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Academy of Surveying and Mapping Basic Research Fund Program","award":["2019YFB2102503"],"award-info":[{"award-number":["2019YFB2102503"]}]},{"name":"Chinese Academy of Surveying and Mapping Basic Research Fund Program","award":["2019YFB2102500"],"award-info":[{"award-number":["2019YFB2102500"]}]},{"name":"Chinese Academy of Surveying and Mapping Basic Research Fund Program","award":["42201434"],"award-info":[{"award-number":["42201434"]}]},{"name":"Chinese Academy of Surveying and Mapping Basic Research Fund Program","award":["201806"],"award-info":[{"award-number":["201806"]}]},{"name":"Chinese Academy of Surveying and Mapping Basic Research Fund Program","award":["AR2111"],"award-info":[{"award-number":["AR2111"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing images of nighttime lights (NTL) were successfully used at global and regional scales for various applications, including studies on population, politics, economics, and environmental protection. The Suomi National Polar-orbiting Partnership with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data has the advantages of high temporal resolution, long coverage time series, and wide spatial range. The spatial resolution of the monthly and annual composite data of NPP-VIIRS NTL is only 500 m, which hinders studies requiring higher resolution. We propose a multi-source spatial variable and Multiscale Geographically Weighted Regression (MGWR)-based method to achieve the downscaling of NPP-VIIRS NTL data. An MGWR downscaling framework was implemented to obtain NTL data at 120 m resolution based on auxiliary data representing socioeconomic or physical geographic attributes. The downscaled NTL data were validated against LuoJia1-01 imagery based on the coefficient of determination (R2) and the root-mean-square error (RMSE). The results suggested that the spatial resolution of the data was enhanced after downscaling, and the MGWR-based downscaling results demonstrated higher R2 (R2 = 0.9141) and lower RMSE than those of Geographically Weighted Regression and Random Forest-based algorithms. Additionally, MGWR can reveal the different relationships between multiple auxiliary and NTL data. Therefore, this study demonstrates that the spatial resolution of NPP-VIIRS NTL data is improved from 500 m to 120 m upon downscaling, thereby facilitating NTL-based applications.<\/jats:p>","DOI":"10.3390\/rs14246400","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T08:41:41Z","timestamp":1671439301000},"page":"6400","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Spatial Downscaling of NPP-VIIRS Nighttime Light Data Using Multiscale Geographically Weighted Regression and Multi-Source Variables"],"prefix":"10.3390","volume":"14","author":[{"given":"Shangqin","family":"Liu","sequence":"first","affiliation":[{"name":"Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China"},{"name":"Geospatial Big Data Application Research Center, Chinese Academy of Surveying and Mapping, Beijing 100036, China"},{"name":"National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China"},{"name":"Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5519-934X","authenticated-orcid":false,"given":"Xizhi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Geospatial Big Data Application Research Center, Chinese Academy of Surveying and Mapping, Beijing 100036, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China"},{"name":"Geospatial Big Data Application Research Center, Chinese Academy of Surveying and Mapping, Beijing 100036, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agen","family":"Qiu","sequence":"additional","affiliation":[{"name":"Geospatial Big Data Application Research Center, Chinese Academy of Surveying and Mapping, Beijing 100036, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liujia","family":"Chen","sequence":"additional","affiliation":[{"name":"State Geospatial Information Center, Beijing 100070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Huang","sequence":"additional","affiliation":[{"name":"Faculty of Geology and Geomatics, Tianjin Chengjian University, Tianjin 300384, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"Chen","sequence":"additional","affiliation":[{"name":"Geospatial Big Data Application Research Center, Chinese Academy of Surveying and Mapping, Beijing 100036, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics and Geographic Sciences, Liaoning Technical University, Fuxin 123000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3061","DOI":"10.1080\/01431160010007015","article-title":"Census from Heaven: An estimate of the global human population using night-time satellite imagery","volume":"22","author":"Sutton","year":"2001","journal-title":"Int. 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