Land surface temperature (LST) is a crucial physical parameter for hydrological, meteorological, climatological, and climate change studies. To encourage the use of satellite-derived LST products in a wide range of ap...
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Land surface temperature (LST) is a crucial physical parameter for hydrological, meteorological, climatological, and climate change studies. To encourage the use of satellite-derived LST products in a wide range of applications, providing feedback on product performance over regional and global scales is an urgent task. However, considering that the uncertainty of newly released LST products is still unclear, it is urgently necessary to perform a comprehensive validation and error analysis, especially in areas with special geographical and weather conditions, such as the Tibetan plateau (TP). In particular, fewer studies have been concerned with the degraded LST retrieval accuracy over the TP because of the sparse ground measurements. In this study, moderate-resolution imaging spectroradiometer (MODIS) LST products (C6.1) were comprehensively evaluated based on the independent ground observation systems with different atmospheric and LST conditions. The in situ measurements collected from the Tibetan Observation and Research Platform and surface radiation systems are located on the American Plain and the TP, respectively, incorporating various land-cover types, including barren land, grassland, cropland, shrubland, and sparse and dense vegetation, among others. The spatial representativeness evaluation indicated that relatively high-quality in situ LSTs can be obtained during nighttime. Compared with the North American Plain (with a mean RMSE of 1.56 K), MODIS LST retrievals have larger discrepancies (mean RMSE of 2.34 K) over the TP with complex terrain and weather conditions. Emissivity determination is the primary source of the uncertainty in the generalized split-window (GSW) algorithm. Moreover, simulation settings of atmospheric and LST conditions in the GSW algorithm cannot cover a wide range of conditions at a global scale. It is expected to develop new LST retrieval algorithm to meet the quality specifications of users over the TP. Overall, this study ident
Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface temperature (LST) products are essential data sources for global and regional climate change research. Currently, several versions of the MODIS LST pr...
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Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface temperature (LST) products are essential data sources for global and regional climate change research. Currently, several versions of the MODIS LST product have been released, yet the performance differences and uncertainties they introduce in land surface studies remain insufficiently addressed. To bridge this gap, this study focuses on four distinct versions of the LST product: MxD11A1 Collection 5 (C5), Collection 6 (C6), Collection 6.1 (C6.1), and MxD21A1 Collection 6.1 (MxD21). The spatial resolution of all product generations is 1 km, and the temporal resolution is 0.5 days. This study provides a comprehensive analysis of the errors arising from different generations of these products in various land surface process studies. The error assessment includes cross-comparisons between product versions and evaluations of the absolute errors generated. Absolute errors in evaluation data were collected from 13 surface sites within the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project during the period 2013-2018. Cross-validation results show that the largest difference between C5 and C6.1 occurs over bare land, with an RMSE of approximately 1.45 K, while there is no significant change between C6 and C6.1. MOD21 shows considerable variation compared to C6.1 at night across different land cover types, with RMSE over cropland exceeding 2 K. The temperature difference between MOD21 and C6.1 is more pronounced at night (2.01 K) than during the day (0.30 K). validation results based on temperature indicate that C5 has greater uncertainty compared to C6, especially over bare land, where errors are 2.06 K and 1.06 K, respectively. Furthermore, MxD21 demonstrates significant day-night performance discrepancies, with an average bias of 0.10 K at night, while daytime errors over bare land can reach 2 K, potentially influenced by atmospheric conditions. based on the research in this paper, i
作者：
Duan, Si-BoLi, Zhao-LiangLi, HuaGoettsche, Frank-MWu, HuaZhao, WeiLeng, PeiZhang, XiaColl, CesarChinese Acad Agr Sci
Inst Agr Resources & Reg Planning Key Lab Agr Remote Sensing Minist Agr Beijing 100081 Peoples R China Hebei GEO Univ
Sch Land Resources & Urban Rural Planning Shijiazhuang 050031 Hebei Peoples R China Chinese Acad Sci
Inst Remote Sensing & Digital Earth State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China KIT
Hermann von Helmholtz Pl 1 D-76344 Eggenstein Leopoldshafen Germany Chinese Acad Sci
Inst Geog Sci & Nat Resources Res State Key Lab Resources & Environm Informat Syst Beijing 100101 Peoples R China Chinese Acad Sci
Inst Mt Hazards & Environm Chengdu 610041 Sichuan Peoples R China Univ Valencia
Fac Phys Dept Earth Phys & Thermodynam Burjassot 46100 Spain
Land surface temperature (LST) is an important physical quantity at the land-atmosphere interface. Since 2016 the Collection 6 (C6) MODIS LST product is publicly available, which includes three refinements over bare s...
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Land surface temperature (LST) is an important physical quantity at the land-atmosphere interface. Since 2016 the Collection 6 (C6) MODIS LST product is publicly available, which includes three refinements over bare soil surfaces compared to the Collection 5 (C5) MODIS LST product. To encourage the use of the C6 MODIS LST product in a wide range of applications, it is necessary to evaluate the accuracy of the C6 MODIS LST product. In this study, we validated the C6 MODIS LST product using temperature-basedmethod over various land cover types, including grasslands, croplands, cropland/natural vegetation mosaic, open shrublands, woody savannas, and barren/sparsely vegetated. In situ measurements were collected from various sites under different atmospheric and surface conditions, including seven SURFRAD sites (BND, TBL, DRA, FPK, GCM, PSU, and SXF) in the United States, three KIT sites (EVO, KAL, and GBB) in Portugal and Namibia, and three HiWATER sites (GBZ, HZZ, and HMZ) in China. The spatial representativeness of the in situ measurements at each site was separately evaluated during daytime and nighttime using all available clear-sky ASTER LST products at 90 m spatial resolution. Only six sites during daytime are selected as sufficiently homogeneous sites despite the usually high spatial thermal heterogeneity, whereas during nighttime most sites can be considered to be thermally homogeneous and have similar LST and air temperature. The C6 MODIS LST product was validated using in situ measurements from the selected homogeneous sites during daytime and nighttime: except for the GBB site, large RMSE values ( > 2 K) were obtained during daytime. However, if only satellite LST with a high spatial thermal homogeneity on the MODIS pixel scale are used for LST validation, the best daytime accuracy (RMSE < 1.3 K) for the C6 MODIS LST product is achieved over the BND and DRA sites. Except for the DRA site, the RMSE values during nighttime are < 2 K at the selected homogeneou
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