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Improving the accuracy of extant gridded population maps using multisource map fusion

文献类型：期刊论文

作者Gao, Peng3; Wu, Tianjun2; Ge, Yong1,4,5; Li, Zihan3
刊名GISCIENCE & REMOTE SENSING
出版日期2021-12-19
页码18
关键词Gridded population maps multisource map fusion uncertainty accuracy China
ISSN号1548-1603
DOI10.1080/15481603.2021.2012371
通讯作者Ge, Yong(gey@lreis.ac.cn)
英文摘要Population distribution is the most direct indicator used to describe human activities. Grid-based population distribution maps overcome the drawbacks of statistical data and are thus more suitable for integrated analysis with environmental data. However, current modeling methods seeking to improve accuracy ignore the role of many existing products, resulting in the ineffective use of advantageous information from different gridded population maps. In this study, the multisource map fusion method is developed and combined with population mapping to simply and efficiently achieve improved results accuracy by understanding the uncertainty of different gridded products. Three areas in China with significant environmental differences were used as case studies to validate the results. The case studies use representative Granger-Ramanathan (GR), variance weighted (VW), and random forest (RF) algorithms to implement multisource map fusion for three existing population maps - GPW4, LandScan, and WorldPop. The results of the experiments indicate that fusing multisource population maps can produce a more accurate product than input maps. Compared with the highest accuracy input data, the maximum reduction percentages for the RMSE and MAE of fused maps at the grid scale are 13.66% and 20.39% in the Beijing, Tianjin, and Hebei Region (BTHR); 15.47% and 18.29% in Guangdong Province; and 5.05% and 6.15% in Guizhou Province. This study provides new strategies for producing high-accuracy population distribution maps, and its inexpensive features make it especially suitable for developing countries to produce wide-range gridded population maps that are more accurate than existing products using a few surveys.
WOS关键词TIANJIN-HEBEI REGION ; IMPERVIOUS SURFACES ; SOIL MAPS ; MODEL ; SPATIALISATION ; PATTERN ; IMAGERY ; AREA
资助项目Strategic Priority Research Program of Chinese Academy of Sciences[XDA20030302] ; National Natural Science Foundation for Distinguished Young Scholars of China[41725006] ; Key Research and Development Program of Shaanxi[2021NY-170] ; Fundamental Research Funds for the Central Universities, CHD[300102120201]
WOS研究方向Physical Geography ; Remote Sensing
语种英语
WOS记录号WOS:000731853600001
出版者TAYLOR & FRANCIS LTD
资助机构Strategic Priority Research Program of Chinese Academy of Sciences ; National Natural Science Foundation for Distinguished Young Scholars of China ; Key Research and Development Program of Shaanxi ; Fundamental Research Funds for the Central Universities, CHD
源URL[http://ir.igsnrr.ac.cn/handle/311030/168450]  
专题中国科学院地理科学与资源研究所
通讯作者Ge, Yong
作者单位1.Univ Chinese Acad Sci, Beijing, Peoples R China
2.Changan Univ, Coll Sci, Dept Math & Informat Sci, Xian, Peoples R China
3.Changan Univ, Sch Earth Sci & Resources, Xian, Peoples R China
4.Changan Univ, Sch Land Engn, Xian, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Gao, Peng,Wu, Tianjun,Ge, Yong,et al. Improving the accuracy of extant gridded population maps using multisource map fusion[J]. GISCIENCE & REMOTE SENSING,2021:18.
APA Gao, Peng,Wu, Tianjun,Ge, Yong,&Li, Zihan.(2021).Improving the accuracy of extant gridded population maps using multisource map fusion.GISCIENCE & REMOTE SENSING,18.
MLA Gao, Peng,et al."Improving the accuracy of extant gridded population maps using multisource map fusion".GISCIENCE & REMOTE SENSING (2021):18.

入库方式： OAI收割

来源：地理科学与资源研究所

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