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  • Aug. 8, 2025

Arid Land Geography ›› 2025, Vol. 48 ›› Issue (5): 765-777.doi: 10.12118/j.issn.1000-6060.2024.087

• Climatology and Environment • Previous Articles     Next Articles

Error analysis of multi-source land surface temperature products in the Heihe River Basin based on in-situ data

LI Xu1(), JIANG Hongnan2(), XU Jianhui3   

  1. 1. College of Ecology and Environment, Xinjiang University, Urumqi 830017, Xinjiang, China
    2. College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, Xinjiang, China
    3. Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, Guangdong, China
  • Received:2024-02-08 Revised:2025-02-14 Online:2025-05-25 Published:2025-05-13
  • Contact: JIANG Hongnan E-mail:lx625625@stu.xju.edu.cn;jiang_hn0609@sina.com

Abstract:

This study used in-situ land surface temperature observation data (from 2017 to 2019) from seven stations in the Heihe River Basin, northern Gansu Province, China, to evaluate the errors of four land surface temperature products: the Fengyun-3C visible and infrared radiometer (FY-3C VIRR) land surface temperature product, the Terra moderate resolution imaging spectroradiometer (MOD11A1/MOD11C3) land surface temperature product, the European Center for medium-range weather forecasts fifth-generation land surface reanalysis dataset (ERA5-LAND), and the China Meteorological Administration land data assimilation system (CLDAS-V2.0). Bias (BIAS), root mean square error (RMSE), correlation coefficient (CC), and ratio of standard deviation (RSD), were employed as statistical metrics for analyzing errors across different temporal scales. The results indicated the following. (1) All four land surface temperature products exhibited a general spatial pattern of higher temperature in the south and lower temperature in the north. However, the FY-3C VIRR and MOD11A1 products exhibited finer spatial details. (2) The FY-3C VIRR daytime land surface temperature product demonstrated relatively lower BIAS and RMSE values, indicating higher accuracy. Further, the MOD11A1 daytime land surface temperature product yielded the highest CC values, ranging across 0.957-0.987. However, it also produced larger errors. This was attributed to the tendency of the MOD11A1 daytime product to overestimate temperatures. (3) The MOD11A1 nighttime land surface temperature product outperformed the FY-3C VIRR, ERA5-LAND, and CLDAS-V2.0 nighttime products in terms of accuracy. Among these, the CLDAS-V2.0 nighttime product exhibited the largest errors. (4) For the FY-3C VIRR, MOD11A1, and ERA5-LAND products, the nighttime land surface temperature accuracy surpassed those of their respective daytime products. Conversely, the CLDAS-V2.0 daytime land surface temperature product exhibited higher accuracy than its nighttime counterparts.

Key words: land surface temperature, FY-3C VIRR, MODIS, ERA5-LAND, CLDAS-V2.0, Heihe River Basin