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Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information

, , , , , , , , , , and . ISPRS International Journal of Geo-Information, 5 (5): 55 (2016)

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Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information, , , , , , , , , and 1 other author(s). ISPRS International Journal of Geo-Information, 5 (5): 55 (2016)Actor-network theory: a suitable framework to understand how land cover mapping projects develop?, , and . Land Use Policy, 20 (4): 299-309 (2003/10)Opening practice: supporting reproducibility and critical spatial data science., and . J. Geogr. Syst., 23 (4): 477-496 (2021)Geosensor Network Optimisation to Support Decisions at Multiple Scales., and . W2GIS, volume 13912 of Lecture Notes in Computer Science, page 3-16. Springer, (2023)Comparing and Combining Different Expert Relations of How Land Cover Ontologies Relate., , and . SDH, page 573-583. Springer, (2004)Moving from Pixels to Parcels: the Use of Possibility Theory to Explore the Uncertainty Associated object Oriented Remote Sensing., , , , , , , and . SDH, page 487-500. Springer, (2008)Use of airborne polarimetric SAR, optical and elevation data for mapping and monitoring of salt marsh vegetation habitats., , and . SAR, volume 9243 of SPIE Proceedings, page 92430N. SPIE, (2014)A Comparison of Geographically Weighted Principal Components Analysis Methodologies (Short Paper)., , , , , , and . COSIT, volume 240 of LIPIcs, page 21:1-21:6. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2022)Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map., , , , , , and . Remote. Sens., 8 (3): 261 (2016)Multiscale spatially varying coefficient modelling using a Geographical Gaussian Process GAM., , and . Int. J. Geogr. Inf. Sci., 38 (1): 27-47 (January 2024)