over unpaid mapping efforts. Despite these setbacks, open mapping remains vital for youth geospatial skill empowerment as well as addressing geospatial data gaps in local challenges, such as flood mapping and urban development. To surmount these barriers, increased funding of Local community NGOs like Unique Mappers Network, targeted OSM data awareness campaigns and mapping projects ,as well as collaborations with academic, government agencies and international agencies i are essential to bolster volunteer engagement and elevate the quality of Nigeria’s geospatial data, unlocking its potential for transformative impact using the OpenStreetMap.

Keywords: OpenStreetMap, Unique Mappers Network, Geospatial data, volunteer mobilization, Nigeria

The rapid growth of the OpenStreetMap community in Africa is a tremendous success, leading to numerous training, mentorship, and local initiatives. However, this success can also create a fragmented landscape for volunteers. How does a new mapper find their way? How does an experienced contributor become a community leader?

This talk introduces the Humanitarian OpenStreetMap Team's "Connect & Learn" program, a strategic initiative designed to answer these questions by unifying our community engagement efforts. We will share our journey of consolidating multiple programs—from mentorship to expert volunteer networks—into a single, cohesive ecosystem. The goal is to create clear, accessible, and scalable pathways that support a contributor's journey from their first edit to becoming a community champion.

We will delve into the core components of the "Connect & Learn" framework, including a centralized training platform, structured mentorship opportunities, and a network for deploying skilled volunteers where they are needed most. By creating shared resources and pedagogical standards, the program aims to break down silos, foster greater collaboration between projects and hubs, and empower local communities with the tools they need to lead and sustain their own growth. We will share how we are designing this program to be measurable, meaningful, and inclusive, ensuring it serves our diverse global community effectively.

Overview and Rationale

Across Africa's rapidly growing cities, communities remain invisible in formal planning systems despite being well-represented in OpenStreetMap (OSM). While citizens map what matters to them, the analytical potential of this rich OSM data remains largely untapped—especially for education, community advocacy, and understanding urban inequalities.

geo3D

geo3D is an openly licensed Python framework that transforms OSM building footprints into interactive 3D city models and spatial analysis tools. It bridges the gap between grassroots mapping and data-driven urban insights, making sophisticated spatial analysis accessible to educators, NGOs, and community organizations across Africa.

geo3D is timely and novel in that it:

• Connects grassroots mapping with spatial data science;
• Produces ISO-conformant Level of Detail 1 (LoD1) models and lightweight pseudo-3D html visualisations from OSM building footprints;
• Enables value-added analysis like population estimation and BVPC to examine spatial inequality;
• Prioritises pedagogical transparency and reproducibility through open Jupyter Notebook;
• Embeds feedback loops between learning and OSM data improvement by flagging topological errors in buildings for user correction at the source;
• Is designed specifically for place-based learning at the neighbourhood level in African cities and settlements.

This workshop builds on a successful pilot in Cape Town, South Africa, geo3D was used to model local environments and uncover patterns of overcrowding, and housing inequality.

Structure and Activities

Duration: 1.5–1.75 hours
Format: Hands-on workshop with semi-structured demonstrations, peer learning, and Q\&A

• Introduction and Framing (10 minutes): Welcome and orientation to the workshop objectives with overview of geo3D.
• Live Demonstration and Guided Hands-on Activity (80 minutes): Work-through 4 Jupyter notebooks (3D modeling, spatial analysis --population estimation and Building Volume per Capita and visualization.
• Wrap-up and Community Building (15 minutes): Q&A, sharing ideas, and invitation to collaborate on geo3D’s GitHub repo and share derivative research and projects

OSM Alignment and Thematic Fit

geo3D is powered by OpenStreetMap. Its entire workflow—from extraction of building footprints to modelling and metric generation—is designed to extend the value of OSM data into educational, analytical, and advocacy contexts. The tool is intended not only to use OSM, but to enhance and contribute to it: participants are encouraged to detect and correct topological errors in OSM building data through geo3D's built-in diagnostic functions.

Thematically, the workshop aligns strongly with:
- Mapping for social justice and inclusion: by enabling visibility of housing inequality and under-resourced communities.
- Education and capacity-building: by bringing reproducible OSM workflows into classrooms and local organisations.
- Data quality and community verification: by supporting feedback loops between analysis and source improvement.

Learning Outcomes

By the end of the workshop, participants will:

1. Understand how to generate and validate 3D City Models from OSM data using open tools.
2. Be able to run and adapt geo3D to perform spatial analysis.
3. Learn how to estimate population and BVPC from building data and interpret results in local contexts.
4. Gain insights into reproducible workflow design for teaching, research, or community engagement.
5. Build confidence to lead similar workshops in their own institutions or communities.
6. Leave with links to reusable resources, sample data, and open documentation.

Target Audience and Requirements

Audience:
Primary: educators, community organizers, NGO's and development practitioners seeking accessible tools for spatial analysis and civic engagement. Secondary: OSM contributors interested in extending their mapping impact into advocacy and education

Requirements:
- Participants: Basic familiarity with GIS concepts is recommended but not mandatory. (Skill level: beginner - intermediate)
- Bring: Participants should bring laptops. Installation instructions and sample datasets will be made available.
- Room Requirements: A projector and reliable internet connection are essential for live demonstrations and collaborative exercises.

Reproducibility and Open Access

Participants will leave with a full reproducible pipeline they can adapt, reuse, and share. The workshop models best practices in open science and computational reproducibility.

Building and leading OpenStreetMap communities requires passion and dedication, but too often leads to volunteer burnout and unsustainable practices. Drawing from personal experiences, this interactive workshop explores whether it's possible to build thriving mapping communities while maintaining personal well-being, and if so, how.
This session combines practical frameworks with honest discussions about the realities of community leadership. We'll explore various approaches to sustainable community leadership, including distributed leadership models that prevent over-reliance on individuals, and strategies that are effective within African contexts.
We would like the workshop to create space for both emerging and experienced leaders to share challenges, learn from each other's experiences, and develop strategies for building resilient communities. Through small-group discussions and interactive exercises, attendees will create personalized sustainability plans and connect with one another.

Open mapping has emerged as a lifeline, and not a tool for data, in areas affected by conflict, displacement, and disaster in Africa. It keeps people on the map, connects them to lifesaving aid, and fosters improved coordination between humanitarian responders and local players. In this panel discussion, I share first-hand experience and learning from ongoing research and mapping activities using OpenStreetMap (OSM) and GIS technologies to support internally displaced persons (IDPs) in Northeastern Nigeria, a region that is home to one of the longest-running humanitarian crises on the continent.

Since 2009, the insurgency and related violence by Boko Haram have displaced over 2.5 million people in Nigeria's northeast. It is where most reside in camps or host communities that have limited access to basic healthcare, clean water, and infrastructure. There, open and collaborative mapping have played a critical role in bridging the information gap connecting humanitarian responders with populations whose needs are likely to be opaque in government data systems.
Drawing from my experience of creating the Community Positive Health (CPH) Index and previous work of promoting spatial data initiatives with the input of OpenStreetMap contributors, GRID3, and ArcGIS platforms, I present to present three crucial issues during this panel:

1. Mapping as Visibility: Making Displaced Communities Count
   In crisis environments, invisibility too often equals exposure. The majority of IDP camps and informal settlements are not represented in national data sets, so they are underrepresented for aid access. By participatory data collection and open street maps contribution, we've been able to trace the physical size of camps, health centers, road accessibility, and water points so that frontline responders can visualize gaps and intervene.

Our project combines field data gathering with Survey123 and ArcGIS Field Maps leveraging OSM basemaps to identify where services are and aren't. In Borno and Adamawa States, for instance, it helped local NGOs understand how far women in IDP camps have to travel to access maternal health care, which in turn influenced the placement of mobile clinics.

1. Local Mapping Networks as Connectors
   Open mapping is not about maps; it's about people. One of the most powerful lessons learned in the field is the role that local YouthMappers chapters, humanitarian volunteers, and displaced persons themselves have in initiating mapping projects. These mappers are intermediaries between communities and organizations translating needs into spatial data, and spatial data into action.

For example, Nigerian indigenous mapping communities assisted in mapping roads, trails, and facilities in areas where satellite data could not fully represent. Their contextual knowledge was essential in confirming OSM data and pinpointing informal health facilities not included in government records. In others, young displaced people were taught to collect spatial data, not only giving them a voice but also providing them with a skillset and returning them to society.

1. Ground and Coordination Challenges
   Even within the rich tool set and talent pool of the open mapping community, coordination challenges between the global actors and grassroots base become very real. Global organizations bring resources without context, while local mappers do not necessarily lack technical tool access or organized support.
   I will present descriptions of working in this nexus overcoming data interoperability challenges, access constraints, language barriers, and ethical issues. For instance, while collecting geospatial data about vulnerable populations like women or children, community consent, privacy, and data protection norms had to be diligently observed, especially in areas of conflict.

We also had the issue of preparedness of data. When there are floods or an outbreak, time is of essence. Mapping initiated during a crisis is already too late. This is where pre-crisis mapping gains importance—having ready OSM Basemaps of camps, roads, and facilities means responders aren't spending valuable hours on orienting themselves.

1. Long-term Resilience Through Open Data
   Perhaps the most important lesson from the frontlines is that open mapping builds resilience after disaster. The maps don't just guide emergency response they inform policy, planning, and investment far beyond the news cycle's duration. For example, the CPH Index project is being developed as a reusable platform for governments and NGOs to find underserved populations, track change over time, and model interventions (e.g., location of new health facilities or road upgrades).

Therefore, mapping is an empowering process. It creates a lingua franca across communities and institutions. It surfaces unarticulated suffering. And it generates accountability.

Planned Contributions to the Panel
Throughout this roundtable, I'll share the following:
Field experiences of IDP camp and health facility mapping in Northeast Nigeria
Case studies of OSM-based coordination among local mappers, humanitarians, and government partners
Practical lessons and solutions in data collection, ethics, and multi-stakeholder engagement
A demonstration of how mapping outputs (dashboards, maps, story maps) were leveraged to inform humanitarian response
Reflections on scaling and sustaining open mapping networks in low-resource settings

Closing Reflection
As co-founder of Agape Global Health and Education (AGHE), a nonprofit focused on mapping health vulnerabilities and improving access for underserved children and families, I have worked directly with local stakeholders to co-create spatial tools that guide humanitarian action and strengthen community resilience. In times of humanitarian crisis, mapping has been more than a technical feat it has been an enabler, a facilitator, and a tool for justice. When people map their own lives, and when agencies value and respond to the data, we begin to build collaborative systems able to act to crisis and plan for recovery.

I would like to use this panel discussion to promote a greater appreciation of the effort that goes into building those systems, and to be able to relate to others who are working to plot a more equitable future for Africa's poorest.

OpenStreetMap has become an essential tool for understanding the world, especially in regions where commercial and governmental data are limited. At TomTom, we believe that the best maps are made together. In this session, I will share how TomTom is working hand-in-hand with OSM communities across Africa to build high-quality, up-to-date, and inclusive maps that serve both local needs and global technologies.

With the high costs and limited access to high resolution aerial imageries, there is a growing need to capacitate local mapping communities with the prerequisite technology and skills to create aerial imageries at a cost effective rate. The Drone Tasking Manager, OpenDroneMap and low cost drones are essential in achieving this feat.

HOT, alongside Freetown City Council, OpenStreetMap Sierra Leone and CODOHSAPA / FEDURP have just completed a city-wide drone imagery acquisition campaign, using an open community drone model, where city residents flew, processed and uploaded 75km2 of high resolution aerial imagery and 3d models for Freetown’s urban area.

This workshop would introduce participants to the Freetown campaign, the technology used to and help them to plan and execute on their own city wide community drone mapping campaigns

Participants will experience how to design and build flight plans at a city scale, transfer flight plans to drones, and then download and process the resulting images.

As Africa’s cities grow rapidly, the need for informed planning, accessible transport systems, and smarter infrastructure becomes more urgent. This workshop introduces participants to practical geospatial analysis using Python and OSMnx, a powerful open-source tool that allows anyone to extract, visualize, and analyze street networks directly from OpenStreetMap (OSM).

Participants will learn step-by-step how to download real-world urban road networks, perform routing and network analysis, and generate useful insights that support decision-making in transport, accessibility, and sustainable urban development. By focusing on real examples from Tanzanian cities such as Dar es Salaam or Dodoma, this session turns complex geospatial problems into simple, actionable workflows.

Whether you are a planner, analyst, student, or civic tech enthusiast, this workshop will empower you to use open data and code to map the future of your city.

Overview

In this 90-minute session, OpenGeoCity Tanzania will guide participants through the entire process of performing urban spatial analysis using the Python programming language and OSMnx — a Python library designed to work directly with OSM data.

You will not only learn how to visualize road networks, but also how to measure urban form, model accessibility, and analyze infrastructure gaps using real-time geospatial data. This workshop brings together the power of open data, open-source software, and local knowledge to build smarter and more connected communities.

What You Will Learn:

By the end of this workshop, you will be able to:

➤ Access OpenStreetMap Data with Python

Learn how to download roads, buildings, and key features using simple code.

➤ Visualize and Explore Urban Networks

Create basic maps and explore the layout of streets and city structure.

➤ Analyze Connectivity and Accessibility

Measure how well areas are connected and find the shortest routes between places.

➤ Apply Insights to Real Urban Challenges

Use open data to support better planning, transport, and service delivery.

Who Should Attend:

This workshop is designed for:

➤ Urban Planners and Transport Specialists

➤ GIS Analysts and Developers

➤ City Managers and Government Data Units

➤ Students and Researchers in Urban Studies

➤ Community Mappers and OSM Contributors

➤ Anyone interested in building data-driven cities

Introduction/Background
The increasing frequency of climate-induced disasters, such as floods and droughts, poses serious challenges to underserved communities across Africa. These challenges are exacerbated by infrastructural gaps, limited access to spatial data, and a lack of locally informed decision-making tools. While traditional mapping often fails to capture the dynamic nature of community vulnerabilities, open mapping—especially via OpenStreetMap (OSM)—offers a participatory and scalable alternative for resilience planning. Despite its potential, there remains a gap in systematically integrating artificial intelligence (AI), machine learning (ML), and community-centric data into open mapping workflows to generate real-time, actionable insights.

Main Aim and Purpose of the Study
This study presents a methodological framework that integrates AI-assisted image classification, open geospatial tools, and community-driven data collection to improve spatial awareness, resource allocation, and emergency preparedness in vulnerable regions. The research specifically evaluates how open mapping, powered by AI and community collaboration, enhances flood response, healthcare delivery, and environmental monitoring in under-resourced areas of Nigeria, South Africa, and Kenya.

Methodology
Our approach combines multiple methodologies:

Data Acquisition: Using drone imagery and Sentinel-2 satellite data over targeted regions, including flood-prone and informal urban settlements.

AI/ML Integration: Applying convolutional neural networks (CNNs) and supervised classification models (e.g., Random Forest, U-Net) to extract features like road networks, buildings, vegetation cover, and flood extent.

Community Validation: Engaging local mappers and community leaders in YouthMappers chapters to validate automated outputs via MapSwipe and Field Papers.

Toolchain: Leveraging QGIS, JOSM, Google Earth Engine, and the OSM iD editor alongside custom Python scripts for model deployment.

Quality Assessment: Performing intrinsic and extrinsic quality assessments using metrics such as positional accuracy, semantic accuracy, and completeness based on ground truth surveys and authoritative data sources.

Key Findings
The integrated workflow improved map coverage in three pilot regions by over 70%, while reducing the time required for feature mapping by 60% compared to manual-only methods. In areas with recurrent flooding, risk zones were identified with 92% classification accuracy, enabling proactive community evacuation planning. Engagement with community mappers increased map validation rates and fostered digital inclusion, especially among women and youth. The framework also demonstrated the capacity of AI-augmented mapping to support real-time decision-making during emergencies, with significant potential for scalability across other African countries.

Scientific Contribution and Practical Benefits
This research contributes to the growing body of knowledge on AI-enhanced participatory mapping by:

Presenting a reproducible, open-source mapping workflow that integrates machine learning with local knowledge.

Demonstrating how AI can complement rather than replace human mappers in producing high-fidelity, inclusive spatial data.

Providing insights into the sociotechnical challenges of implementing such systems in low-resource settings (e.g., power outages, digital literacy gaps).

Highlighting how open mapping can bridge the gap between geospatial technology and humanitarian resilience planning.

All scripts, data, and trained models will be published in a GitHub repository under an open-source license to ensure reproducibility. Data outputs will be uploaded to OpenAerialMap and OSM for community use, while metadata and evaluation protocols will be documented in the Zenodo repository.

Implications for the OSM Community
The results show that AI-assisted mapping, when combined with inclusive community practices, offers an effective pathway for increasing the utility, adoption, and sustainability of OpenStreetMap in Africa. The approach provides a scalable solution to both routine and disaster mapping in settings with limited resources. By fostering knowledge exchange between researchers, local mappers, and humanitarian actors, this study opens new directions for collaborative geospatial innovation and ethical data governance in Africa’s mapping ecosystem.

Keywords: OpenStreetMap, AI-assisted mapping, disaster resilience, participatory mapping, satellite imagery, YouthMappers, QGIS, open geospatial science, humanitarian response, African data innovation

The Open Mapping Gurus are more than just skilled mappers—they are trusted local leaders, mentors, and catalysts for community resilience through open data. They are the ones we activate in times of disaster, who rally communities for climate action, and who champion inclusive mapping where it's needed most. As we move from short-term project engagements to long-term, sustainable community impact, we must also grow this powerful network—starting with identifying and supporting the next generation of Gurus.

This workshop invites participants to take part in the next chapter of the Open Mapping Guru movement: expanding the model beyond Asia-Pacific and growing a vibrant network in Africa. The session draws from the Asia-Pacific Open Mapping Hub’s 2025–2030 Community Building Strategy, while exploring how its principles—local leadership, inclusive participation, and data for community action—can be adapted to African contexts and realities.

With early interest from mappers in countries like Nigeria, Kenya, and Uganda, and growing momentum for cross-regional mentorship, this is the moment to scale the Guru model. The session will explore:

What makes a strong Open Mapping Guru?
How can we recruit, train, and support new Gurus in Africa?
What regional or global challenges can Gurus help address together?
How do we sustain Gurus beyond projects—through leadership development, recognition, and peer networks?

Participants will use interactive frameworks, reflection tools, and community stories to:

Identify opportunities to recruit and grow Guru circles in their countries
Align their community needs with the regional strategy goals
Explore ways to collaborate across borders and continents
Build a roadmap to support locally driven, globally connected Guru communities

This session is not just a training—it’s a recruitment rally, a movement-building moment, and an invitation to help shape the future of the Open Mapping Guru project in Africa and beyond. Join us if you're ready to lead, grow, and bring others with you.

Sudan is in the midst of a complex and destructive war that has all but destroyed its urban infrastructure and left millions of its people without a place to call home. The capital, Khartoum, has been particularly devastated with unparalleled destruction and disruption of essential services. In this context, timely, precise, and open geospatial data have emerged as a critical resource for humanitarian response and urban recovery planning. OpenStreetMap (OSM), a worldwide collaborative mapping platform, seems to be a good base for such activities. This paper examines the applicability of using Open Street Map (OSM) data for mapping urban infrastructure and population distribution in Sudan conflict zones.
This study offers a systematic methodology to evaluate, process, and leverage OSM data for development planning and decision-making in the context of conflict and post-conflict.

This study has two main aims, to assess the spatial completeness and reliability of OpenStreetMap (OSM) building versus health infrastructure coverage across Khartoum and neighborhood and to illustrate how OSM building and health infrastructure data can be integrated with population, remote sensing, and conflict event data to inform targeted humanitarian response and reconstruction efforts. A second objective is to assess how community-led mapping activities and workshops contribute to enhancing the quality and capacity of local mapping activities and operations.
We adopted a methodology that combines spatial analysis, empirical evaluation, and participatory mapping practices. First, we extracted OpenStreetMap (OSM) building footprints and health-related features (e.g., hospitals, clinics, and pharmacies) using the Overpass API and the Humanitarian OpenStreetMap Team (HOT) export tool. We then compared these datasets with historical pre-conflict basemaps and third-party authoritative sources, when available. We evaluated completeness, positional accuracy, and attribute quality through visual inspection and quantitative spatial metrics.
A central component of our approach was organizing local mapping workshops. In partnership with universities, humanitarian NGOs like Khartoum Reconstruction Initiative (KRI), and volunteer mappers in Sudan and the diaspora, we held these workshops, which focused on mapping missing infrastructure in OpenStreetMap (OSM), validating existing features, and training participants in using geospatial tools for crisis mapping. There was a strong response from local mappers, particularly youth and university students. We documented how this participatory model contributed to data enrichment and capacity building in digital cartography and open data literacy.

Our analysis revealed key results, including over 150,000 building footprints and more than 500 health facilities tagged in OSM within Khartoum state. While urban centers showed relatively high completeness, peri-urban and rural areas exhibited considerable data gaps, particularly in the classification of public infrastructure and emergency services. Spatial overlays with conflict zones showed that many high-density residential areas had significant infrastructure damage, which was corroborated by satellite imagery. Our analysis also showed that many previously mapped health facilities were now inaccessible or damaged, highlighting the urgent need for updated data collection.
Through a comparative analysis of raster land cover data from 2019 and 2022 (TIF), we calculated pixel-based change detection using ArcGIS Pro’s Raster Calculator and statistical tools. This enabled us to identify areas with gains (where land cover increased or improved), areas with losses (where land cover or buildings were destroyed), and areas with no change. We visualized these classes through bar charts using Matplotlib and exported them as CSV summaries. The gain-loss-no-change classification communicated spatial trends to decision-makers and humanitarian agencies.
This study makes several scientific and practical contributions. From a scientific standpoint, it demonstrates the feasibility of using volunteered geographic information (VGI), such as OpenStreetMap (OSM), in complex, resource-limited, and crisis-affected environments. The study also proposes a reproducible, scalable methodology for evaluating OSM completeness, performing raster-based land change analysis, and integrating multiple spatial datasets to inform humanitarian responses. Our approach emphasizes reproducibility; all scripts, data sources, and analysis tools are openly available under open licenses, and our methodology is documented step by step for replication.

From a practical standpoint, this work supports humanitarian organizations by providing them with reliable spatial products and analytics derived from OSM data. It also strengthens local capacity by training communities in mapping tools and geospatial thinking. Training materials, workshop models, and mapping protocols developed through this initiative have been adopted by organizations such as Map4Sudan, HOT, and UN agencies working in the region.

In terms of impact, the project has demonstrated that open mapping can be an essential component of crisis response and recovery. By enabling community members to participate in data creation and verification, the project has increased trust in open data and promoted civic engagement. The project has also laid the groundwork for a broader digital resilience strategy in Sudan and other conflict-affected African countries, where official data may be outdated, unavailable, or politically sensitive.
Integrating scientific spatial analysis with community-based mapping demonstrates the power of OpenStreetMap (OSM) as not just a map, but also as a living, adaptive infrastructure for crisis resilience. Thus, OpenStreetMap should be recognized as a strategic digital asset and integrated into national spatial data infrastructures (NSDIs), urban planning frameworks, and emergency response systems.

Future work will include more in-depth assessments of OSM temporal dynamics, using artificial intelligence for damage detection based on OSM basemaps and satellite imagery, and developing real-time dashboards for humanitarian coordination. We also recommend that academic and humanitarian institutions collaborate to incorporate participatory mapping into school and university curricula to foster sustainable mapping ecosystems across the continent.

Keywords: OpenStreetMap, Sudan conflict, Khartoum, buildings, health infrastructure, population mapping, humanitarian GIS, urban resilience, VGI, collaborative mapping, geospatial analysis, crisis response, post-conflict recovery.

L’atelier avait pour objectif de permettre aux participants de découvrir et maîtriser les bases de QGIS, un logiciel libre de système d’information géographique (SIG).

Contenus abordés :
- Introduction aux SIG et à QGIS
- Interface du logiciel : menus, barres d’outils, panneau des couches
- Importation et visualisation de données (vecteur et raster)
- Symbologie : personnaliser l’apparence des données
- Outils de sélection, de mesure et de navigation
- Création et édition de couches vecteur
- Utilisation des outils de géotraitement de base
- Mise en page cartographique (composer une carte imprimable)

Objectifs atteints :
- Savoir charger et lire une couche SIG
- Comprendre les principaux formats (SHP, GeoJSON, etc.)
- Réaliser une carte simple avec légende et titre

Méthodologie : Formation interactive avec exercices pratiques et cas concrets sur les zones inondable de Niamey Niger.

In humanitarian, disaster, crisis, and many further contexts, timely, accurate and relevant geospatial information is often unavailable, outdated, or misaligned with on-the-ground realities. Latest technological developments and data-driven concepts are enabling us to capture the world in unprecedented detail- with ever-growing volumes of data, promising greater resolution and coverage. But can we truly trust global models that lack local insight?

Research and real-world project examples from around the globe send a clear message: when communities on the ground are not involved, estimates, assessments, and decisions often miss the mark. This can lead to misguided — and sometimes even harmful — outcomes, with serious consequences for the very people and landscapes affected.
So why not turn to those who know the terrain best? Local insights and validation isn’t optional — it’s essential. And the good news? There are practical tools and approaches that make it easy to involve local communities in meaningful ways.
One of them is the Sketch Map Tool (SMT): an open-source web application developed by the Heidelberg Institute for Geoinformation Technology (HeiGIT) and the GIScience Research Group at Heidelberg University to bridge the gap between expert geospatial analysis and community-based knowledge. Driven by the aim to develop a low-tech approach to capture local insights, that does not require previous training or tech knowledge and equipment, apart from map reading and access to a phone or camera.

SMT offers a low-barrier, intuitive platform for communities, NGOs, and responders to express local knowledge, risks, needs, and perceptions through freehand sketching — even in places where formal mapping data is sparse or incomplete.

Inspired by and building on fieldpapers, it allows users to draw spatial information directly onto a paper map using pens, to then scan or photograph the marked Sketch Maps, upload the pic/scan to the SMT website and download the pen drawn markings of the Sketch Maps in different geodata formats (raster data as GeoTIFF, vector data as a GeoJSON file). Through the use of paper maps, accessibility is enhanced and engagement is possible even in offline or analogue settings. This access is further supported through the multi-lingual setup of the SMT website, which currently contains German, English, French, Spanish and Czech, with more languages being planned.

Beyond capturing tangible features like buildings, roads, waterbodies or landmarks, SMT also enables the collection of soft or intangible data — such as community concerns, perceived risks, flood-prone areas, informal settlements, and community assets or locally relevant landmarks — that are again mainly missing from conventional datasets. These maps, therefore, serve not only as a tool for data collection but also support participatory discussion processes that drive inclusion and empowerment.

What role does Open Street Map play for the SMT?
When the Sketch Maps are generated by users, they can choose from a variety of basemaps, including OpenStreetMap (OSM), satellite imagery, or other custom layers. As these base maps serve as orientation, the better and more detailed the base map, the better and more accurate marking with pens can be.

SMT is integrated with the ohsome (OpenStreetMap History Analytics) dashboard, enabling users to visualise OSM data coverage and quality over time for specific regions. When a user selects an area of interest in SMT, it is automatically transferred to the ohsome dashboard, where an analysis of the completeness and recency of data in that area is performed. All analysis parameters can be adjusted to suit the specific use case.
This integration provides valuable insights into the suitability of OSM base map data for field data collection, helps identify existing data gaps, and supports targeted mapping efforts to improve data quality. Such analysis is crucial for ensuring reliable map-based orientation in the field, as outdated or incomplete map data can lead to misorientation, which in turn can negatively impact the accuracy of collected field data.

In previous use cases, these insights have helped ensure that the OSM database is improved directly by local communities or by organising mapping events such as mapathons to engage additional contributors.

And how does AI support the SMT users?
HeiGIT is making use of AI-based feature detection to support automatic recognition and digitisation of drawn features. Machine learning models are utilised to interpret both hand-drawn maps and scanned paper sketches, converting them into structured geospatial data while preserving the original community input. The models have been improved and trained with thousands of Sketch Maps to ensure that the drawings are captured as realistically as possible.
This fusion of low-tech data collection with high-tech processing empowers local actors without placing technical demands on them. The Sketch Map Tool is further publicly available at https://sketchmaptool.heigit.org and is designed to function well even in low-bandwidth or offline environments.

What other developments are down the line?
Capturing local data and ensuring that community insights are collected sustainably — without reliance on external data providers — requires bottom-up approaches.
In this spirit, SMT will soon integrate OpenAerialMap (OAM), enabling the use of recent satellite and, importantly, drone imagery as background layers for sketching. This integration allows users to upload their drone imagery to OAM and access it directly within SMT, supporting more detailed, timely, and locally targeted mapping efforts.

As development continues, we invite the OSM Africa and humanitarian mapping communities to test, contribute to, and collaborate on real-world applications of SMT. We especially welcome partnerships with local mapping groups, Red Cross and Red Crescent societies, and anticipatory action actors working in climate-vulnerable regions.

What can participants expect during the workshop?
The Sketch Map Tool demonstrates the power of pairing inclusive, analogue-friendly community engagement with the latest advances in AI and geospatial technology. By enabling local actors to capture what they know, see, and experience — and by supporting them with powerful analytics behind the scenes — SMT fosters more relevant, representative, and timely geospatial information. It empowers communities to make their voices visible and ensures that their insights inform real-world decisions in humanitarian and development contexts.
We look forward to sharing this work with an intro talk followed by step-by-step walkthroughs using real-world examples of previous and current SMT users, from humanitarian, risk and vulnerability mapping to mapping of cultural landmarks, and enabling participants to directly conduct the steps themselves.

We would love to have this opportunity to enable us to learn about the ideas and challenges of the community and strengthen collaboration with the OpenStreetMap Africa network.

The transition away from fossil energy sources faces a major bottleneck in the extension and modernization of the electrical grid. Failing to expand the grid fast enough could increase global emissions by about 12 % in 2050, compared to a pathway that supports rapid grid modernization and extension (IEA 2023).
Furthermore, in Africa only around 53 % of the population had access to electricity in 2023 (World Bank 2024). In many African countries, data on electrical infrastructure is outdated, incomplete, or not publicly available, presenting a significant barrier for governments, utilities, and planners.

The Case for Open Grid Data in OpenStreetMap in Africa:

Open grid data ensures that infrastructure planning is more inclusive and cost-effective: datasets can be cross-checked, reused, and improved collaboratively, giving policymakers and planners a reliable foundation for decision-making.

Where official data is unavailable, OpenStreetMap often becomes the de facto platform for mapping the grid—but progress there can be limited by outdated or low-resolution satellite imagery provided by services such as ESRI and Microsoft, particularly in some African countries. Therefore, having local communities involved is the best way to maintain and improve this data in OpenStreetMap in the long-term.

Since OpenStreetMap is both editable and collaborative, local communities, NGOs, and governments can contribute directly—filling gaps, correcting errors, and improving data quality. For example, the YouthMappers initiative in Sierra Leone enabled students and organizations to map the power grid, helping electricity providers reduce planning costs and accelerate deployment.

Expanding access to electricity is vital for poverty reduction, economic stability, and climate resilience. However, one of the greatest obstacles to grid expansion remains the lack of reliable data. In some cases, information is even withheld due to perceived security concerns, echoing outdated “security through obscurity” practices.

Moreover, open grid data is instrumental in identifying off-grid communities that could be connected to national networks, helping to target interventions and investments (Arderne et al., 2020), particularly in contexts where official data is scarce such as in many African countries.

Open data on energy infrastructure supports not only decarbonization and electrification, but also broader human development outcomes, including: innovation and entrepreneurship, improved healthcare and education services, enhanced opportunities for women and girls, especially where clean cooking access is introduced.

Additionally, by relying on open-source data from OpenStreetMap, governments and local authorities can build high-quality datasets without the cost of proprietary sources. For instance, the U.S. Department of Energy’s “Electric Energy Infrastructure Data” project achieved estimated savings of 65 % (≈ 2 million USD) over proprietary datasets.

Furthermore, OpenStreetMap grid data is increasingly being used in energy systems modelling activities. For example, PyPSA Earth, an open-source global energy system model, uses OpenStreetMap grid data as the foundation for constructing its electricity grid network, and has been used in many African contexts such as a net-zero planning study for Nigeria (Parzen et al. 2023).

MapYourGrid initiative:

Therefore, we formed the MapYourGrid initiative in 2025, where we aim to map the world’s electrical transmission grid on OpenStreetMap, by using tools and strategies we have developed, and by collaborating with local communities.
In the past few months, we have standardized, optimized, and partially automated the grid-mapping process to boost both engagement and accessibility.

Since volunteers have already mapped most of the global transmission grid in OSM, our focus is on connecting and training these mappers more effectively—especially to tackle the final 30 %, which is hardest to capture.

Therefore, MapYourGrid has: established a centralised communication channel that multiplies training and support, generated a wealth of innovative ideas from community members, and laid the groundwork for long-term data maintenance, critical as global grid length must more than double by 2050 and over half of existing lines will need upgrading or replacement.

Moreover, we have built a website with a tutorial, an interactive world map with tools built inside to map effectively, and will produce many high-quality videos. Furthermore, as to empower local communities in Africa, we will be making video tutorials in English, French, Spanish and Portuguese.

In the near-future, we will run at least three continent-wide mapping sprints, turning grid mapping into a social, game-like experience that motivates both new and experienced contributors. We will also provide advanced technical training materials, such as written guides and videos for more experienced grid mappers. This will help beginner mappers evolve to advanced levels, greatly improving data accuracy and completeness.

Finally, to date, our team has mapped over 180,000 towers (approximately 58,000 km of power lines), including more than 17,000 towers across Africa, such as in Mozambique, Nigeria, Tanzania, Zambia and Kenya. However, we intend to increase our collaboration with communities all around Africa, and together map the electrical grid in OpenStreetMap.

Launched in 2022 as a pilot phase with the vision of building the capacity of OpenStreetMap communities on OpenSource tools in general and OpenStreetMap in particular, HOT's Community Working Group Mentorship Program has evolved over the years with the first and second cohorts held in 2023 and 2024 respectively. In addition to the capacity-building component, which contributes to the personal and professional development of participants, the programme also provides a platform for exchanges and networking for global communities, and fosters the emergence of leaders who contribute to the creation or consolidation of Open Mapping communities.

As a result, the program has empowered 200+ people (mentors/mentees) and 500+ people outside the program with Open Source technologies, limiting technical gaps between communities and enabling effective disaster response. The program also fostered the emergence of new leaders in several communities where the Open Mapping culture had not yet been established. 27 projects were developed by the participants on various themes.

This talk will highlight:
- The design and goals of the program
- Thematic focus areas and mentorship methods
- Outcomes from previous cohorts (statistics, testimonials, case studies)
- Challenges and lessons learned
- The role of mentorship in bridging knowledge gaps and increasing inclusion in mapping

Target audience:
- OSM community leaders and mappers
- Local chapters and YouthMappers
- Organizations and individuals interested in community development and mentorship
- Anyone seeking to replicate mentorship initiatives in their region or support it.

OpenStreetMap is often built with strong community participation, yet too often, the communities whose environments are mapped don’t get to see or use the final products. In this talk, I’ll reflect on real experiences from Tanzania where maps were created to support flood resilience, litter monitoring, and public service access, and examine whether and how those maps were shared back with the people who contributed.

I will share lessons on what has worked, including printed maps shared through ward leaders, participatory validation sessions, and local cleanup initiatives as well as challenges around closing the feedback loop. I’ll also propose practical, low-tech strategies for making community maps more accessible, understandable, and usable by local people.

J'ai nommé ma solution InodZéroRisque.
Mon projet, InodZéroRisque, est une application de système d'alerte précoce conçue pour réduire les risques d'inondation.

En quoi consiste le projet ?
L'objectif principal d'InodZéroRisque est de prévenir et d'atténuer les impacts des inondations en fournissant des informations rapides et localisées aux populations. L'application se base sur l'utilisation des données OpenStreetMap (OSM) pour identifier les zones à risque, cartographier les réseaux hydrographiques et les infrastructures, et ainsi alerter les communautés avant que les inondations ne se produisent.

Title: Power to the People: How Africa Can Drive Its Own Clean Energy Transition
Workshop Abstract
Africa is undergoing a profound energy transformation. As nations across the continent strive to achieve universal energy access, integrate renewable energy sources, and build climate-resilient power systems, the demand for reliable, accessible, and up-to-date power grid data has never been greater.
Yet, most African countries face severe challenges related to energy infrastructure data: outdated maps, siloed records, lack of digitization, and restricted access. This disconnect inhibits efforts to plan smart grids, identify unelectrified areas, integrate renewables, and prepare for climate shocks.
This workshop demonstrates how OpenStreetMap (OSM) can be leveraged to address these challenges. By enabling communities, institutions, and governments to collaboratively map and maintain their electricity infrastructure, OSM helps lay the foundation for modern, clean, and inclusive energy systems.
We will explore how open power grid data underpins energy modeling tools like PyPSA to support electrification planning, optimize grid expansion, and simulate renewable integration. Through a mix of practical demos, case studies, and hands-on mapping, this session will equip participants with the tools, strategies, and inspiration to shape Africa's energy future using open data.
We also introduce OhMyGrid—an open data, open tooling initiative that supports new and experienced mappers alike in contributing meaningfully to Africa’s power infrastructure map. With tutorials, curated datasets, and community-built mapping tools, OhMyGrid lowers the entry barrier for energy data contribution and accelerates Africa's transition toward open energy planning.
Background and Context
Many African countries are charting ambitious paths toward energy access and sustainability. Programs such as the African Union’s Agenda 2063, Sustainable Development Goal 7 (Affordable and Clean Energy), and national electrification plans all aim to connect millions of homes and businesses across the continent.
Despite the progress, the lack of transparent, up-to-date, and centralized energy infrastructure data remains a critical barrier.
Common data challenges include:
Lack of centralized repositories: Infrastructure is often fragmented across agencies and formats.

Restricted access: Utilities may restrict access due to security or proprietary concerns.

Analog formats: Paper maps and static PDFs are common, hindering digital workflows.

Undocumented rural systems: Informal or community-built mini-grids are rarely mapped.

Limited capacity: Many institutions lack tools and skills to manage spatial grid data.

These challenges slow progress in grid expansion, renewable energy investment, disaster preparedness, and equitable energy access.
OpenStreetMap as a Game Changer
As a grassroots, collaborative and transparent data platform, OpenStreetMap (OSM) is the only global mapping platform that supports detailed energy infrastructure mapping.

Over the years, the African OSM community has successfully mapped:
High-voltage transmission lines

Substations and transformers

Mini-grids and decentralized energy systems

Electrified vs. unelectrified settlements

These datasets have supported governments, NGOs, and researchers in:
Planning rural electrification

Mapping energy access gaps

Evaluating climate and conflict impacts on grid resilience

OSM allows communities to become active participants in their energy future, creating living maps that evolve alongside infrastructure on the ground.

Energy Modeling for Africa’s Future
Energy modeling is a powerful tool to inform investment, planning, and policy decisions. With transparent models like PyPSA, planners can simulate electrification scenarios, compare grid vs. off-grid options, and optimize renewable energy integration.
But these models are only as good as the data they rely on.
Without high-quality infrastructure data, models cannot:
Identify optimal routing for transmission lines

Simulate voltage drop or transformer constraints

Assess the cost-effectiveness of grid expansion

Analyze access disparities between urban and rural zones

By integrating OSM data with satellite imagery, census records, and renewable resource datasets, African planners can build robust models for equitable, sustainable energy futures.
The Role of OhMyGrid
OhMyGrid is a community-driven initiative dedicated to making power grid mapping in Africa accessible, structured, and impactful. We work to lower the barriers for new contributors and provide advanced tools for experienced mappers and energy planners.
Key contributions include:
Curated Data Sources
We maintain a collection of open-access datasets to help users jumpstart their mapping efforts, including transmission line traces, open government records, and national electrification plans.
Tutorials and Best Practices
Our learning hub provides beginner-to-advanced tutorials tailored to different user needs—whether you're mapping your first substation or validating voltage routing logic in urban grids.
Custom-Built Mapping Tools
We’ve developed open-source tools and hint layers to support faster, more accurate mapping. These include:
Optimised Overpass queries to ensure only relevant data is pulled with each session
Power infrastructure tagging helpers
Validator tools for common tagging mistakes
An active community of power grid mappers to discuss and develop together.

OhMyGrid complements the OSM community by bridging the gap between mappers, planners, and energy modelers.
Outcomes and Impact
By the end of the session, participants will:
Understand the pivotal role of open grid data in clean energy planning and how OSM data feed into energy modeling tools.

Gain practical experience mapping power infrastructure in OSM and contribute your first transmission line, substation or power plant.

Learn how to use various tools and strategies on how to map the electrical grid.

Develop an understanding of how to form, organise and activate a local community for power infrastructure mapping.

ohsomeNow (also referred to as ohsomeNow Stats) is a real-time analytics dashboard and API developed by the Heidelberg Institute for Geoinformation Technology (HeiGIT). It tracks and visualizes OSM contributions globally. ohsomeNow brings transparency and context to OpenStreetMap’s massive, ongoing collaboration. Its fine-grained, flexible analytics help users understand mapping behavior patterns, measure impact of events or campaigns, and monitor trends at country or global levels.

The newly upgraded ohsomeNow Stats dashboard offers near real-time access to all OSM contributions since 2005, enabling detailed, flexible analysis of global mapping activities. Developed in partnership with the Humanitarian OpenStreetMap Team (HOT), it now includes all edits—not just those tagged with hashtags—updated every minute and calculated on demand.

In many humanitarian contexts, maps can help to save lives and to find the people in need. Yet, a common challenge persists across NGOs and humanitarian networks: while Information Management (IM) staff may have data and reporting skills, many lack the geographic information system (GIS) knowledge needed to fully harness spatial data and to understand which data sets are of best fit. The IFRC GIS Training Platform was developed to bridge this critical gap—making GIS accessible, practical, and relevant to humanitarian practitioners and beyond.
In this lightning talk, we will introduce the IFRC GIS Training Platform, a collaborative and open source platform that was developed in close partnership between the Heidelberg Institute for Geoinformation Technology (HeiGIT), the International Federation of Red Cross and Red Crescent Societies (IFRC), the British Red Cross, the German Red Cross and the Netherlands Red Cross’ data and digital team (510). The platform provides a modular and hands-on GIS training curriculum specifically designed to match and support humanitarian use cases. It enables learners with basic IM or data skills—but little or no prior GIS experience—to start creating, using, and analysing spatial data effectively.
Each training module on the platform has been created and refined in close collaboration with Red Cross and Red Crescent field and technical experts. Their feedback and real-world challenges shaped the content, ensuring it addresses genuine needs, such as mapping flood-prone areas, tracking outbreaks, or planning logistics in disaster response.
The platform includes interactive tutorials, real-world data exercises, a Wiki and practical examples that resonate with humanitarian professionals. From using QGIS for the first time to conducting spatial analysis with open data, like Open Street Map data, learners can walk away with skills they can immediately apply in the field.
Beyond individual learning, the platform is designed to scale. We offer “Training of Trainers” (ToT) sessions for institutions, networks, communities or teams who want to not only build internal capacity but also run their own training events. These ToT sessions, led by members of the platform consortium, equip participants with both the technical content and the pedagogical tools needed to confidently facilitate trainings themselves.
This training model has already been adopted by several National Red Cross and Red Crescent Societies, resulting in a growing network of GIS-savvy humanitarians who are also empowered to pass on their knowledge to others. The modular structure of the platform allows for localised adaptation and integration with ongoing capacity-building efforts, including integration with OpenStreetMap-based workflows.
And for sure, the training materials are freely available online (Creative Commons Non-Commercial) and have a strong focus on open data, while not being limited to it. The materials are easy to integrate into workshops, university courses, or humanitarian training programs.
What can participants expect from the talk?
In this talk, we will share not only the platform and its content but also stories from those who have used it: from IM officers in Red Cross and Red Crescent Societies to humanitarians discovering GIS for the first time. We'll also share partnership opportunities—either by joining our upcoming ToT programs or adopting the platform in own contexts.

The city of Maricá, in the state of Rio de Janeiro (Brazil), is historically affected by natural disasters, which mainly hit the less affluent areas of the city, where people who have fewer resources to deal with risks and damage. On the other hand, city halls in small and medium-sized cities don't always have a spatial data infrastructure or a Web mapping platform that allows for the integration of data layers related to disaster risk reduction (DRR). Given this panorama, a collaborative mapping platform is proposed, with layers related to DRR infrastructure. Seven areas vulnerable to disasters (neighbourhoods: Jardim Atlântico, Itaocara, Cajueiros, Mumbuca, Centro, Bananal, Jaconé), have been adopted as areas of interest (AOI) for this pilot project, which is an initiative of the Virtual Institute for Sustainable Development - IVIDES. org, in cooperation with the YouthMappers UFRJ chapter (Rio de Janeiro, Brazil), chaired by Dr. Raquel Dezidério Souto, chairwoman of IVIDES.org and associated researcher of the Laboratory of Cartography of the Federal University of Rio de Janeiro (GeoCart-UFRJ). Throughout 2024 and 2025, various training sessions have been carried out in order to map the seven AOI collaboratively. In order to execute the project and provide interactive data visualization, two Web maps were created, one for the acquisition an initial mapping of data in OpenStreetMap (OSM) and the other for the display of validated data in a private environment, where changes by others can be controlled. The first Web map (for raw data mapping and visualization) shows layers with data retrieved dynamically from the OpenStreetMap database using Overpass API queries, which were included in the dynamic layers of a structure developed with uMap. In this first Web map [1] it is possible to check the coverage of existing data related to the research topic in OSM and the two more used editors for OSM - iD and JOSM, can be accessed to collaborate with data missing in these AOI. The second Web map [2], developed with the Leaflet JavaScript library and the WordPress content management system (CMS), with the “Leaflet map” plug-in installed and active, containing the layers with OSM data that have already been validated, plus the static layers that have been added with data from the public authorities, such as data on the sirens at the hydrological or geological warning and alarm stations, which issue alarms to evacuate areas before a disastrous event occurs. A total of 16 layers are being considered initially: Areas subject to flooding; Areas subject to mass movements; Classification of the coast as its vulnerability to the coastal erosion; Schools (public and private); Geological alert and alarm stations; Hydrological alert and alarm stations; Hydrological monitoring stations; Meteorological monitoring stations; Hydrants; Hospitals (public and private); Clinic centers (public and private); Hotels; Churches; Pluviometers; Villages and towns; and Localities. For the Web map project developed with the WordPress CMS, custom icons were designed, which can be found on the GitHub [3]. The icons were designed with a black border to make them more visible on the map. The files were formatted in Scalable Vector Graphics (.SVG) and Portable Network Format (.PNG). The second format was adopted for the Web map in WordPress, as it was better for visualization. The Web map project developed with uMap adopted simple symbols, which are present in its standard collection of symbols. Some aggregations are made for layers with a lot of data (with the clustering resource provided by uMap), in order to improve visualization and navigation on the map. The strengths of this methodology, developed for the city of Maricá, but which could be adopted by other municipalities, are that it relies on the collaborative effort of anyone minimally trained to map on the OSM and the socialization of information on disaster-prone areas with the population. However, some difficulties have been encountered, such as: i) some people have difficulty using programs and equipment needed to interact with the map; ii) weak Internet signals in locations far from large urban centers; iii) a lack of data for certain categories, such as data on the vulnerability of areas to disasters. All these difficulties have been encountered by many other researchers carrying out collaborative research and mapping. This initiative is related to the United Nations 2030 Agenda [4] and the Sustainable Development Goals (SDGs) [5], especially: SDG 3 - Ensure healthy lives and promote well-being for all at all ages; SDG 11- Make cities and human settlements inclusive, safe, resilient and sustainable; SDG 13 - Take urgent action to combat climate change and its impacts; and SDG 17 - Strengthen the means of implementation and revitalize the Global Partnership for Sustainable Development. With the progress of this research, we hope to collaborate in providing information support, not only for prevention and mitigation operations, but also for consultation with the resident population, in order to contribute to DRR in the areas covered.
[1] http://u.osmfr.org/m/1013950/
[2] https://ivides.org/infomarica
[3] https://github.com/raqueldeziderio/leaflet_wp
[4] https://sdgs.un.org/2030agenda
[5] https://sdgs.un.org/goals

Urban air pollution is a growing public health crisis in rapidly developing cities such as Lagos, Nigeria, where vulnerable communities often remain unmapped and underserved. The Eco-Smart Cities project -launched in Nigeria and Côte d’Ivoire by the Open Mapping Hub - West and Northern Africa (WNA) under the Humanitarian OpenStreetMap Team (HOT) - aims to address this challenge by remotely mapping over 30 urban settlements across Lagos, Kaduna, and Oyo (Nigeria), as well as Gagnoa, Anyama, Yamoussoukro, and Bingerville (Côte d’Ivoire). The initiative integrates OpenStreetMap (OSM) as a participatory community mapping tool, enabling local contributions of critical infrastructure data to support localized climate and health interventions.

This project demonstrates how community-generated OSM data—including roads, health centers, and building footprints—can be combined with R Shiny, an open-source web application framework, to build an interactive visualization tool for air pollution risk assessment. The tool integrates Earth Observation (EO) data from the Sentinel-5P satellite to display 7-year average NO₂ exposure (2018–2024), overlaid with health vulnerability indicators derived from OSM data. This visual approach enables the identification of pollution hotspots, high-density exposure zones, and public health service gaps, particularly in underserved communities.

By linking satellite-based air quality data with OSM data, the application supports environmental health monitoring, evidence-based urban planning, and more equitable public health interventions. This open-source, scalable framework illustrates the power of combining OSM, EO data, and R-based visualization tools for impactful, data-driven cartography—empowering communities and decision-makers across the Global South to respond more effectively to the dual challenges of urbanization and climate change.

This talk guides one through the steps of creating 3D cartographic visualizations using QGIS and Blender Softwares .As it typically becomes difficult for GIS professionals to be able to present things in a visually engaging way—particularly when illustrating terrain, height, or spatial variation. By combining QGIS's data-processing capabilities together with Blender's capability to render, we present a workflow that converts 2D maps into photorealistic 3D environments. Participants will be taught how to process spatial data in QGIS (e.g., Digital Elevation Models and shapefiles), export properly, and utilize Blender for realistic modeling and visualization. This hands-on method enables the use of open-source software to leverage higher quality visual outputs—without ever exiting the open-source ecosystem (FOSS Systems).

Due to the rapid urbanisation that has been taking place in Africa, where it is estimated that 60% of the population will reside in cities by 2050, it is crucial to strengthen the resilience and management capacity of urban areas. In Angola, despite the development of new formally planned urban centers, there is still a significant lack of geospatial data, which hinders the efficiency of public services and the distribution of goods to the population.
This presentation aims to present the results of the mapping of the housing units of the Praia Amélia urbanisation, in the city of Moçâmedes, developed through open-access techniques and platforms, particularly OpenStreetMap (OSM).
The study included the collection of data on the ground, georeferencing and the systematic recording of constructive and spatial attributes, which were then integrated into interoperable digital environments.
The resulting dataset contributes to the democratisation of territorial information and strengthens urban governance based on open data.

Background:

The past four State of the Map Africa events have offered a diverse range of presentations, interactions, and learnings that highlighted the potential for practical utilization of GIS and remote sensing to accelerate Africa's path towards sustainable development. While the previous events have improved the ecosystem for geospatial sciences in Africa, there is need for a paradigm shift in how future State-of-the-map events could be organized as well as how the OSM at large should be run.

This abstract provides a proposition that translates to the following objectives for a paradigm shift, to expound on new opportunities for OpenStreetMap Africa.

1. To develop a repository for talks, presentations, data and research for OSM Africa available in real time for its members and interested parties.
2. To devise a standardized framework that is expert-led on how user case applications of OpenStreetMap and free open-source software can be applied across Africa.
3. To define new mandate for OpenStreetMap Africa institutional structure to foster research and publication of African-based innovations and solutions to the geospatial industry.
4. To develop an OpenStreetMap Africa strategy

The African Union vision 2063 calls upon sound institutional structures that govern the line of action to foster sustainable development. Governed by this African Vision of 2063, OSM Africa could set the path for institutional capacity development, to foster the interest of the African tailor-made geospatial solutions to development. The State of the Map Africa events and OSM at large therefore, provides an opportunity to establish such sustainable structures that speak to the continent's interest, while building from the previous isolated geospatial work of country OSM. This proposition offers an opportunity for discussion during the state of the map 2025 on how to leverage individual and country potentials, amidst the changing global environment in resource pool and utilization.

Outcomes
The outcome of this proposition aims to have:
1. A developed integrated OpenStreetMap Africa platform that becomes a repository for talks data, and presentations for every state of the map Africa Event and other interested researchers interested in sharing their work.
2. A standardized framework on user case applications of OpenStreetMap and free and open-source software across Africa
3. A revised institutional structure of OpenStreetMap Africa that fosters research and publications of African- based innovations and solutions to the geospatial industry.
4. A developed OpenStreetMap Africa strategy.

The OpenStreetMap Foundation plays a crucial role in supporting the global OSM community, yet many active mappers remain unclear about its functions and how they can participate beyond membership. This interactive workshop aims to demystify the OSMF and provide ways for meaningful involvement.
We'll start with an overview of OSMF's structure, responsibilities, and decision-making processes, addressing common misconceptions about what the Foundation does and doesn't do. The session will then shift its focus to practical participation opportunities, including joining working groups, contributing to policy discussions, and participating in Board elections.
The workshop will also feature volunteers from various OSMF working groups who will share their personal journeys and experiences. Attendees will have opportunities to ask questions, identify areas that match their interests and skills, and understand how their participation can strengthen African representation within the Foundation.
Whether you're an OSMF member who only votes annually or a long-time mapper who's never joined, this session will equip you with the knowledge and confidence to take your next step.

In many underserved regions cross Africa, communities remain invisible on digital maps, limiting their access to essential services, representation in planning, and ability to respond to crises. This project based in Damongo, in Ghana’s Savannah Region, uses Mapillary as a key tool to document and map the community’s transformation over time visually. Through the collection of street-level imagery, the study captured detailed before-and after views of roads, signage, and infrastructure changes across various parts of the district. These images were processed and integrated into OpenStreetMap (OSM) using JOSM, improving the quality and coverage of local map data. The addition to data collection, the mobile apps used OsmAnd, Organic Maps and StreetComplete to contribute to open mapping. In my presentation, the study will demonstrate how leveraged open-source mobile tools to collect data in rural Ghana, highlighting the critical roles these accessible tools play in making mapping more efficient and effective. The study area will show how mobile mapping empowers us to go beyond traditional computer-based approaches, bringing mapping to the field. This approach not only enhances data accuracy but also foster community engagement and participation in the mapping process. The projects align directly with the 2025 theme,” Mapping the Future : Connecting Communities &Fostering Collaboration,” by showing how open-source tools can connect local knowledge with global platforms, foster collaboration between mappers and communities, and build resilience through data. More than just creating maps, this initiative builds capacity, promote digital inclusion, and provides visual evidence of community evolution making open mapping tool a long- term transformation. Keywords: Mobile Mapping Tools; Community Visibility; Community Resilience; Open Source Tools; Ghana

In Freetown, it is estimated that over 360,000 people reside in informal settlements. These are vibrant and dynamic neighbourhoods of varying size, recency, and characteristics. The residents of these settlements move between their neighbourhoods and other parts of the city for economic and social reasons, but also to access services not available where they live.

As informal settlements often evolve without formal planning processes, the entry and exit points that connect them to adjacent neighbourhoods are not optimised. This means that some parts of informal settlements are very well served by access routes and some are poorly served.

For persons living with disabilities in informal settlements, a lack of proximate entry/exit points or inaccessible entry/exit points can greatly exacerbate the already challenging process of accessing essential services, economic opportunity, or social networks.

Using recently acquired high-resolution drone imagery, OpenStreetMap data, and community-driven mapping approaches, the Humanitarian OpenStreetMap Team (HOT), Freetown City Council (FCC), National Commission for Persons with Disabilities – Sierra Leone (NCPD), and OpenStreetMap Sierra Leone (OSM SL) are collaborating to develop analytical methods aimed at evaluating the current state of accessibility in seven informal settlements for persons with disabilities. The project also seeks to model how various proposed physical interventions could enhance their access to services and opportunities beyond the settlements where they reside.

The analysis employs open-source GIS (Geographic Information Systems) tools to evaluate optimal walkability zones within the seven informal settlements, focusing on access to key entry and exit points such as bridges, crossways, and highways.

Alongside open drone software - Drone Tasking Manager (Drone TM) and OpenDroneMap (ODM) - to capture and process the high-resolution imagery, the analysis leverages several open mapping and open geo-tools and databases, including:
- OpenStreetMap and OSM editors for digitising high-quality building datasets plus POIs.
- Mapillary for capturing and processing 360-degree images/videos to validate disability-friendly metrics on highways and entry/exit points.
- pgRouting for determining how long it takes to travel to entry/exit points from households and recommends the most efficient routes to be used by PWDs.
- uMap for visualising and sharing routing analysis for persons with disabilities (PWDs), providing relevant stakeholders with evidence-based insights to support decision-making.

This BMZ-funded project aims to equip the Freetown City Council (FCC) with actionable insights to support the improvement of entry and exit point infrastructure, while also deepening the understanding of barriers to accessibility faced by persons with disabilities.

We propose to share with the State of the Map Africa audience the analytical approach used in the 'Promoting Inclusion and Accessibility for Persons with Disabilities in Freetown’s Informal Settlements, Sierra Leone' project, to gather feedback to refine and adapt the methodology for use in Freetown and other similar contexts.

Abstract:
Effective urban solid waste management in African cities remains a critical challenge characterized by rapid urbanization, limited infrastructure, and insufficient data. Traditional top-down approaches often fail to address the unique, hyperlocal realities of waste generation, disposal behaviors, and service gaps. This presentation explores how OpenMap Development Tanzania (OMDTZ) with the funds from the World Bank, has implemented community-driven data collection approaches in Tanzania, Mozambique, and Kenya to fill this knowledge gap and build more responsive, inclusive waste management systems.
Through the integration of OpenStreetMap (OSM), mobile data tools like OpenDataKit, OsmAnd, and participatory mapping techniques, communities have been engaged in mapping informal waste collection points, illegal dumping sites, transfer stations, and service coverage areas. By centering local knowledge, these projects have produced actionable geospatial data that informs city-level planning, supports environmental health interventions, and amplifies citizen voices in waste governance.
Participants will gain insights into how grassroots data collection not only improves the quality of open data but also reshapes power dynamics in urban planning placing communities at the forefront of building cleaner, more sustainable cities.

Description:
Urban waste management systems across many African cities face severe capacity challenges. Waste collection services are often inconsistent, infrastructure is unevenly distributed, and data on where and how waste is generated and handled is largely missing or outdated. This session shares lessons from community-centered mapping initiatives implemented by OMDTZ and partners in Dar es Salaam, Nacala-Mozambique, and Mombasa-Kenya, where local residents have played a central role in generating critical waste-related datasets.
Instead of relying solely on municipal audits or high-tech surveys, the approach engages community members, youth groups, and local organizations to map and monitor solid waste dynamics in their own neighborhoods. Equipped with mobile tools, participatory maps, and training, local data collectors document:

1. Community perception and attitudes on the solid waste management
2. Waste handling modes, disposal methods, and payment behavior
3. Informal dumpsites and hotspots for illegal dumping
4. Waste collection service routes and gaps
5. Types and volumes of waste generated in residential areas
6. Proximity of vulnerable communities to un-managed waste zones

These datasets are then analyzed and shared with the responsible authority, allowing governments and funders to create the city-level strategic plans for solid waste management. While researchers access real-time, location-specific information for designing targeted interventions, from optimizing collection routes to deploying behaviour change campaigns.

This talk will cover:
1. The methodology for engaging communities and collecting waste-related geospatial data
2. Case studies from Tanzania, Mozambique, and Kenya that demonstrate impact
3. Tools and platforms used for data collection, visualization, and decision-making
4. How local knowledge has influenced waste policies and infrastructure planning
5. Challenges and solutions for sustaining community engagement and ensuring institutional uptake of data

By leveraging community knowledge and open technologies, these projects have helped cities move toward more resilient, inclusive, and evidence-based solid waste systems. The session will also highlight how this approach contributes to climate resilience, youth empowerment, and the democratization of urban data ecosystems.
Ideal for practitioners, urban planners, open data advocates, and local government officials, this session will offer replicable strategies for harnessing community-driven data to transform waste governance and sustainability in rapidly growing urban areas.

Accurate geospatial data is critical for effective public health interventions, particularly during disease outbreaks in resource-limited settings. We implemented a novel, low-cost participatory mapping approach that successfully geolocated 764 residential areas in Blantyre district, Malawi, during the 2022-2023 cholera outbreak response.

Despite Blantyre district's having comprehensive health records, approximately 60-70% of residential areas documented in cholera case listings lacked proper mapping and geographical coordinates in existing spatial datasets. This data gap severely hindered targeted vaccination campaigns and outbreak response efforts during Malawi's deadliest cholera outbreak.

We developed a community-embedded methodology that leveraged local knowledge through Health Surveillance Assistants (HSAs) and utilized accessible technology tools. Our mapping workflow integrated KoBo Toolbox for offline data collection on smartphones, participatory mapping with YouthMappers and local health workers as guides, real-time data monitoring and validation and community stakeholder engagement for quality assurance.

Our project employed a simple yet effective combination of tools. KoBo Toolbox for survey design and data collection, smartphone GPS capabilities for coordinate capture, R Statistical Software for data processing and standardization, GitHub for code sharing and reproducibility and Zenodo repository for dataset sharing.

In 15 working days, our team of five data collectors (3 YouthMappers and 2 research assistants from Malawi Liverpool Wellcome Research Programme (MLW)) successfully mapped 764 residential areas with <5-meter GPS accuracy at a total cost of $2,005.69 (approximately $2.60 per location). This represents an 85% cost reduction compared to conventional professional surveying approaches ($15,000 to $30,000 for comparable coverage) while maintaining acceptable spatial accuracy for public health applications.

Key innovations in our study were the elimination of expensive surveying equipment through smartphone-based GPS collection. Leveraging existing health system infrastructure and community health worker networks. Offline-capable data collection system suitable for areas with poor connectivity. Real-time validation and quality assurance mechanisms and open-source data processing pipeline for reproducibility.

The resulting dataset, now publicly available through Zenodo (https://doi.org/10.5281/zenodo.15487740), has been integrated into ongoing cholera surveillance and vaccination planning efforts. Our methodology demonstrates significant potential for scalability across Malawi and similar resource-constrained settings, particularly in countries with established community health worker programs.

This experience highlighted the effectiveness of combining simple, accessible technologies with participatory approaches and local knowledge systems. Key success factors included strong stakeholder engagement, iterative validation processes, and the strategic use of existing health infrastructure.
Beyond outbreak response, this approach has broader applications for patient locator systems (currently implemented at MLW), health service planning, and routine disease surveillance. The methodology offers a practical framework for rapidly generating accurate geospatial data in emergency contexts while building local capacity and ensuring community ownership.

In Algerian cities, the experience of female users in public spaces remains underexplored. While some public spaces lack the sense of safety or adequate amenities for women—particularly mothers—other spaces unexpectedly offer women-friendly environments. What are the socio-spatial characteristics that ensure women’s spatial conviviality? And how can public spaces be assessed in relation to women’s lived experience?
As part of a Ph.D. thesis (2024), the social project called (Madinatouha) was developed to create an assessment tool that combines an index with collaborative mapping. Sixteen indicators were identified after an extensive literature review, and grouped into four main axes (Safety, Dignity, Functionality, and Comfort), each considering both the cultural and functional dimensions of public spaces in the city of Blida. The index was translated into a mobile application that allows participatory, real-time data collection and visualization tool.
The app was co-designed by the researcher (an architect with experience in communication and graphic design) in collaboration with a phone developer. After trials and adjustments, the prototype was launched on Google Play. A team of trained young female architects led a five-month field data collection campaign across Blida. A follow-up focus group with the data collectors was conducted to reflect on field challenges, propose improvements to the assessment tool, and identify distinctive patterns in women’s urban experiences.
The challenges acknowledged, not as weaknesses, but as valuable feedback to refine the collaborative mapping tool. The presentation will outline the development process of the Madinatouha app, share insights from the collected data—analyzed using Microsoft Excel and ArcGIS—and highlight key lessons from this collaborative approach to mapping women’s experience in public spaces.
One of the project’s strengths lies in its capacity to generate a wide range of maps and charts, showing the significant importance of participatory mapping and Geographic Information Systems in providing real-time and accurate data about public spaces from a user's view. This participatory method offers a practical pathway for urban planners and decision-makers to better reflect public spaces design.
The fieldwork revealed several challenges: unreliable internet connections disrupted real-time data entry; the time-consuming nature of assessments; cultural sensitivities around privacy; varying perceptions of safety; and occasional risks such as phone theft in crowded markets.
The focus group recommended involving urban planning institutions and architectural firms in future iterations of the tool. To improve data reliability, it also proposed combining expert evaluations with user input. The project continues to evolve, with the aim of developing a more sustainable and interactive model for mapping women’s experiences in public space.
The project is believed to foster greater community participation and influence urban policies to be more responsive to women's needs. By reflecting on both technical and social aspects of the initiative, the presentation aims to inspire mappers, developers, and planners to design participatory tools that genuinely reflect the diversity of public spaces in the city.

Background

Trocaire Malawi is working with Green Girls Platform on a STEM for Climate Action project that aims to provide 300 young people in Malawi aged 11 to 20 with the knowledge and hands-on skills needed to apply STEM (Science, Technology, Engineering, and Mathematics) to address climate challenges in Lilongwe. The project is promoting STEM and climate education, problem-solving skills, knowledge sharing, and managements for a period of one year. The project's primary goal is to integrate STEM into environmental education, allowing young people to understand the importance of using STEM to create climate solutions at a young age and aligning with global climate initiatives. The project has partnered with the ministry of education, ministry of climate change and natural resources, Youth Mappers and University Environmental Clubs. The emphasis is on collaborating and co-creating knowledge with local leaders, teachers, community-based organizations, and young people in rural Lilongwe to derive environmental solutions through geospatial skills.

Objectives and project justification

Young people, particularly girls and young women, are disproportionately vulnerable in Malawi, to climate change due to limited access to environmental education and awareness, particularly regarding the potential of STEM in climate action. While developed countries take bold steps to address climate change issues using STEM related approaches, Malawi lacks coordinated capacity to explore and utilize strategies that utilizes STEM, one of which being geospatial science. The project concentrates on educating 300 Young people from three marginalized communities in Lilongwe on how they can identify environmental challenges, work as teams, learn from others and fully utilize mapping skills to come up with sustainable climate solutions that work in their contexts.

Overall objective: To train 300 young people aged between 11-20 in 3 underserved communities in Lilongwe on STEM for climate action by December 2025.

Project Action Points:

1. STEM and Environmental Literacy: The project is integrating STEM and environmental concepts into project activities, curriculum materials, and hands-on experiments with students.

2. Implementation of 3 Youth-led climate action projects: The project is encouraging students to identify local environmental issues and design their own projects that are aided by geographic information tools to address these challenges and provide guidance and resources to support their project development, implementation, and evaluation.

3. Encourage teamwork and collaboration among students: By organizing group activities, workshops, and competitions where they work together to solve environmental problems. The project emphasizes the importance of collective effort and diverse perspectives in finding innovative climate solutions.

4. Establish 3 STEM for climate action hubs: Climate Education hubs have been established in all 3 communities with toolkits and documentation of the project for replication as well as knowledge sharing and management for the communities.

Implementation Strategy

1. STEM training sessions for students

The project begins with hands-on trainings in three areas of STEM and climate action, providing an overview of environmental conservation and climate change, as well as the role of young people in climate action. This is followed by lessons on technology and climate action led by Youth Mappers by teaching GIS and its integration with climate action, teaching youth how to develop solutions to climate change in Malawi.

1. Action Projects

Following the trainings together with youth mappers, environmental challenges are identified that are specific to their communities and students develop STEM-based solutions tailored to their local contexts, resulting in solutions that work in their contexts. These solutions are monitored and supported throughout the implementation of the action projects.

1. Knowledge Sharing and Management

Following the completion of the projects, each community conducts exchange visits to see what they have accomplished and to learn and share their experiences. The peer learning is aimed at enhancing sharing of their experiences, successful approaches, and challenges. Further areas of learning include a knowledge exchange workshop that is organized, where students discuss collective strategies for addressing Malawi's climate change issues in Lilongwe through mapping.

1. Establishment STEM for Climate Action hubs.

Lessons are documented by compiling toolkits for knowledge management and establish a climate change hub in each community to facilitate easy sharing of information and learning for youth who were not part of the project. The hubs support the sustainability of the project by continious engagement with YouthMappers and Environmental Clubs.

Earth Observation (EO) combined with OpenStreetMap (OSM) has become a powerful driver of geospatial intelligence across Africa, supporting everything from disaster response to agricultural planning and infrastructure development. But despite its potential, many EO-OSM workflows remain manual, fragmented, and difficult to scale, especially in the fast-paced environments where they’re most needed.

This work introduces a new frontier: Agentic AI—autonomous, goal-driven systems that can reason, plan, and interact with tools, APIs, and data to carry out complex tasks with minimal human input. The python-based geospatial and machine learning tools, can serve as intelligent co-pilots for EO-integrated mapping workflows that can: rapidly respond to disasters by fusing Sentinel radar data with OSM building footprints to identify flood zones and assess impacted communities; spot infrastructure gaps by analyzing Sentinel-2 imagery alongside OSM road networks to recommend missing roads or generate MapRoulette tasks; and automate land use classification with open EO datasets like Landsat and Sentinel-2, where agents handle everything from data preprocessing to training models and generating visual maps.

This work also covers practical knowledge, reusable Python workflows, and a fresh perspective on how agentic AI can power faster, smarter, and more scalable mapping across Africa and beyond.

Introduction
To conduct a study analyzing under-resourced populations in a dense, dynamic city like Lagos, understanding where these populations reside, and their proximity to telecommunications and health system access alike, is vital. Understanding location and travel accessibility affects how a person can travel to access primary healthcare – as areas that are further away from a facility strongly benefits from a telehealth initiative.
Geographically identifying under-reached populations and applicable population segments to target interventions, understanding where current health system delivery gaps in facility and service availability and poor geographic/physical access to health facilities and low performance. The Lagos Innovation portfolio, a geospatial analysis performed by members of the Geospatial Insights Support Team (GIST) from DevGlobal and Dev-Afrique Development Advisors, aimed to analyze and identify underserved communities who could potentially receive telehealth interventions for an interventional research study conducted by Solina Centre for International Development and Research (SCIDaR) and VillageReach.

Methods
Geospatial datasets were procured from GRID3, OpenStreetMap, and OpenCellID, while tabular datasets were acquired from the Nigeria Federal Ministry of Health, the Lagos Bureau of Statistics, and the Lagos Primary Healthcare Board.
GRID3 population density data from 2021 (quantified as high, medium, and low), which demonstrates the distribution and intensity of human activity across all 20 LGAs, was overlayed with the coordinates of existing health facilities obtained from the Lagos Primary Healthcare Board. The existing health facilities were mapped with their primary, secondary, and tertiary-level healthcare facility levels. Additional information, such as their operational status, as defined by the Nigeria Federal Ministry of Health’s Master Facility Lists and Health Facility Registry, public/private status, and clinical staffing levels, were also incorporated for each facility.
A 3km buffer was created around each active healthcare facility to show the estimated coverage of healthcare services, a more conservative estimate compared to the World Health Organization’s 5 kilometers optimal distance for healthcare accessibility. As a result, areas outside the 3km buffer were staked as potential intervention locations for the telemedicine study. These areas of potential intervention were further overlayed with Google Earth imagery and OpenStreetMap road network data to precisely map areas of considerable development and human activity.
For each LGA in Lagos state, a set of socioeconomic indicators – such as gender (male/female), income level (low or high), education level (elementary or advanced levels), housing type (based on building size, rental/ownership costs and luxurious building features), and employment type (high/low) - were obtained from the Lagos Bureau of Statistics, categorized and appended to each LGA. Potential service points were then overlaid on top of the LGAs with appended socioeconomic indicators.
Additional analyses were performed to analyze the effects of travel time and cell signal catchment areas. Travel time catchments were determined in Python using OpenStreetMap road networks (including routing information), and the osmnx, networkx (to Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.), and sklearn Python modules to (1) download, model, analyze and visualize street networks and incorporate speed, travel time, and routing, (2) create, manipulate, and model the complex road network, and (3) analyze the projected graph network. The travel time catchment area, determined as the number of intersections that could be traversed within a 20-minute time, was determined for both driving (using a 30km/hr. speed) or walking (using a 5km/hr. speed) scenarios. These catchment areas were overlaid on the circular buffer areas. Areas selected were typically those with high measures of poverty (e.g., low income, poor housing type and/or employment type) that were outside of the healthcare-accessible buffer areas.
Another auxiliary analysis, to map cell signal catchment areas, was performed to help guide potential telemedicine initiatives. Tower location coordinates were obtained from OpenCellID, which contained information about the tower location, the type of transmission (2G, 3G, 4G, and 5G), and other indicators. Each tower location had a buffer mapped around it, equivalent to the radius (“range”) of transmission. The individual tower buffers were merged together for each type of transmission, using dissolve in QGIS, to create a zone for each transmission type.

Results
A total of 26 potential service points were identified as underserved areas across different local government areas (LGAs) and local council development areas (LCDAs) in Lagos. These locations were found in Ikorodu (6), Ibeju Lekki (5), Badagry (2), Ojo (2), Alimosho (2), straddling Ojo and Alimosho (1), Ifako Ijaye (1), Amuwo Odofin (2), straddling Oshodo-Isolo/Ikeja (1), Lagos Island (1), Eti Osa (1), and Epe (1) LGAs.
When analyzing the distribution of primary healthcare facilities, including community health centers, rural health clinics, paediatrics practices, family medicine practices, etc., about 70 percent of the total healthcare facilities in Lagos state were made of such facilities, with more primary healthcare facilities occurring in higher-population density areas LGAs (e.g., Alimosho, Badagry, Eti-Osa, Kosofe, Ikorodu, and Ojo). Additionally, it was found that private HCFs were more prevalent than public HCFs in the higher-density locations. Our results also suggested a low population of clinical staff occurred across the state.
When using calculated travel time from each underserved point, it was found that the travel time-specific catchment areas often went further outside of the circular buffer zone used to signal healthcare accessibility. When incorporating the travel time buffers into the analysis, the number of communities captured as part of each catchment area were often much higher than those captured solely by the circular healthcare accessibility buffer.
The majority of cell signal network types encountered in underserved communities are 2G, according to an analysis of cell signal range and LGA data, with 3G and 4G services available in more population-dense areas of the state.

Discussion
By utilizing a hybrid approach of mapping and spatial overlay of local health facilities, telecommunications access, road networks, travel time catchments and various socioeconomic indicators, our team was able to identify a shortlist of 26 underserved settlements across 11 LGAs in Lagos state that could be potentially be best serviced by a telehealth intervention.
After these initial results were disseminated by the GIST in May 2023, these results were passed to SCIDaR and VillageReach for a telemedicine research intervention study, “Implementation Research to Test Equitable Digital-First Care in Lagos”. Taken together, these results could be taken as a first step improving equitable access to primary healthcare for underserved populations in Lagos State.

In many open mapping projects, communication is often treated as an afterthought, something that follows the data collection, rather than guiding it. But what if communication was not the last step, but the first?

This session will explore why communication should start at project design particularly in open mapping work focused on community resilience, climate adaptation, and participatory data. Through examples from OpenMap Development Tanzania (OMDTZ)’s projects

The session will focus on understand the Role of Early Storytelling in Advocacy, Funding, and Long-Term Engagement

Rumours and misinformation increasingly contribute to instability and violent conflict around the world. The proliferated use of the internet and social media has escalated and ramped up the speed of misinformation-sharing, contributing to offline violence. Many communities routinely face threats from misinformation online, as well as from other sources such as television, radio, and word of mouth. Information deficits and this link between misinformation and violent conflict urgently need to be addressed, especially in conflict-prone settings. Since 2013, the Sentinel Project has been developing and expanding initiatives to manage misinformation in unstable environments, to prevent and mitigate violence. These projects have become effective mobile phone-based participatory information services for engaging communities in monitoring, verifying, and countering the spread of harmful rumours and misinformation that contribute to conflict. The inspiration for these projects was the Una Hakika pilot project, first developed in the Tana Delta, Kenya. Participants report rumours, which are investigated by the project team and a network of trained volunteers and stakeholders. Once a rumour has been verified, the facts are reported to the affected communities. The most common communication channels are SMS, voice calls, and the engagement of volunteer community ambassadors. This intake and verification process involves gathering a large amount of information from various sources, such as open mapping, open data, and GIS, and attempting to make sense of it. The next step involves mapping reports of rumours to see how they develop and spread through the area. The interface then profiles rumour reports according to the risk levels posed and provides an analysis that reinforces and determines responses and interventions. Additionally, the existing Una Hakika system can also provide real-time information on increased volatility in its operational area. More broadly, Una Hakika supports positive behavioural change among citizens by establishing, training, and equipping a broad community of practice focused on countering misinformation and other forms of harmful online content.

Pangolins are among the most endangered and least understood mammals globally. As the most trafficked mammal in the world, they have faced increasing threats from habitat loss and illegal wildlife trade. In response to this crisis, the Tanzania Research Conservation Organization (TRCO) emerged as a national leader in pangolin conservation through research, education, policy advocacy, and community engagement. To complement these efforts, Geospatial Technology and Environment (GeoTE) initiated a collaborative project aimed at integrating OpenStreetMap (OSM) into the conservation landscape.
The initiative, titled “Mapping for Pangolins,” brought together GIS professionals, students, conservationists, researchers, and local communities in a coordinated mapping campaign. The primary objective was to produce open, accurate, and up-to-date geospatial data to support pangolin protection, habitat monitoring, and community-based conservation planning. Using the OSM platform, participants successfully mapped key features within TRCO’s focus areas such as roads, settlements, water bodies, forest boundaries, and land cover types that are often underrepresented or missing from existing datasets.
By leveraging OSM’s collaborative and open-access nature, the project empowered local communities and students to actively contribute to environmental conservation through citizen science. Participants were trained to use OSM tools, including iD Editor, Field Papers, and GPS-based applications such as OsmAnd and Organic Maps. These efforts enabled the creation of actionable spatial data that helped TRCO identify high-risk areas for pangolin trafficking, assess human-wildlife interactions, and enhance planning for habitat protection.
The initiative also contributed to a broader goal of promoting geospatial innovation for environmental sustainability in Tanzania. Ensuring that the generated data remained open and accessible to stakeholders including government agencies, NGOs, researchers, and local communities, enhanced collaboration and informed decision-making at multiple levels. Follow-up sessions were conducted to validate map quality and to maintain the engagement of newly trained mappers, particularly from YouthMappers chapters across the country.
This project demonstrated how OpenStreetMap can serve as a vital tool in modern conservation strategies, especially in regions where data scarcity limits effective planning. The collaborative effort between TRCO, GeoTE, and the open mapping community provided a scalable and replicable model for integrating spatial data into wildlife conservation.
In conclusion, “Mapping for Pangolins” showcased the power of open geospatial data and citizen participation in addressing critical conservation challenges. The initiative emphasized that protecting species like the pangolin requires not only scientific research and policy but also accurate, community-driven mapping to reflect real-world conditions on the ground. As a result, the project made a significant contribution to pangolin conservation and highlighted the transformative role of OpenStreetMap in supporting biodiversity and ecological resilience.
This presentation will offer valuable insights into how OpenStreetMap can be effectively applied beyond urban and infrastructure mapping, showcasing its critical role in conservation and biodiversity protection. By highlighting a real-world case from Tanzania that combines youth engagement, community participation, and geospatial innovation, the session will inspire similar collaborations globally. It will also provide a replicable model for how OSM data can support endangered species protection and habitat monitoring.

There will be a whiteboard at the conference with allotted time and room for these sessions. Speakers will have to put in topics that are related to OSM and Open Mapping, have a ticket and adhere to the SotM Africa Code of Conduct. This is a first-come, first-served session

geo3D. Harnessing OpenStreetMap for Community-Led 3D City Modelling and Sustainable Development Education in Africa

Abstract

While OpenStreetMap (OSM) has become central to participatory mapping across Africa, tools for extending 2D mapping into spatial modelling remain fragmented. This paper addresses: How can open geospatial data and free software enable reproducible, interactive, and meaningful local-scale 3D modelling for education and community empowerment in Africa?

We present geo3D: an openly licensed tool integrating OSM data, Jupyter Notebook, and 3D urban modelling for spatial reasoning and SDG-aligned learning. Rather than claiming educational effectiveness, we present geo3D as a foundational framework enabling communities to progress from descriptive mapping to analytical modelling for evidence-based planning and spatial literacy development.

Problem Statement

Participatory mapping has expanded rapidly across Africa through OSM, HOTOSM, and YouthMappers, contributing 6.2M building footprints between 2015-2021. However, engagement remains largely descriptive, focused on feature collection rather than analytical modelling or scenario exploration.

Key gaps identified include: Fragmented tools (Existing 3D tools, such as QGIS 3D, OSM2World and 3dfier address discrete pipeline stages without integration), Missing reproducible workflows (Participatory mapping remains project-based with undocumented processes), Educational limitations (Activities confined to digitization rather than higher-order spatial analysis), Technical barriers (No openly licensed framework links OSM data validation, 3D model generation, and spatial analysis)

This fragmentation reflects broader pedagogical challenges where mapping is introduced as an end rather than a pathway to spatial reasoning and problem-solving.

geo3D Framework (Technical Architecture / Methodology)

Implemented in Python within Jupyter Notebook, geo3D is guided by four principles:

1. Integration: Unified preprocessing, 3D generation, and spatial analysis workflows designed to execute at a community (local) level to facilitate hands-on, grassroots learning.
2. Reproducibility: Documented, replicable notebook-based pipelines
3. Standards compliance: ISO 19107-compliant topologically valid models with Jupyter Notebooks that conform to Computing Best Practice.
4. Accessibility: Openly licensed, cloud-deployable for low-resource contexts

geo3D operates under two primary Processing Options, determined by the scale of analysis:
- Village: Optimised for areas with fewer than 2500 buildings.
- Suburb: Tailored for areas with more than 2500 buildings.

Following this, users select a Processing Strategy based on their needs:
1. osm_LoD1_3DCityModel: A high-quality, lightweight LoD1 3D City Model adhering to Open Geospatial Consortium (OGC) and International Standards Organization (ISO) spatial schema for 3D primitives (ISO 19107). This model enables quantitative analyses for urban planning, noise propagation, energy demand, and wind comfort factors. The strategy requires a raster Digital Elevation Model (DEM).
2. interactiveOnly: A pseudo-3D HTML-based interactive visualisation tool for user engagement, navigation, and sharing.

Spatial Analysis Capabilities
Integrated analytical functions include: Population estimation based on building footprints and local knowledge, Building Volume per Capita (BVPC) spatial equity metric linking residential volume to population, Topology error detection creating feedback loops for OSM data improvement.

Cape Town Case Study

Testing across four diverse sites demonstrated technical feasibility:

Performance results:
Processing time varied from 8 seconds (50 buildings, 25m DEM) to 45 minutes (2,187 buildings, 5m DEM) with all models validated using val3dity for ISO 19107 compliance. Proof-of-concept demonstrates alignment between grassroots learning and neighbourhood-scale suitability .

Spatial analysis outcomes:
Population for all areas where estimated based on local knowledge and OSM data. Where areas had an existing census metric; a population growth rate and projected (future) population estimate was possible. These values yield: Mamre (peri-urban): 10,736 current population, 1.43% growth → 12,368 by 2034 and Salt River (urban): 9,023 current population, 2.63% growth → 11,703 by 2034

BVPC inequality analysis highlighted housing and economic disparity across all areas. Walmer Estate (affluent): 190.1m³/person, Salt River (urban): formal: 86.1m³/person and social housing: 96.6m³/person, Mamre (rural): formal 83.1m³/person and informal: 42.6m³/person (indicating overcrowding) and CPUT dormitories: 99.4m³/person

Results correspond with recent spatial inequality studies, providing quantitative evidence for SDG 11 discussions.

Discussion

By bridging descriptive and analytical practice geo3D addresses the mapping-to-modelling gap (highlighted in the Problem Statement) through:
- Integrated learning: Students learn programming while practicing scientific computing
- Place-based inquiry: Operating where users have local knowledge and experience
- Dual pedagogical tracks: Analytical rigour (LoD1 models) and community communication (pseudo-3D visualizations)
- Reproducible workflows: All steps documented in openly licensed Jupyter notebooks

SDG Alignment
While untested without validation; the geo3D framework supports: SDG 4 (Quality Education): Integrating digital literacy and computational thinking, SDG 8 (Decent Work): Building geospatial data science skills and SDG 11 (Sustainable Cities): Enabling communities to model and assess built environments

Scope Limitations and Future Research

While demonstrating technical feasibility, several critical aspects require further investigation:
- Educational effectiveness: No empirical evidence that geo3D improves spatial literacy or student engagement compared to traditional approaches. Educational value claims remain theoretical.
- Community empowerment impact: Assumptions that analytical tools lead to empowerment lack demonstration. Whether communities use geo3D outputs for advocacy or decision-making requires investigation.
- Meaningfulness: BVPC and population metrics reflect researcher rather than demonstrated community priorities. Indicator relevance needs community validation.
- Contextual transferability: Evidence limited to Cape Town. Applicability across diverse African contexts—varying infrastructure, resources, linguistic and cultural approaches—remains untested.

This positioning establishes geo3D as a proven technical foundation while acknowledging the empirical work needed to validate its educational and empowerment potential. In other words: the research question (how) has been satisfied but the paper has exposed several avenues of further research that must investigate the tools effectiveness.

Research Opportunities and Implementation

Community Research Pathways
- Participatory validation: Feedback loops between analysis and OSM editing
- Educational research: Investigating how 3D modelling influences spatial literacy
- Interdisciplinary collaboration: Linking mapping with public health, climate adaptation, housing policy

Technical Requirements
- Python 3.9 with Jupyter Notebook
- Cloud deployment eliminates installation barriers
- Optimized for neighbourhood scales (50-5,000 buildings)
- Modular design adaptable to schools, universities, NGOs, community organizations

Contribution and Future Development

This tool paper contributes:
1. Methodological innovation: Linking grassroots mapping with analytical urban modelling
2. Educational framework: Demonstrating reproducible spatial workflows as pedagogical tools
3. Technical foundation: Providing tested, extensible pipeline for diverse contexts
4. Community platform: Enabling progression from descriptive cartography to interactive modelling

Future development focuses on partnerships with OSM Africa networks and responding to the needs of the community

Conclusion

geo3D addresses how open geospatial data and openly licensed software can enable meaningful local-scale modelling by providing a reproducible foundation for participatory spatial education. The framework transforms the question from "what is mapped" to "what can be modeled and interrogated," supporting evolution from descriptive cartography to analytical spatial reasoning.

As proven technical capability rather than demonstrated social impact, geo3D establishes a platform for collaborative research addressing African urban development challenges while acknowledging the empirical work needed to validate educational and empowerment potential.

A lightning talk is available at: https://adriankriger.github.io/geo3D/

In many rural areas of Uganda, pregnant women face life-threatening challenges due to limited access to health services, poor road networks, and the absence of timely emergency responses. This project leveraged the power of open mapping—specifically Open StreetMap to bridge this critical gap by connecting communities with life-saving maternal healthcare services.
The project involved identifying and mapping key locations such as health centers, maternity wards, drug shops, ambulance routes, and referral hospitals. Using participatory mapping methods, we engaged local community members, village health teams, and youth volunteers to collect geospatial data that reflects the true needs and conditions of their areas. The data was then uploaded to Open StreetMap, creating a publicly accessible resource for health workers, NGOs, and government responders.

One of the most impactful results of this initiative was the improvement in emergency response planning. Local officials used the maps to plan faster routes for ambulances and to identify communities at higher risk due to isolation. The availability of mapped health data helped maternal health programs target outreach efforts more accurately, bringing prenatal and postnatal services closer to the people who need them most.

The project also served as a platform for building digital literacy and fostering community collaboration. By involving residents in every step—from data collection to validation—we ensured that the mapping process was inclusive and responsive to local priorities.

This case study demonstrates how open mapping tools can support sustainable development, promote resilience, and improve public health in underserved regions. It also emphasizes the importance of community participation in making mapping initiatives meaningful and impactful. Through this work, we contribute to a larger vision of connecting communities across Africa and using open data to drive equitable access to essential services.

This session provides a space for university students and alumni to pitch their visual solutions to a data visualization challenge competition. This is a way to empower university students and recent graduates with practical geospatial data visualization skills. The session is organized by the Resilience Academy to offer students and alumni from the University of Dar es Salaam, Ardhi University, Sokoine University of Agriculture, and State University of Zanzibar a hands-on experience in developing real-world solutions for specific client needs. In collaboration with GIZ, the challenges in the session are focused on supporting urban water and climate resilience in Tanzania’s rapidly growing cities of Mwanza and Tanga.

During the session, there will be two introductory presentations to familiarize participants with the program. Following these, student teams will pitch their solutions to the challenge. The session will conclude with the announcement of the winning groups and the presentation of awards.

Visualization Challenge 2025: https://resilienceacademy.ac.tz/data-visualisation-c/water-security-climate-resilience-visualization-challenge-transforming-data-into-actionable-insights-for-tanga-and-mwanza-cities/

Municipal solid waste (MSW) is a growing global challenge, with 3 billion people lacking access to safe disposal and global waste generation expected to rise from 2.01 to 3.40 billion tonnes by 2050. Poor waste management, especially open dumping, contributes to environmental degradation, disease transmission, and emerging health risks from microplastics. Despite the UN’s call to end unsafe waste practices, effective and inclusive management systems remain critically underdeveloped—particularly in Sub-Saharan Africa, where less than 50% of MSW is collected and about 70% is openly dumped. In East Africa, Tanzania—and especially its commercial capital, Dar es Salaam—stands out as a hotspot for mismanaged plastic waste. The city generates approximately 4,600 tonnes of waste daily, yet less than 40% is collected, with the remainder being illegaly burned or dumped to later accumulate in streets, drains, and rivers, including the heavily polluted Msimbazi River, a major contributor of plastic waste to the Indian Ocean.

To address the lack of reliable data on urban waste accumulation, we present a city-scale, open-data-based approach to map visible MSW in Dar es Salaam using deep learning and street-view imagery (SVI). In close collaboration with OpenMap Development Tanzania and HeiGIT, we developed an open-source end-to-end workflow that involves collecting, annotating, and processing 360-degree SVI across 41 wards, training a deep learning classification model to detect solid waste, and generating a high-resolution MSW pollution indicator. This approach provides actionable spatial insights to optimize urban cleaning strategies, reduce health risks linked to water contamination, and support evidence-based planning for more sustainable waste management.

The Street-view imagery was collected between throughout 2024 by OMDTZ using a Bajaj tricycle equipped with a GoPro Max 360° camera. This data collection effort covered major roads across Dar es Salaam. The imagery was made publicly available on Mapillary to enable open access and collaborative research.

To identify visible waste in street-view images, a two-step image annotation process was implemented using the open-source tool MapSwipe4Web for. Additionaly to manual labeling, we opted for Crowdsourced Pre-labeling: The MapSwipe community reviewed street-level panoramic images and flagged those containing visible waste. All positively labeled images were manually reviewed by the authors to ensure quality. Further manual labeling was conducted, particularly for underrepresented classes.

Images were annotated into the following three main classes: Waste Piles: Defined as accumulations of waste with horizontal and vertical extent, often indicative of illegal dumping or unmanaged MSW. Trash Bags: Properly packaged waste (typically in plastic or paper bags) that appears to be ready for collection. No Trash: Images with no visible waste.

To ensure spatial representativeness and reduce redundancy, images were sampled approximately every 10 meters along one-third of the road segments in each ward. In total, over 40,000 360° street-view panoramas were annotated. Due to the computational and geometric challenges associated with high-resolution equirectangular imagery, each panorama was segmented into 12 overlapping patches. This approach reduced computational load, minimized distortion effects, and maintained spatial context for classification. Further labelling on the image patches resulted in a final training dataset size of 7378 (with augmented 29605) waste images and 7640 (27410) no waste images for the trashbag model and 1818 (7325) waste images and 1920 (6965) no waste images for the waste model. A classification-based approach utilizing the YOLOv11 architecture was employed to detect visible waste, as it significantly reduces annotation effort by eliminating the need for bounding box labeling. This method was used because conventional object detection offers limited practical benefits and introduces unnecessary complexity to the annotation workflow.. The resulting models demonstrated strong performance, achieving precision scores of 0.87 for trash bags and 0.98 for waste piles, and recall scores of 0.86 and 0.98, respectively.

Nevertheless, some limitation need to be considered. For instance, the model occasionally struggled to distinguish between visually similar objects like trash bags and plastic buckets or plastic tarpaulins. For waste piles, materials like rubble or patterned floor mosaics sometimes led to misclassifications..

We deployed the trained models across the entire city, processing a total of 500,000 panoramic images covering 1300 kilometers of road network. The results were aggregated onto a hexagonal grid to produce a spatially explicit indicator of visible waste pollution. This analysis was further complemented with UAV-derived observations of waste piles along the Msimbazi River—a region largely inaccessible to ground-based street-view imaging—yielding a comprehensive waste pollution map for the entire study area.

Using this workflow we can show that there are several hotspots of waste pollution in Dar es Salaam mostly located in densly populated informal settlements, while the wards along the coastline show only little waste pollution. Combining the created data with data from OSM, it was recognised that there is a lot of open waste in the immediate vicinity of the drainage system, which can lead to a higher risk of flooding due to clogging.

Our results show the value of street view imagery for open mapping in OpenStreetMap and beyond. The extensive SVI of the entire street-network provides possibilities for other future usa-cases to enhance OSM like building material, blockage of drainage canals, road surface, etc.

The source data, code, and resulting datasets are publicly accessible, and the entire workflow is transferable to other geographic regions. The required resources are relatively low-cost, and open-source crowdsourcing tools, such as MapSwipe, can be leveraged to efficiently generate comprehensive datasets for model training.

We often say children are the future, but what if they could also map the future? In this talk, I'll share my experience and reflections on introducing OpenStreetMap to grade school learners and why it's not only possible but necessary. While OSM is already popular among university students and professionals, there's a largely untapped group that can benefit from learning about maps and spatial thinking from an early age; primary school students.

Using stories, activities and real-life examples from my volunteer work and academic journey, I'll highlight how teaching young learners about mapping can spark curiosity, sharpen digital skills and build a deeper understanding of their communities. I'll explore simple ways to introduce OSM to children without overwhelming them and how we can design context specific learning environment that encourages creativity and inclusion.
This session will also reflect on the importance of early exposure to open data principles, especially in communities that are often underrepresented in the geospatial field. If we want a more inclusive mapping future, we must start by nurturing young minds today.
Whether you are a mapper, educator, or just curious this talk is for you. Let us plant the seeds of spatial literacy early and watch them grow.

My Name is Ashok Thakulla, and I'm a geomatics Engineer from Nepal. My Journey in the OpenStreetMap (OSM) community began in 2020 as a second-year university student Mapper, driven by questions: Why are some places and communities still missing from the Maps? Since then, I have grown from a student mapper to a Global validator, Trainer, and Project Lead, a YouthMappers Leadership Fellow, and now, the YouthMappers Volunteer Regional Ambassador for Asia Region(2025).
In this lightning talk, I will share how youth-led mapping initiatives in Nepal have transformed both Communities and Mappers. I will reflect on how my journey from learner to mentor can resonate with African mappers, and how we can collaborate across continents.
Let’s imagine a future where Kathmandu and Kisumu co-host mapping campaigns, and student mentors from Nepal and Nigeria learn together.

Landsat surface temperature (LST) can be utilised for assessing global warming, evaluating vegetation adaptability, monitoring glaciers, tracking urban heat temperatures and land cover. This study aimed to accomplish the following objectives: (a) to ascertain land surface temperature for both dry and wet seasons; (b) to evaluate the NDVI for the dry and wet seasons; and (c) to investigate the correlation between NDVI and land surface temperature, as well as the impact of elevated temperatures on vegetation and public health in the Wa Municipal of the Upper West Region of Ghana.
The results of this study showed variations in temperatures in the dry and wet seasons. The annual assessment of these temperatures found that the LST values for the dry season in 2024 were higher than in 2019. The wet seasons in 2024 showed a drop in temperature compared to 2019, indicating an increase in rainfall and cloud cover, preventing the earth's surface from heating up. There was a high vegetation cover during the wet seasons for both 2019 and 2024 as compared to the vegetation cover in the dry season from 2019 to 2024.
The linear regression analyses indicated a negative correlation between Land Surface Temperature (LST) and Normalised Differential Vegetation Index (NDVI) in all seasons indicating that as vegetation cover decreases temperature rises.
To alleviate these impacts, management must concentrate on urban greening, healthcare readiness, climate-resilient agriculture and public awareness.

The OpenStreetMap (OSM) ecosystem is very vast, making it complicated to investigate user preferences for OSM-related software or topics. This ecosystem has an important community component and a large set of software resources that serve many different purposes, such as retrieving, editing, validating or converting data, collecting data in the field, routing, geoservices... These programs are increasingly present in the daily lives of OSM users, especially in countries outside the US-Europe axis (such as Latin America and Africa), where new users are becoming interested in OSM and the applications, which
is reflected in the significant increase in the number of contributions on the map. This research aims to survey the publication profile of the weeklyOSM [1], analyzing the content of the issues published on the last ten years (#272 to 768), since it began to be organized with the OSM Blog Collector [2], a system with free and open source code, designed, programmed and improved by TheFive [3] and which has been used to manage the content of the weekly publishings since its number 272, in September 2015. The weeklyOSM reports news from the reporting week, is produced by mappers and OSM enthusiasts and is independent from organizations and companies [4]. It covers currently 15 languages and has been informing the OSM user community without fail since its release as the German weekly OSM-Wochennotiz [5], whose initial issue was published on July 23, 2010. Its workflow naturally favors sampling OSM-related topics from a wide variety of sources, such as social networks, blogs, OpenStreetMap Foundation channels or institutional news sites. Thus, by analyzing their content, it is hoped that the results will serve as a proxy for understanding the interest in certain categories and the usage of certain software by OSM users. The methodological flow started with the initial export of the articles stored in the OSM Blog Collector (OSMBC), in a file in .CSV format. The records were then imported into a PostgreSQL database and analyzed using SQL. Of the initial 32,261 records (articles) and 35 categories, the records prior to number 272 were excluded and the categories were standardized to conform to the actual weeklyOSM's categories (About us, Breaking news, Community, Did you know that..., Education, Events, Humanitarian OSM, Imports, Licenses, Local chapter news, Mapping, Mapping campaigns, Maps, Open Data, OpenStreetMap Foundation, OSM in action, OSM in the media, OSM research, Other Geo Things, Picture, Programming, Releases, Software, Upcoming Events). Thus, after the initial processing, 18,672 records (articles) were obtained, classified into the current 24 categories and considered as the initial set for the analysis. In a second stage, queries were made regarding the occurrence of 102 software in the articles (e.g. “Panoramax”), saving the results files in .csv format and making them available on GitHub [6], with its
subsequent classification into 14 software groups (3D model, aerial imagery, API, converter, data extraction, data quality, desktop editor, library, mobile editor, notes editor, OSM based service, routing, street level imagery, tagging) and re-importing them into the database in a new table, forming a second set of records. Making the data and results available on GitHub guarantees the transparency and reproducibility of the analysis. The search for software and the design of the categories were inspired by the sources [7-11]. From the starting set for the analysis, the initial and final numbers of the category (e.g. “Mapping”) were collected, and the total number of articles in the category was calculated, resulting in a ranking showing the most popular categories for publishing articles. From the second set (only the records of the 102 selected software), the software' indices were calculated, which correspond to the software's participation in the group to which it belongs. The results found in the first stage of the analysis show that the ten most popular weeklyOSM categories to associate with articles were: “Mapping” (2,778 articles), “Other geo things” (2,331), "Community" (2,212), “Did you know that...” (1,177), “Events” (1,153), “Maps” (1,064), “Software” (1,060), "Programming" (963), “Humanitarian OSM” (821) and “OpenStreetMap Foundation” (782); and the full ranking can be accessed on the GitHub [12]. In the second stage of the analysis, with the set of data which contains only the records of articles that included the 102 selected software, two main statistics were obtained: i) the number of articles for the 14 groups of software and ii) the participation index of a given software in the group to which it belongs. For the first processing (i), the five groups with the highest number of articles were: “Desktop editor” (1,193), “OSM based service” (968), "Routing" (524), “Mobile editor” (522) and “Street Level Imagery” (424); and the full results are found on the GitHub [13]. For the second processing (ii), there was a greater variety of software in the “OSM based service”, “Desktop editor” and “Mobile editor” groups; the complete set of graphs are found on the GitHub [14]. As a result of the research, we could infer that weeklyOSM, over the last ten years, has expressed the variety of themes and programs related to OSM, with a large representation of content pertinent to “mapping” and “community”, which are at the heart of the OSM ecosystem. Thus, could be inferred that the analysis had a representative result from the point of view
of reality; and c) in addition to this “panoramic” view of the content in general, it was possible to observe the participation of the software in their respective group, inferring their relevance in the context of the collaborative mapping with OSM. Limitations of the research include the difficulty in performing queries on very heterogeneous strings, requiring greater attention from the researcher and the static nature of the analysis, making it more time-consuming to carry out the workflow. With the publication of this research, we hope to highlight the wide variety of information resources available to OSM contributors and, in particular, to highlight the role of weeklyOSM as a representative vehicle for information on the OSM ecosystem, freely accessible to the community and which has fulfilled its objective without fail since its first edition on 2010.

[1] weeklyOSM Editorial Team. weeklyOSM. https://weeklyosm.eu
[2] weeklyOSM Editorial Team. OSM Blog. https://blog.openstreetmap.de/blog/2010/07/osm-wochennotiz-nr-1/
[3] TheFive et al. OSM Blog Collector. https://osmbc.openstreetmap.de/
[4] weeklyOSM Editorial Team. Blog OSM Histoire. https://blog.openstreetmap.de/mitmachen/
[5] TheFive. TheFive's OpenStreetMap user profile. https://www.osm.org/user/TheFive
[6] Souto, R. D. weeklyOSM-stats. https://github.com/raqueldeziderio/weeklyOSM-stats
[7] Comparison of editors. OpenStreetMap Wiki. https://wiki.openstreetmap.org/wiki/Comparison_of_editors
[8] ToastHawaii. OSM APPs Catalog. https://osm-apps.org/?category=edit
[9] OpenStreetMap contributors. List of OSM based services. OpenStreetMap Wiki.
https://wiki.openstreetmap.org/wiki/List_of_OSM-based_services
[10] https://software.wambachers-osm.website/ ("Improve the map" category)
[11] Editor usage stats. OpenStreetMap Wiki. https://wiki.openstreetmap.org/wiki/Editor_usage_stats
[12] Souto, R. D. https://github.com/raqueldeziderio/weeklyOSM-stats/tree/main/statistics
[13] Souto, R. D. https://github.com/raqueldeziderio/weeklyOSM-stats/tree/main/selection
[14] Souto, R. D. https://github.com/raqueldeziderio/weeklyOSM-stats/tree/main/graphics_software_in_group

Plastic pollution poses a significant environmental challenge in urban areas, contributing approximately 80% of marine litter and severely impacting cities like Nkumba, Uganda, where inadequate waste management amplifies ecological and public health risks. Traditional detection methods, such as field surveys, are labor-intensive, costly, and unscalable, making them impractical for large-scale monitoring in resource-constrained African contexts. Earth observation, particularly Sentinel-2 satellite imagery, offers a scalable, cost-effective alternative through spectral indices like the Plastic Index (PI) and Floating Debris Index (FDI). However, accurate visualization and spatial contextualization of detected plastic litter hotspots require reliable basemaps. OpenStreetMap (OSM), with its freely accessible, community-driven geospatial data, serves as an effective basemap for mapping detection results and defining study area boundaries. This study leverages Sentinel-2 imagery, processed in Google Earth Engine (GEE), to detect and map plastic litter hotspots in Nkumba, Uganda, from June 2024 to February 2025, using OSM as an a basemap and area location map to enhance the interpretability and access of findings for environmental management in African urban settings.

Access to reliable geospatial data is essential for effective planning, infrastructure development, and service delivery. The Upper East Region of Ghana faces challenges related to poor accessibility mapping, outdated spatial data, and a lack of digital infrastructure information. These challenges hinder decision-making for local governments, development agencies, civil society organizations, and even individuals who want to use the data.
This project aims to bridge this data gap by mapping and updating the accessibility of public services, infrastructure, and points of interest using Mapillary and OpenStreetMap (OSM). By capturing street-level imagery and integrating geospatial data into OSM, we will provide an open and accessible dataset that can support urban planning, disaster risk management, and mobility improvements. This will help people with disabilities and help them identify points of interest in their neighborhood.
This project will provide high-quality, up-to-date geospatial data to support infrastructure planning, mobility improvements, and public service accessibility in the Upper East Region. By leveraging Mapillary and OpenStreetMap, the initiative will enhance decision-making processes, promote open data usage, and empower local communities with digital mapping skills.

Spatial Girls Network is a women led organization from Malawi. It all started as the result of the Open Women Awards in 2024. The three Co-founders were recognized as emerging stars in open mapping from Malawi. With this recognition, they thought of doing something that would also help fellow ladies to have access to different opportunities, take up leadership roles and make a difference.
The mission for Spatial Girls Network is to empower and inspire girls and young women in Geospatial science and technology, so that they contribute to decision making hence creating a sustainable community.
We would like to share what the organization is about, what we have done so far, call for collaboration and that we are ready to learn from the different communities on how we can give better impact and contribute to a sustainable community.