ASSESSING VOLUNTEERED GEOGRAPHIC INFORMATION (VGI) QUALITY BASED ON CONTRIBUTORS' MAPPING BEHAVIOURS

20 citations as recorded by crossref.

1. Spatial data quality and uncertainty publication patterns and trends by bibliometric analysis E. Bielecka & E. Burek https://doi.org/10.1515/geo-2019-0018
2. Centaur VGI: An Evaluation of Engagement, Speed, and Quality in Hybrid Humanitarian Mapping K. Watkinson et al. https://doi.org/10.1080/24694452.2022.2058907
3. A Spatio-Temporal VGI Model Considering Trust-Related Information Y. Zhao et al. https://doi.org/10.3390/ijgi5020010
4. Assessing OpenStreetMap Data Using Intrinsic Quality Indicators: An Extension to the QGIS Processing Toolbox S. Sehra et al. https://doi.org/10.3390/fi9020015
5. Modeling aggregated expertise of user contributions to assess the credibility of OpenStreetMap features B. Muttaqien et al. https://doi.org/10.1111/tgis.12454
6. Artificial intelligence-based solution to estimate the spatial accuracy of volunteered geographic data N. Mohammadi & M. Malek https://doi.org/10.1080/14498596.2014.927337
7. An exploratory analysis of usability of Flickr tags for land use/land cover attribution Y. Yan et al. https://doi.org/10.1080/10095020.2018.1560044
8. Estimation of Wastewater Discharges by Means of OpenStreetMap Data J. Schilling & J. Tränckner https://doi.org/10.3390/w12030628
9. A framework for classification of volunteered geographic data based on user’s need N. Mohammadi & A. Sedaghat https://doi.org/10.1080/10106049.2019.1641562
10. An Open Data and Citizen Science Approach to Building Resilience to Natural Hazards in a Data-Scarce Remote Mountainous Part of Nepal B. Parajuli et al. https://doi.org/10.3390/su12229448
11. How sustainable is OpenStreetMap? Tracking individual trajectories of editing behavior X. Zhang et al. https://doi.org/10.1080/17538947.2024.2311320
12. Determining the data quality-influencing characteristics of participants in volunteered geographic information campaigns – the case of maritime disasters M. Tavra et al. https://doi.org/10.1080/19475705.2026.2659907
13. Digital Crowdsourcing and VGI: impact on information quality and business intelligence A. Bai et al. https://doi.org/10.1007/s41324-024-00572-2
14. Why we can read maps F. Mocnik https://doi.org/10.1080/15230406.2022.2127911
15. Collaborative toponyms in OpenStreetMap: an open-source framework to investigate the relationship with intrinsic quality parameters D. Miranda Nunes & S. Camboim https://doi.org/10.1080/15230406.2025.2566807
16. Shared Data Sources in the Geographical Domain—A Classification Schema and Corresponding Visualization Techniques F. Mocnik et al. https://doi.org/10.3390/ijgi8050242
17. A Contributor-Focused Intrinsic Quality Assessment of OpenStreetMap in Mozambique Using Unsupervised Machine Learning A. Madubedube et al. https://doi.org/10.3390/ijgi10030156
18. Exploiting the Potential of VGI Metadata to Develop A Data-Driven Framework for Predicting User’s Proficiency in OpenStreetMap Context G. Rajaram & K. Manjula https://doi.org/10.3390/ijgi8110492
19. Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap S. Sehra et al. https://doi.org/10.3390/ijgi6070195
20. Mining Trajectory Data and Geotagged Data in Social Media for Road Map Inference J. Li et al. https://doi.org/10.1111/tgis.12072