The potential of citizens as a source of geographical information has been recognized for many years.Such activity has grown recently due to the proliferation of inexpensive location aware devices and an ability to sh...The potential of citizens as a source of geographical information has been recognized for many years.Such activity has grown recently due to the proliferation of inexpensive location aware devices and an ability to share data over the internet.Recently,a series of major projects,often cast as citizen observatories,have helped explore and develop this potential for a wide range of applications.Here,some of the experiences and learnings gained from part of one such project,which aimed to further the role of citizen science within Earth observation and help address environmental challenges,LandSense,are shared.The key focus is on quality assurance of citizen generated data on land use and land cover especially to support analyses of remotely sensed data and products.Particular focus is directed to quality assurance checks on photographic image quality,privacy,polygon overlap,positional accuracy and offset,contributor agreement,and categorical accuracy.The discussion aims to provide good practice advice to aid future studies and help fulfil the full potential of citizens as a source of volunteered geographical information(VGI).展开更多
Updating an authoritative Land Use and Land Cover(LULC)database requires many resources.Volunteered geographic information(VGI)involves citizens in the collection of data about their spatial environment.There is a gro...Updating an authoritative Land Use and Land Cover(LULC)database requires many resources.Volunteered geographic information(VGI)involves citizens in the collection of data about their spatial environment.There is a growing interest in using existing VGI to update authoritative databases.This paper presents a framework aimed at integrating multi-source VGI based on a data fusion technique,in order to update an authoritative land use database.Each VGI data source is considered to be an independent source of information,which is fused together using Dempster-Shafer Theory(DST).The framework is tested in the updating of the authoritative land use data produced by the French National Mapping Agency.Four data sets were collected from several in-situ and remote campaigns run between 2018 and 2020 by contributors with varying profiles.The data fusion approach achieved an overall accuracy of 85.6%for the 144 features having at least two contributions when the confidence threshold was set to 0.05.Despite the heterogeneity and limited amount of VGI used,the results are promising,with 99%of the LU polygons updated or enriched.These results show the potential of using multi-source VGI to update or enrich authoritative LU data and potentially LULC data more generally。展开更多
基金funded by the European Commission’s Horizon 2020 program as part of the LandSense project[grant number 689812]Horizon 2020[LandSense,689812]。
文摘The potential of citizens as a source of geographical information has been recognized for many years.Such activity has grown recently due to the proliferation of inexpensive location aware devices and an ability to share data over the internet.Recently,a series of major projects,often cast as citizen observatories,have helped explore and develop this potential for a wide range of applications.Here,some of the experiences and learnings gained from part of one such project,which aimed to further the role of citizen science within Earth observation and help address environmental challenges,LandSense,are shared.The key focus is on quality assurance of citizen generated data on land use and land cover especially to support analyses of remotely sensed data and products.Particular focus is directed to quality assurance checks on photographic image quality,privacy,polygon overlap,positional accuracy and offset,contributor agreement,and categorical accuracy.The discussion aims to provide good practice advice to aid future studies and help fulfil the full potential of citizens as a source of volunteered geographical information(VGI).
基金supported by Horizon 2020 Framework Programme[grant number 689812].
文摘Updating an authoritative Land Use and Land Cover(LULC)database requires many resources.Volunteered geographic information(VGI)involves citizens in the collection of data about their spatial environment.There is a growing interest in using existing VGI to update authoritative databases.This paper presents a framework aimed at integrating multi-source VGI based on a data fusion technique,in order to update an authoritative land use database.Each VGI data source is considered to be an independent source of information,which is fused together using Dempster-Shafer Theory(DST).The framework is tested in the updating of the authoritative land use data produced by the French National Mapping Agency.Four data sets were collected from several in-situ and remote campaigns run between 2018 and 2020 by contributors with varying profiles.The data fusion approach achieved an overall accuracy of 85.6%for the 144 features having at least two contributions when the confidence threshold was set to 0.05.Despite the heterogeneity and limited amount of VGI used,the results are promising,with 99%of the LU polygons updated or enriched.These results show the potential of using multi-source VGI to update or enrich authoritative LU data and potentially LULC data more generally。
