{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T12:32:49Z","timestamp":1764333169669,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T00:00:00Z","timestamp":1653868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2020YFA0608703","42171370","41830648","21-Y20B01-9001-19\/22"],"award-info":[{"award-number":["2020YFA0608703","42171370","41830648","21-Y20B01-9001-19\/22"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["2020YFA0608703","42171370","41830648","21-Y20B01-9001-19\/22"],"award-info":[{"award-number":["2020YFA0608703","42171370","41830648","21-Y20B01-9001-19\/22"]}]},{"name":"China High-Resolution Earth Observation System","award":["2020YFA0608703","42171370","41830648","21-Y20B01-9001-19\/22"],"award-info":[{"award-number":["2020YFA0608703","42171370","41830648","21-Y20B01-9001-19\/22"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite-derived rugged land surface temperature (LST) is an important parameter indicating the status of the Earth\u2019s surface energy budget and its seasonal\/temporal dynamic change. However, existing LST products from rugged areas are more prone to error when supporting applications in mountainous areas and Earth surface processes that occur at high spatial and temporal resolutions. This research aimed to develop a method for generating rugged LST with a high temporal and spatial resolution by using an improved ensemble LST model combining three regressors, including a random forest, a ridge, and a support vector machine. Different combinations of high-resolution input parameters were also considered in this study. The input datasets included Moderate Resolution Imaging Spectroradiometer (MODIS) LST datasets (MxD11A1) for nighttime, temporal Sentinel-2 Multispectral Instrument (MSI) datasets, and digital elevation model (DEM) datasets. The 30 m rugged LST datasets derived were compared against an in situ LST dataset obtained at Saihanba Forest Park (SFP) sites and an ASTER-derived 90 m LST, respectively. The results with in situ measurements demonstrated significant LST details, with an R2 higher than 0.95 and RMSE around 3.00 K for both Terra\/MOD- and Aqua\/MYD-based LST datasets, and with slightly better results being obtained from the Aqua\/MYD-based LST than that from Terra\/MOD. The inter-comparison results with ASTER LST showed that over 80% of the pixels of the difference image for the two datasets were within 2 K. In light of the complex topography and distinct atmospheric conditions, these comparison results are encouraging. The 30 m LST from the method proposed in this study also depicts the seasonality of rugged surfaces.<\/jats:p>","DOI":"10.3390\/rs14112617","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T02:30:06Z","timestamp":1653964206000},"page":"2617","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["High Spatiotemporal Rugged Land Surface Temperature Downscaling over Saihanba Forest Park, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Xiaoying","family":"Ouyang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Youjun","family":"Dou","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"given":"Jinxin","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China"}]},{"given":"Xi","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Jianguang","family":"Wen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1016\/j.scitotenv.2017.10.226","article-title":"Determination of annual and seasonal daytime and nighttime trends of MODIS LST over Greece-climate change implications","volume":"616","author":"Eleftheriou","year":"2018","journal-title":"Sci. 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