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To date, many methods have been proposed to estimate LST from satellite thermal infrared data. The single-channel (SC) algorithm can provide an accurate result in retrieving LST based on prior knowledge of known land surface emissivity (LSE). The SC algorithm is extensively employed for retrieving LST from Landsat series data due to its simplicity and its reliance on just one thermal infrared channel. The Thermal Infrared Sensor (IRS) on the Chinese ZY1-02E satellite is a pivotal instrument employed for gathering thermal infrared (TIR) data of land surfaces. The objective of this research is to evaluate the feasibility of a single-channel approach based on water vapor scaling (WVS) for deriving LST from ZY1-02E IRS data because of its wide spectrum range, i.e., 7~12 \u03bcm, which is affected strongly by both atmospheric water vapor and ozone. Three study areas, namely the Baotou, Heihe River Basin, and Yantai Sea sites, were selected as validation sites to evaluate the LST inversion accuracy. This evaluation was also conducted via cross-comparison between the retrieved LST and MODIS LST products. The results revealed that the WVS-based method exhibited an average bias of 0.63 K and an RMSE of 1.62 K compared to the in situ LSTs. The WVS-based method demonstrated reasonable accuracy through cross-validation with the MODIS LST product, with an average bias of 0.77 K and an RMSE of 2.0 K. These findings indicate that the WVS-based method is effective in estimating LST from ZY1-02E IRS data.<\/jats:p>","DOI":"10.3390\/rs16020383","type":"journal-article","created":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T03:50:56Z","timestamp":1705549856000},"page":"383","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Estimation of Land Surface Temperature from Chinese ZY1-02E IRS Data"],"prefix":"10.3390","volume":"16","author":[{"given":"Xianhui","family":"Dou","sequence":"first","affiliation":[{"name":"Key Laboratory of Physical Electronics and Devices, Ministry of Education, Faculty of Electronic and Information Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"},{"name":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2232-1521","authenticated-orcid":false,"given":"Kun","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Sciences, 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"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4530-2286","authenticated-orcid":false,"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Sciences, 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":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Chenyang","family":"Ma","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Sciences, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Hongzhao","family":"Tang","sequence":"additional","affiliation":[{"name":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100094, China"}]},{"given":"Xining","family":"Liu","sequence":"additional","affiliation":[{"name":"China Sanya Institute of South China Sea Geology, Guangzhou Marine Geological Survey, Sanya 572025, China"}]},{"given":"Yonggang","family":"Qian","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Sciences, 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"}]},{"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Physical Electronics and Devices, Ministry of Education, Faculty of Electronic and Information Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}]},{"given":"Jinglun","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Sciences, 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":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Yichao","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Sciences, 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":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Sciences, 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":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"The Fourth Topographic Survey Team, ACCUR Ministry of Natural Resources, Harbin 150028, China"}]},{"given":"Juntao","family":"Yang","sequence":"additional","affiliation":[{"name":"The Fourth Topographic Survey Team, ACCUR Ministry of Natural Resources, Harbin 150028, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2850","DOI":"10.3390\/rs70302850","article-title":"A New Global Climatology of Annual Land Surface Temperature","volume":"7","author":"Bechtel","year":"2015","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1038\/nclimate3250","article-title":"Local temperature response to land cover and management change driven by non-radiative processes","volume":"7","author":"Bright","year":"2017","journal-title":"Nat. Clim. Change"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.uclim.2017.05.010","article-title":"Investigating the relationship between local climate zone and land surface temperature using an improved WUDAPT methodology\u2014A case study of Yangtze River Delta, China","volume":"24","author":"Cai","year":"2018","journal-title":"Urban Clim."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1038\/s41558-018-0258-y","article-title":"Greening of the land surface in the world\u2019s cold regions consistent with recent warming","volume":"8","author":"Keenan","year":"2018","journal-title":"Nat. Clim. Change"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2136","DOI":"10.1109\/JSTARS.2020.3046755","article-title":"Generating Comparable and Fine-Scale Time Series of Summer Land Surface Temperature for Thermal Environment Monitoring","volume":"14","author":"Shen","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1038\/386698a0","article-title":"Increased plant growth in the northern high latitudes from 1981 to 1991","volume":"386","author":"Myneni","year":"1997","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2915","DOI":"10.1073\/pnas.1315126111","article-title":"Afforestation in China cools local land surface temperature","volume":"111","author":"Peng","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"124577","DOI":"10.1016\/j.jhydrol.2020.124577","article-title":"Estimation of surface heat fluxes via variational assimilation of land surface temperature, air temperature and specific humidity into a coupled land surface-atmospheric boundary layer model","volume":"583","author":"Tajfar","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"124105","DOI":"10.1016\/j.jhydrol.2019.124105","article-title":"Evaluation of twelve evapotranspiration products from machine learning, remote sensing and land surface models over conterminous United States","volume":"578","author":"Xu","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_10","first-page":"1","article-title":"A Four-Component Parameterized Directional Thermal Radiance Model for Row Canopies","volume":"60","author":"Li","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2012.12.008","article-title":"Satellite-derived land surface temperature: Current status and perspectives","volume":"131","author":"Li","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.1175\/BAMS-D-11-00254.1","article-title":"The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables","volume":"94","author":"Hollmann","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e2022RG000777","DOI":"10.1029\/2022RG000777","article-title":"Satellite Remote Sensing of Global Land Surface Temperature: Definition, Methods, Products, and Applications","volume":"61","author":"Li","year":"2023","journal-title":"Rev. Geophys."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3719","DOI":"10.1080\/01431160010006971","article-title":"A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region","volume":"22","author":"Qin","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Jim\u00e9nez-Mu\u00f1oz, J.C., and Sobrino, J.A. (2003). A generalized single-channel method for retrieving land surface temperature from remote sensing data. J. Geophys. Res. Atmos., 108.","DOI":"10.1029\/2003JD003480"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1109\/TGRS.2008.2007125","article-title":"Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data","volume":"47","author":"Cristobal","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5113","DOI":"10.1029\/JC080i036p05113","article-title":"Estimation of Sea Surface Temperatures from Two Infrared Window Measurements with Different Absorption","volume":"80","author":"McMillin","year":"1975","journal-title":"J. Geophys. Research. Part C Ocean."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1109\/LGRS.2008.2006410","article-title":"A Split-Window Algorithm for Estimating LST From Meteosat 9 Data: Test and Comparison with In Situ Data and MODIS LSTs","volume":"6","author":"Atitar","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1080\/01431168708954793","article-title":"The impact of spectral emissivity on the measurement of land surface temperature from a satellite","volume":"8","author":"Becker","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3365","DOI":"10.1029\/JD094iD03p03365","article-title":"Theoretical algorithms for satellite-derived sea surface temperatures","volume":"94","author":"Barton","year":"1989","journal-title":"J. Geophys. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1080\/014311697218548","article-title":"Land surface emissivity and temperature determination in the whole HAPEX-Sahel area from AVHRR data","volume":"18","author":"Caselles","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1109\/36.700995","article-title":"A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images","volume":"36","author":"Gillespie","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3681","DOI":"10.1016\/j.rse.2011.09.007","article-title":"Residual errors in ASTER temperature and emissivity standard products AST08 and AST05","volume":"115","author":"Gillespie","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/j.rse.2006.04.012","article-title":"Improved land surface emissivities over agricultural areas using ASTER NDVI","volume":"103","author":"Sobrino","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.rse.2016.04.023","article-title":"A water vapor scaling model for improved land surface temperature and emissivity separation of MODIS thermal infrared data","volume":"182","author":"Malakar","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_26","first-page":"1","article-title":"Temperature and Emissivity Retrieval From Hyperspectral Thermal Infrared Data Using Dictionary-Based Sparse Representation for Emissivity","volume":"61","author":"Ma","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1080\/01431169008955028","article-title":"Towards a local split window method over land surfaces","volume":"11","author":"Becker","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/0034-4257(92)90096-3","article-title":"A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies","volume":"42","author":"Hook","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.rse.2005.06.003","article-title":"Extending surface temperature and emissivity retrieval to the mid-infrared (3\u20135 \u03bcm) using the Multispectral Thermal Imager (MTI)","volume":"98","author":"Mushkin","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1029\/2018JD029330","article-title":"A Practical Single-Channel Algorithm for Land Surface Temperature Retrieval: Application to Landsat Series Data","volume":"124","author":"Wang","year":"2019","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ma, L., Zhao, Y., Woolliams, E.R., Dai, C., Wang, N., Liu, Y., Li, L., Wang, X., Gao, C., and Li, C. (2020). Uncertainty Analysis for RadCalNet Instrumented Test Sites Using the Baotou Sites BTCN and BSCN as Examples. Remote Sens., 12.","DOI":"10.3390\/rs12111696"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"044004","DOI":"10.1117\/1.JRS.11.044004","article-title":"Vicarious radiometric calibration\/validation of Landsat-8 operational land imager using a ground reflected radiance-based approach with Baotou site in China","volume":"11","author":"Liu","year":"2017","journal-title":"J. Appl. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2018.04.0072","article-title":"The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China","volume":"17","author":"Liu","year":"2018","journal-title":"Vadose Zone J. VZJ"},{"key":"ref_34","unstructured":"Wan, Z., Hook, S., and Hulley, G. (2020, July 08). MODIS\/Terra Land Surface Temperature\/Emissivity 5-Min L2 Swath 1 km V061, Available online: https:\/\/lpdaac.usgs.gov\/products\/mod11_l2v061\/."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1016\/j.rse.2007.05.024","article-title":"Validating MODIS land surface temperature products using long-term nighttime ground measurements","volume":"112","author":"Wang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1016\/j.rse.2008.11.007","article-title":"The ASTER spectral library version 2.0","volume":"113","author":"Baldridge","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Yang, J., Duan, S.-B., Zhang, X., Wu, P., Huang, C., Leng, P., and Gao, M. (2020). Evaluation of Seven Atmospheric Profiles from Reanalysis and Satellite-Derived Products: Implication for Single-Channel Land Surface Temperature Retrieval. Remote Sens., 12.","DOI":"10.3390\/rs12050791"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1804","DOI":"10.1109\/TGRS.2016.2633810","article-title":"Vicarious Calibration of the Landsat 7 Thermal Infrared Band and LST Algorithm Validation of the ETM+ Instrument Using Three Global Atmospheric Profiles","volume":"55","author":"Sobrino","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1109\/36.911125","article-title":"An atmospheric correction algorithm for thermal infrared multispectral data over land-a water-vapor scaling method","volume":"39","author":"Tonooka","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2778","DOI":"10.1109\/TGRS.2005.857886","article-title":"Accurate atmospheric correction of ASTER thermal infrared imagery using the WVS method","volume":"43","author":"Tonooka","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4864","DOI":"10.1080\/01431161.2015.1040132","article-title":"An improved NDVI-based threshold method for estimating land surface emissivity using MODIS satellite data","volume":"36","author":"Tang","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.rse.2004.02.003","article-title":"Land surface temperature retrieval from LANDSAT TM 5","volume":"90","author":"Sobrino","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_43","first-page":"205","article-title":"Dynamic Modelling of VFC from 2000 to 2010 Using NDVI and DMSP\/OLS Time Series: A Study in Guangdong Province, China","volume":"8","author":"Shobairi","year":"2016","journal-title":"J. Geogr. Inf. Syst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1283","DOI":"10.1109\/JSTARS.2022.3143552","article-title":"An Operational Land Surface Temperature Retrieval Methodology for Chinese Second-Generation Huanjing Disaster Monitoring Satellite Data","volume":"15","author":"Zhao","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/S0034-4257(00)00171-1","article-title":"A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data","volume":"75","author":"Sobrino","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ecoenv.2015.07.004","article-title":"Statistical analysis of land surface temperature\u2013vegetation indexes relationship through thermal remote sensing","volume":"121","author":"Kumar","year":"2015","journal-title":"Ecotoxicol. Environ. Saf."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1080\/10286600600888565","article-title":"Comparison of different ANN techniques in river flow prediction","volume":"24","author":"Kisi","year":"2007","journal-title":"Civ. Eng. Environ. Syst."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3140","DOI":"10.1080\/01431161.2012.716538","article-title":"Evaluation of land surface temperature and emissivities retrieved from MSG\/SEVIRI data with MODIS land surface temperature and emissivity products","volume":"34","author":"Qian","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2156","DOI":"10.3390\/rs4072156","article-title":"Analysis of the Scaling Effects in the Area-Averaged Fraction of Vegetation Cover Retrieved Using an NDVI-Isoline-Based Linear Mixture Model","volume":"4","author":"Obata","year":"2012","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/2\/383\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:49:16Z","timestamp":1760104156000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/2\/383"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,18]]},"references-count":49,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["rs16020383"],"URL":"https:\/\/doi.org\/10.3390\/rs16020383","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,18]]}}}