{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T22:08:47Z","timestamp":1778278127097,"version":"3.51.4"},"reference-count":83,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,3,11]],"date-time":"2021-03-11T00:00:00Z","timestamp":1615420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the the Second Tibetan Plateau Scientific Expedition and Research program (STEP)","award":["2019QZKK0603"],"award-info":[{"award-number":["2019QZKK0603"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971019"],"award-info":[{"award-number":["41971019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Open Research Fund of National Earth Observation Data Center","award":["NODAOP2020018"],"award-info":[{"award-number":["NODAOP2020018"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Producing gridded electric power consumption (EPC) maps at a fine geographic scale is critical for rational deployment and effective utilization of electric power resources. Brightness of nighttime light (NTL) has been extensively adopted to evaluate the spatial patterns of EPC at multiple geographical scales. However, the blooming effect and saturation issue of NTL imagery limit its ability to accurately map EPC. Moreover, limited sectoral separation in applying NTL leads to the inaccurate spatial distribution of EPC, particularly in the case of industrial EPC, which is often a dominant portion of the total EPC in China. This study pioneers the separate estimation of spatial patterns of industrial and nonindustrial EPC over mainland China by jointly using points of interest (POIs) and multiple remotely sensed data in a random forests (RF) model. The POIs provided fine and detailed information about the different socioeconomic activities and played a significant role in determining industrial and nonindustrial EPC distribution. Based on the RF model, we produced industrial, non-industrial, and overall EPC maps at a 1 km resolution in mainland China for 2011. Compared against statistical data at the county level, our results showed a high accuracy (R2 = 0.958 for nonindustrial EPC estimation, 0.848 for industrial EPC estimation, and 0.913 for total EPC). This study indicated that the proposed RF-based method, integrating POIs and multiple remote sensing data, can markedly improve the accuracy for estimating EPC. This study also revealed the great potential of POIs in mapping the distribution of socioeconomic parameters.<\/jats:p>","DOI":"10.3390\/rs13061058","type":"journal-article","created":{"date-parts":[[2021,3,11]],"date-time":"2021-03-11T05:38:22Z","timestamp":1615441102000},"page":"1058","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Mapping China\u2019s Electronic Power Consumption Using Points of Interest and Remote Sensing Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6993-240X","authenticated-orcid":false,"given":"Cheng","family":"Jin","sequence":"first","affiliation":[{"name":"Ocean College, Zhejiang University, Zhoushan 316021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yili","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8130-7447","authenticated-orcid":false,"given":"Xuchao","family":"Yang","sequence":"additional","affiliation":[{"name":"Ocean College, Zhejiang University, Zhoushan 316021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1778-2112","authenticated-orcid":false,"given":"Naizhuo","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Land Resource Management, School of Humanities and Law, Northeastern University, Shenyang 110169, China"},{"name":"Division of Clinical Epidemiology, McGill University Health Centre, Montreal, QC H3A 1A1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zutao","family":"Ouyang","sequence":"additional","affiliation":[{"name":"Department of Earth System Science, Stanford University, Stanford, CA 94305, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7533-3294","authenticated-orcid":false,"given":"Wenze","family":"Yue","sequence":"additional","affiliation":[{"name":"Department of Land Management, Zhejiang University, Hangzhou 310058, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1080\/01431160802345685","article-title":"Spatial characterization of electrical power consumption patterns over India using temporal DMSP-OLS night-time satellite data","volume":"30","author":"Chand","year":"2009","journal-title":"Int. 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