Assess citizen science based land cover maps with remote sensing products : the Ground Truth 2.0 data quality tool
Maso, Joan (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Julià, Núria (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Zabala Torres, Alaitz (Universitat Autònoma de Barcelona. Departament de Geografia)
Prat Carrió, Ester (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Van der Kwast, Johannes (IHE Delft Institute for Water Education, Department of Water Resources and Ecosystems)
Domingo-Marimon, Cristina (Centre de Recerca Ecològica i d'Aplicacions Forestals)

Fecha:	2020
Resumen:	One of the main concerns in adopting citizen science is data quality. Derived products inherit intrinsic limitations of the capture methodology as well as the uncertainties in observations. OpenStreetMap tools are designed to minimize uncertainties in positional accuracy by ensuring a good co-registration of the observations with imagery or direct use of GPS. When thematically annotating objects contributed by citizens, uncertainty increases. During the H2020 GroundTruth 2. 0 project two land-cover products derived from OSM were analyzed; one created by the University of Heidelberg (http://osmlanduse. org) and another elaborated by University of Coimbra (https://vgi. uc. pt/vgi/osm/osm2lulc/). To be able to assess the quality of both maps, a third product derived from remote sensing was introduced as a reference map. In GroundTruth 2. 0 a tool to show and compare maps as part of the MiraMon Map Browser was developed. The objective was to allow final users to auto-evaluate the quality of their region of interest. The confusion matrix has been used as a method to derive overall commission and omission estimators as well as the Kappa coefficient. Most of the discrepancies between OSM and remote sensing (RS) derived maps are related to different approaches used during data capturing. The data quality tool assesses the quality of individual observations exposed using the OGC standard and describes the quality in an interoperable approach based on QualityML.
Ayudas:	European Commission 689744 European Commission 776740 European Commission 730329
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; Versió publicada
Materia:	Remote sensing ; Quality measurement ; Standards development ; Geographic information systems ; Raster graphics ; Visualization ; Binary data ; Global Positioning System ; Matrices ; Error analysis
Publicado en:	Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), Vol. 11524 (2020) , p. 586-595

DOI: 10.1117/12.2570814

11 p, 1.8 MB

El registro aparece en las colecciones:
Documentos de investigación > Documentos de los grupos de investigación de la UAB > Centros y grupos de investigación (producción científica) > Ciencias > Methods and Applications in Remote Sensing and Geographic Information Systems Research Group (GRUMETS)
Documentos de investigación > Documentos de los grupos de investigación de la UAB > Centros y grupos de investigación (producción científica) > Ciencias > CREAF (Centre de Recerca Ecològica i d'Aplicacions Forestals)
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