{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:52:16Z","timestamp":1760143936901,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T00:00:00Z","timestamp":1709856000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"second Tibetan Plateau Scientific Expedition and Research (STEP)","award":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"],"award-info":[{"award-number":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"]}]},{"name":"Innovative Research Program of the International Research Center of Big Data for Sustainable Development Goals","award":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"],"award-info":[{"award-number":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"]}]},{"name":"Hainan Hundred Special Project","award":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"],"award-info":[{"award-number":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"]}]},{"name":"National Natural Science Foundation of China","award":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"],"award-info":[{"award-number":["2019QZKK0806","CBAS2022IRP03","31, JTT [2018]","42071312"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Earth observation by remote sensing plays a crucial role in granite extraction, and many current studies use thermal infrared data from sensors such as ASTER. The challenge lies in the low spatial resolution of these satellites, hindering precise rock type identification. A breakthrough emerges with the Thermal Infrared Spectrometer (TIS) on the Sustainable Development Science Satellite 1 (SDGSAT-1) launched by the Chinese Academy of Sciences. With an exceptional 30 m spatial resolution, SDGSAT-1 TIS opens avenues for accurate granite extraction using remote sensing. This study, exemplified in Xinjiang\u2019s Karamay region, introduces the BR-ISauvola method, leveraging SDGSAT-1 TIS data. The approach combines band ratio with adaptive k-value selection using local grayscale statistical features for Sauvola thresholding. Focused on large-scale granite extraction, results show F1 scores above 70% for Otsu, Sauvola, and BR-ISauvola. Notably, BR-ISauvola achieves the highest accuracy at 82.11%, surpassing Otsu and Sauvola by 9.62% and 0.34%, respectively. This underscores the potential of SDGSAT-1 TIS data as a valuable resource for granite extraction. The proposed method efficiently utilizes spectral information, presenting a novel approach for rapid granite extraction using remote sensing TIS imagery, even in scenarios with low spectral resolution and a single data source.<\/jats:p>","DOI":"10.3390\/s24061750","type":"journal-article","created":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T03:52:11Z","timestamp":1709869931000},"page":"1750","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Granite Extraction Based on the SDGSAT-1 Satellite Thermal Infrared Spectrometer Imagery"],"prefix":"10.3390","volume":"24","author":[{"given":"Boqi","family":"Yuan","sequence":"first","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"College of Resources and Environment, Yanqi Lake Campus of University of Chinese Academy of Sciences, Beijing 101408, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6084-1889","authenticated-orcid":false,"given":"Qinjun","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"Kashi Aerospace Information Research Institute, Kashi 844199, China"},{"name":"Key Laboratory of the Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China"}]},{"given":"Jingyi","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"College of Resources and Environment, Yanqi Lake Campus of University of Chinese Academy of Sciences, Beijing 101408, China"}]},{"given":"Wentao","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"College of Resources and Environment, Yanqi Lake Campus of University of Chinese Academy of Sciences, Beijing 101408, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8014-434X","authenticated-orcid":false,"given":"Chaokang","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3156","DOI":"10.3390\/rs5073156","article-title":"Targeting Mineral Resources with Remote Sensing and Field Data in the Xiemisitai Area, West Junggar, Xinjiang, China","volume":"5","author":"Liu","year":"2013","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Luo, S., Yin, S., Chen, J., Wu, Y., and Chen, X. 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