{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T12:23:25Z","timestamp":1790425405068,"version":"4.1.0"},"reference-count":65,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,4,1]],"date-time":"2017-04-01T00:00:00Z","timestamp":1491004800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Nature Science Foundation of China","award":["41271538"],"award-info":[{"award-number":["41271538"]}]},{"name":"the Fundamental Research Funds for the Central Universities of China"},{"name":"the project funded by the priority academic program development of Jiangsu higher education institution"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 \u00b0C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions.<\/jats:p>","DOI":"10.3390\/s17040744","type":"journal-article","created":{"date-parts":[[2017,4,3]],"date-time":"2017-04-03T13:32:30Z","timestamp":1491226350000},"page":"744","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds"],"prefix":"10.3390","volume":"17","author":[{"given":"Yingbao","family":"Yang","sequence":"first","affiliation":[{"name":"School of Earth Science and Engineering, Hohai University, 8 Buddha City West Road, Nanjing 210098, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Earth Science and Engineering, Hohai University, 8 Buddha City West Road, Nanjing 210098, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Earth Science and Engineering, Hohai University, 8 Buddha City West Road, Nanjing 210098, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Natural Resources and Environment, Chizhou University, No.199 Muzhi Road, Chizhou 247000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Earth Science and Engineering, Hohai University, 8 Buddha City West Road, Nanjing 210098, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1006\/jare.2001.0867","article-title":"Micrometeorological modeling to understand the thermal anomaly in the sand dunes across the Israel\u2013Egypt border","volume":"51","author":"Qin","year":"2002","journal-title":"J. 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