{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:07:04Z","timestamp":1775578024933,"version":"3.50.1"},"reference-count":126,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2020,8,10]],"date-time":"2020-08-10T00:00:00Z","timestamp":1597017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41921001, 4187127"],"award-info":[{"award-number":["41921001, 4187127"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land surface temperature (LST) is an important variable in the physics of land\u2013surface processes controlling the heat and water fluxes over the interface between the Earth\u2019s surface and the atmosphere. Space-borne remote sensing provides the only feasible way for acquiring high-precision LST at temporal and spatial domain over the entire globe. Passive microwave (PMW) satellite observations have the capability to penetrate through clouds and can provide data under both clear and cloud conditions. Nonetheless, compared with thermal infrared data, PMW data suffer from lower spatial resolution and LST retrieval accuracy. Various methods for estimating LST from PMW satellite observations were proposed in the past few decades. This paper provides an extensive overview of these methods. We first present the theoretical basis for retrieving LST from PMW observations and then review the existing LST retrieval methods. These methods are mainly categorized into four types, i.e., empirical methods, semi-empirical methods, physically-based methods, and neural network methods. Advantages, limitations, and assumptions associated with each method are discussed. Prospects for future development to improve the performance of LST retrieval methods from PMW satellite observations are also recommended.<\/jats:p>","DOI":"10.3390\/rs12162573","type":"journal-article","created":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T09:28:57Z","timestamp":1597138137000},"page":"2573","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":86,"title":["Land Surface Temperature Retrieval from Passive Microwave Satellite Observations: State-of-the-Art and Future Directions"],"prefix":"10.3390","volume":"12","author":[{"given":"Si-Bo","family":"Duan","sequence":"first","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]},{"given":"Xiao-Jing","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]},{"given":"Cheng","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]},{"given":"Zhao-Liang","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"},{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5982-8422","authenticated-orcid":false,"given":"Hua","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Yonggang","family":"Qian","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9674-6020","authenticated-orcid":false,"given":"Maofang","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]},{"given":"Pei","family":"Leng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4038","DOI":"10.1029\/2002JD002176","article-title":"Determination of land surface temperature and soil moisture from Tropical Rainfall Measuring Mission\/Microwave Imager remote sensing data","volume":"108","author":"Wen","year":"2003","journal-title":"J. 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