{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T08:27:12Z","timestamp":1768984032228,"version":"3.49.0"},"reference-count":79,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T00:00:00Z","timestamp":1708560000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["72073125"],"award-info":[{"award-number":["72073125"]}]},{"name":"National Natural Science Foundation of China","award":["2021126"],"award-info":[{"award-number":["2021126"]}]},{"name":"Youth Innovation Promotion Association of the Chinese Academy of Science","award":["72073125"],"award-info":[{"award-number":["72073125"]}]},{"name":"Youth Innovation Promotion Association of the Chinese Academy of Science","award":["2021126"],"award-info":[{"award-number":["2021126"]}]},{"name":"China-Pakistan Joint Research Center of Earth Sciences","award":["72073125"],"award-info":[{"award-number":["72073125"]}]},{"name":"China-Pakistan Joint Research Center of Earth Sciences","award":["2021126"],"award-info":[{"award-number":["2021126"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>It is crucial to detect and classify industrial heat sources for sustainable industrial development. Sustainable Development Science Satellite 1 (SDGSAT-1) thermal infrared spectrometer (TIS) data were first introduced for detecting industrial heat source production areas to address the difficulty in identifying factories with low combustion temperatures and small scales. In this study, a new industrial heat source identification and classification model using SDGSAT-1 TIS and Landsat 8\/9 Operational Land Imager (OLI) data was proposed to improve the accuracy and granularity of industrial heat source recognition. First, multiple features (thermal and optical features) were extracted using SDGSAT-1 TIS and Landsat 8\/9 OLI data. Second, an industrial heat source identification model based on a support vector machine (SVM) and multiple features was constructed. Then, industrial heat sources were generated and verified based on the topological correlation between the identification results of the production areas and Google Earth images. Finally, the industrial heat sources were classified into six categories based on point-of-interest (POI) data. The new model was applied to the Beijing\u2013Tianjin\u2013Hebei (BTH) region of China. The results showed the following: (1) Multiple features enhance the differentiation and identification accuracy between industrial heat source production areas and the background. (2) Compared to active-fire-point (ACF) data (375 m) and Landsat 8\/9 thermal infrared sensor (TIRS) data (100 m), nighttime SDGSAT-1 TIS data (30 m) facilitate the more accurate detection of industrial heat source production areas. (3) Greater than 2~6 times more industrial heat sources were detected in the BTH region using our model than were reported by Ma and Liu. Some industrial heat sources with low heat emissions and small areas (53 thermal power plants) were detected for the first time using TIS data. (4) The production areas of cement plants exhibited the highest brightness temperatures, reaching 301.78 K, while thermal power plants exhibited the lowest brightness temperatures, averaging 277.31 K. The production areas and operational statuses of factories could be more accurately identified and monitored with the proposed approach than with previous methods. A new way to estimate the thermal and air pollution emissions of industrial enterprises is presented.<\/jats:p>","DOI":"10.3390\/rs16050768","type":"journal-article","created":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T11:28:47Z","timestamp":1708601327000},"page":"768","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["The Potential of Using SDGSAT-1 TIS Data to Identify Industrial Heat Sources in the Beijing\u2013Tianjin\u2013Hebei Region"],"prefix":"10.3390","volume":"16","author":[{"given":"Yanmei","family":"Xie","sequence":"first","affiliation":[{"name":"College of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6289-7616","authenticated-orcid":false,"given":"Caihong","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7883-9506","authenticated-orcid":false,"given":"Yindi","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]},{"given":"Dongmei","family":"Yan","sequence":"additional","affiliation":[{"name":"College of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Bo","family":"Cheng","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Xiaolin","family":"Hou","sequence":"additional","affiliation":[{"name":"College of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Hongyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Optoelectronics, Fudan University, Shanghai 200433, China"}]},{"given":"Bihong","family":"Fu","sequence":"additional","affiliation":[{"name":"Innovation Academy for Microsatellites, Chinese Academy of Sciences, Shanghai 201204, China"}]},{"given":"Guangtong","family":"Wan","sequence":"additional","affiliation":[{"name":"College of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"127237","DOI":"10.1016\/j.fuel.2022.127237","article-title":"Current Progress of Process Integration for Waste Heat Recovery in Steel and Iron Industries","volume":"338","author":"Inayat","year":"2023","journal-title":"Fuel"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101221","DOI":"10.1016\/j.tsep.2022.101221","article-title":"Heat Pipe-Based Waste Heat Recovery Systems: Background and Applications","volume":"29","author":"Abdelkareem","year":"2022","journal-title":"Therm. 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