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