{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T18:37:32Z","timestamp":1766428652638,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T00:00:00Z","timestamp":1672358400000},"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":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"],"award-info":[{"award-number":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Innovation Team of XPCC\u2019s Key Area","award":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"],"award-info":[{"award-number":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"]}]},{"name":"Guangdong Yuehai Water Investment Co., Ltd. Multi Parameter Integrated Water Pollution Online Monitoring Technology and Demonstration Application Unveiling Project","award":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"],"award-info":[{"award-number":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"]}]},{"name":"Forestry Innovation program in Guangdong Province","award":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"],"award-info":[{"award-number":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"]}]},{"name":"Major Projects of High-Resolution Earth Observation","award":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"],"award-info":[{"award-number":["41830108","42272346","52271267","2018CB004","JS-21-TJ-011","2022KJCX001","30-H30C01-9004-19\/21"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Maintaining the balance between power station operation and environmental carrying capacity in the process of cooling water discharge into coastal waters is an essential issue to be considered. Earth observations with airborne and sea surface sensors can efficiently estimate distribution characteristics of extensive sea surface temperature compared with traditional numerical and physical simulations. Data acquisition timing windows for those sensors are designed according to tidal data. The airborne thermal infrared data (Thermal Airborne Spectrographic Imager, TASI) is preprocessed by algorithms of atmospheric correction, geometric correction, strip brightness gradient removal, and noise reduction, and then the seawater temperature is inversed in association with sea surface synchronous temperature measurement data (Sea-Bird Electronics, SBE). Verification analyses suggested a satisfied accuracy of less than about 0.2 \u00b0C error between the predicted and the measured values in general. Multiple factors influence seawater temperature, i.e., meteorology, ocean current, runoff, water depth, seawater convection, and eddy current; tidal activity is not the only one. Environmental background temperature in different seasons is the governing factor affecting the diffusion effect of seawater temperature drainage according to analyses of the covariances and correlation coefficients of eight tidal states. The present study presents an efficient and quick seawater temperature monitoring technique owing to industrial warm drainage to sea by means of a complete set of seawater temperature inversion algorithms with multi-source thermal infrared hyperspectral data.<\/jats:p>","DOI":"10.3390\/rs15010205","type":"journal-article","created":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T02:44:03Z","timestamp":1672627443000},"page":"205","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Response of Industrial Warm Drainage to Tide Revealed by Airborne and Sea Surface Observations"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1690-4886","authenticated-orcid":false,"given":"Donghui","family":"Zhang","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6749-1850","authenticated-orcid":false,"given":"Zhenchang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou 510006, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3533-9966","authenticated-orcid":false,"given":"Lifu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps, Shihezi University, Shihezi 832003, China"}]},{"given":"Xuejian","family":"Sun","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Zhijie","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geography, Development & Environment, University of Arizona, Tucson, AZ 85721, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2607-4628","authenticated-orcid":false,"given":"Wanchang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7916-781X","authenticated-orcid":false,"given":"Xusheng","family":"Li","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Remote Sensing Information and Imagery Analyzing Technology, Beijing Research Institute of Uranium Geology, Beijing 100029, China"}]},{"given":"Qin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"68257","DOI":"10.1007\/s11356-022-20542-1","article-title":"Research on the spatiotemporal evolution and influencing factors of green economic efficiency in the Yangtze River economic belt","volume":"29","author":"Song","year":"2022","journal-title":"Environ. 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