1. [1] M. F. Goodchild, "Citizens as sensors: the world of volunteered geography," GeoJournal, vol. 69, no. 4, pp. 211-221, 2007. 2. [2] J. Severinsen, M. de Roiste, F. Reitsma, and E. Hartato, "VGTrust: measuring trust for volunteered geographic information," International Journal of Geographical Information Science, vol. 33, no. 8, pp. 1683-1701, 2019. 3. [3] M. Drews et al., "The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models," Science of The Total Environment, vol. 894, p. 164962, 2023/10/10/ 2023, doi: [ DOI:10.1016/j.scitotenv.2023.164962] 4. [4] Z. Chang et al., "An updating of landslide susceptibility prediction from the perspective of space and time," Geoscience Frontiers, vol. 14, no. 5, p. 101619, 2023/09/01/ 2023, doi: [ DOI:10.1016/j.gsf.2023.101619] 5. [5] C. C. Fonte, L. Bastin, L. See, G. Foody, and F. Lupia, "Usability of VGI for validation of land cover maps," International Journal of Geographical Information Science, vol. 29, no. 7, pp. 1269-1291, 2015/07/03 2015, doi: 10.1080/13658816.2015.1018266. 6. [6] M. Moradi, S. Roche, and M. A. Mostafavi, "Exploring five indicators for the quality of OpenStreetMap road networks: a case study of Québec, Canada," Geomatica, pp. 1-31, 2022, doi: 10.1139/geomat-2021-0012. 7. [7] M. Ahmad, M. S. H. Khayal, and A. Tahir, "Analysis of Factors Affecting Adoption of Volunteered Geographic Information in the Context of National Spatial Data Infrastructure," ISPRS International Journal of Geo-Information, vol. 11, no. 2, p. 120, 2022. 8. [8] V. Antoniou and A. Skopeliti, "Measures and indicators of VGI quality: An overview," ISPRS annals of the photogrammetry, remote sensing and spatial information sciences, vol. 2, p. 345, 2015. 9. [9] C. Dai, D. Lin, E. Bertino, and M. Kantarcioglu, "An approach to evaluate data trustworthiness based on data provenance," in Workshop on Secure Data Management, 2008: Springer, pp. 82-98. 10. [10] M. F. Goodchild and L. Li, "Assuring the quality of volunteered geographic information," Spatial statistics, vol. 1, pp. 110-120, 2012. 11. [11] H. Senaratne, A. Mobasheri, A. L. Ali, C. Capineri, and M. Haklay, "A review of volunteered geographic information quality assessment methods," International Journal of Geographical Information Science, vol. 31, no. 1, pp. 139-167, 2017. 12. [12] M. Forghani and M. R. Delavar, "A quality study of the OpenStreetMap dataset for Tehran," ISPRS International Journal of Geo-Information, vol. 3, no. 2, pp. 750-763, 2014. 13. [13] N. Mohammadi and M. Malek, "Artificial intelligence-based solution to estimate the spatial accuracy of volunteered geographic data," Journal of Spatial Science, vol. 60, no. 1, pp. 119-135, 2015/01/02 2015, doi: 10.1080/14498596.2014.927337. 14. [14] G. Farajolahi and M. R. Delavar, "Provide a model for quality control of local spatial information for the analysis of traffic accident locations," presented at the The 2nd National Conference on Geospatial Information Technology, Tehran, Iran, 2016. [Online]. Available: http://fa.seminars.sid.ir/ViewPaper.aspx?ID=36253. 15. [15] A. Yang, H. Fan, and N. Jing, "Amateur or professional: Assessing the expertise of major contributors in OpenStreetMap based on contributing behaviors," ISPRS International Journal of Geo-Information, vol. 5, no. 2, p. 21, 2016. 16. [16] A. L. Ali and F. Schmid, "Data quality assurance for volunteered geographic information," in International Conference on Geographic Information Science, 2014: Springer, pp. 126-141. 17. [17] B. Vahedi Torgabe and A. A. Alesheykh, "Assessing the Attribute Accuracy of Volunteered Geographic Information," (in eng), Journal of Geomatics Science and Technology, Research vol. 5, no. 3, pp. 49-64, 2016. [Online]. Available: http://jgst.issge.ir/article-1-348-fa.html. 18. [18] M. Bishr and K. Janowicz, "Can we trust information?-the case of volunteered geographic information," in Towards Digital Earth Search Discover and Share Geospatial Data Workshop at Future Internet Symposium, volume, 2010, vol. 640. 19. [19] A. M. Forati and M. Karimipour, "Evaluate the quality of voluntary spatial information by accrediting users and their social groups," presented at the Conference on Surveying & Spatial Information, Tehran, 2016. [Online]. Available: http://fa.seminars.sid.ir/ViewPaper.aspx?ID=89018. 20. [20] A. Khosravi Kazazi and F. HoseinAli, "Increasing the quality of voluntary spatial information results based on EigenRumor algorithm," presented at the Conference on Surveying & Spatial Information, Tehran, 2017. [Online]. Available: http://fa.seminars.sid.ir/ViewPaper.aspx?ID=90158. 21. [21] J. N. Da Costa, "Novel tool for examination of data completeness based on a comparative study of VGI data and official building datasets," Geodetski Vestnik, vol. 60, no. 3, pp. 495-508, 2016. 22. [22] R. Martella, E. Clementini, and C. Kray, "Crowdsourcing geographic information with a gamification approach," Geodetski Vestnik, vol. 63, no. 2, 2019. 23. [23] R. Can, S. Kocaman, and C. Gokceoglu, "A convolutional neural network architecture for auto-detection of landslide photographs to assess citizen science and volunteered geographic information data quality," ISPRS International Journal of Geo-Information, vol. 8, no. 7, p. 300, 2019. 24. [24] A. Alghanim, M. Jilani, M. Bertolotto, and G. McArdle, "Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM," ISPRS International Journal of Geo-Information, vol. 10, no. 7, p. 436, 2021. [Online]. Available: https://www.mdpi.com/2220-9964/10/7/436. 25. [25] W. Shi, Z. Liu, Z. An, and P. Chen, "RegNet: a neural network model for predicting regional desirability with VGI data," International Journal of Geographical Information Science, vol. 35, no. 1, pp. 175-192, 2021/01/02 2021, doi: 10.1080/13658816.2020.1768261. 26. [26] S. Soltani, S. Sardari, M. S. pour, and S. Mousavi, Artificial Neural Networks: Basics, Applications, and Introduction to Easy NN-plus and NeuroSolutions Software. Tehran: Nass, 2010, p. 216. 27. [27] R. J. Shalkof, Artificial Neural Networks. Ahvaz: Shahid Chamran University of Ahvaz, 2003. 28. [28] L. Bragagnolo, R. V. da Silva, and J. M. V. Grzybowski, "Landslide susceptibility mapping with r.landslide: A free open-source GIS-integrated tool based on Artificial Neural Networks," Environmental Modelling & Software, vol. 123, p. 104565, 2020/01/01/ 2020, doi: [ DOI:10.1016/j.envsoft.2019.104565] 29. [29] P.Fogliaroni, F. D'Antonio and E. Clementini, "Data trustworthiness and user reputation as indicators of VGI quality," Geo-spatial Information Science, vol. 21, no. 3, pp. 213-233, 2018. 30. [30] J.C.H. Meier, "An Analysis of Quality for Volunteered Geographic Information ," M.S Thesis, Wilfrid Laurier University, Ontario, Canada, 2015.
|