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Therefore, better understanding of the relationship between NTL intensity and human activities can help extend the applications of NTL remote sensing data. Different from the global effect of human activities on NTL intensity discussed in previous studies, we focused more attention to the local effect caused by the spatial heterogeneity of human activities with the support of the multiscale geographically weighted regression (MGWR) model in this study. In particular, the Suomi National Polar Orbiting Partnership\/Visible Infrared Imaging Radiometer Suite (NPP\/VIIRS) NTL data within Chongqing, China were taken as example, and the point of interest (POI) data and road network data were adopted to characterize the intensity of human activity type. Our results show that there is significant spatial variation in the effect of human activities to the NTL intensity, since the accuracy of fitted MGWR (adj.R2: 0.86 and 0.87 in 2018 and 2020, respectively; AICc: 4844.63 and 4623.27 in 2018 and 2020, respectively) is better than that of both the traditional ordinary least squares (OLS) model and the geographically weighted regression (GWR) model. Moreover, we found that almost all human activity features show strong spatial heterogeneity and their contribution to NTL intensity varies widely across different regions. For instance, the contribution of road network density is more homogeneous, while residential areas have an obviously heterogeneous distribution which is associated with house vacancy. In addition, the contributions of the commercial event and business also have a significant spatial heterogeneity distribution, but show a distinct decrement when facing the COVID-19 pandemic. Our study successfully explores the relationship between NTL intensity and human activity features considering the spatial heterogeneity, which aims to provide further insights into the future applications of NTL data.<\/jats:p>","DOI":"10.3390\/rs14225695","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T04:21:45Z","timestamp":1668399705000},"page":"5695","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Analyzing the Spatially Heterogeneous Relationships between Nighttime Light Intensity and Human Activities across Chongqing, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Jihao","family":"Wu","sequence":"first","affiliation":[{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China"},{"name":"The Academy of Digital China, Fuzhou University, Fuzhou 350108, China"}]},{"given":"Yue","family":"Tu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3654-9658","authenticated-orcid":false,"given":"Zuoqi","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China"},{"name":"The Academy of Digital China, Fuzhou University, Fuzhou 350108, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5628-0003","authenticated-orcid":false,"given":"Bailang","family":"Yu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.rse.2017.01.005","article-title":"Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics","volume":"192","author":"Bennett","year":"2017","journal-title":"Remote Sens. 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