Nisreen Mahmoud
Nisreen Mahmoud is a GIS and Remote Sensing Expert with a specialization in environmental analysis, post-conflict assessment, and urban resilience. Graduated as a Surveying Engineer, she integrates advanced geospatial techniques using platforms such as ArcGIS Pro, Google Earth Engine, QGIS, and Python to support data-driven decision-making.
Nisreen’s recent work centers on mapping land use and land cover changes, assessing environmental damage from conflict, and guiding sustainable reconstruction planning—particularly in Khartoum, Sudan. She actively engages in open mapping initiatives, KRI OSM Sudan, using OpenStreetMap for humanitarian purposes, infrastructure analysis, and collaborative data validation.
In addition to her technical expertise, Nisreen is a strong advocate for geospatial storytelling and community engagement. She leads the podcast "البيئة تحكي" (The Environment Speaks), which highlights environmental challenges and innovations across the Arab world.
Session
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.