A data fusion-based framework to integrate multi-source VGI in an authoritative land use database  

作　　者：Lanfa Liu Ana-Maria Olteanu-Raimond Laurence Jolivet Arnaud-le Bris Linda See 

机构地区：[1]LASTIG,Univ Gustave Eiffel,ENSG,IGN,Saint-Mande,France [2]International Institute for Applied Systems Analysis(IIASA),Laxenburg,Austria

出　　处：《International Journal of Digital Earth》2021年第4期480-509,共30页国际数字地球学报（英文）

基　　金：supported by Horizon 2020 Framework Programme[grant number 689812].

摘　　要：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。

关 键 词：Data fusion DempsterShafer Theory land use OCSGE volunteered geographic information 

分 类 号：P20[天文地球—测绘科学与技术]