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XU Huihui, GAO Meiling, LI Zhenhong, HU Yufeng. The Accuracy Comparison of Near Surface Air Temperature Estimation Using Different Land Surface Temperature Sources[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210541
Citation: XU Huihui, GAO Meiling, LI Zhenhong, HU Yufeng. The Accuracy Comparison of Near Surface Air Temperature Estimation Using Different Land Surface Temperature Sources[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210541

The Accuracy Comparison of Near Surface Air Temperature Estimation Using Different Land Surface Temperature Sources

doi: 10.13203/j.whugis20210541
Funds:

The National Natural Science Foundation of China (42001382, 42041006, 41941019)

  • Received Date: 2021-09-30
    Available Online: 2022-03-31
  • Objectives: Near surface air temperature (NSAT) is a key parameter in the land-atmosphere interaction process. Sparse NSAT observations from in-situ stations usually cannot fully describe the spatial distribution of NSAT, so estimating NSAT by land surface temperature (LST) and auxiliary variables has become an effective approach to obtain the spatial distribution of NSAT. Although there are some multisource LST products published, i.e., the LST from MODIS, Landsat, and Global Land Data Assimilation System (GLDAS), the applicability of each LST product in NSAT estimation still needs further investigation. Methods: Taken Yellow River Basin as the study region, summer NSAT from 2003 to 2019 was estimated based on the GEE (Google Earth Engine) platform with RF (Random Forest) algorithm in this study, and the mean, maximum and minimum NSAT was estimated in two scales (i.e., 30-m and 1000-m) using three LST data sources (Landsat, MODIS and GLDAS). The observed LST from in-situ stations over Yellow River Basin Region were compared with the estimated NSAT by the ten-cross validation method to evaluate the accuracy of different LST sources when estimating NSAT. Results: The results indicate that:1) In terms of mean NSAT, the differences of accuracy of the three LST sources are small. 2) In terms of the maximum and minimum NSAT, the GLDAS LST shows the significant higher accuracy than MODIS and Landsat LST. 3) The RMSEs of estimated mean NSAT are smaller than maximum and minimum NSAT estimation when using the same LST source. 4) For the spatial distribution of accuracy, the stations with higher error mainly located in the southern or western of the study region. Conclusions: The temporal resolution of LST source is significantly important in NSAT estimation. The GLDAS LST shows the highest accuracy in this study especially for extreme NSAT estimation. Besides, the mean NSAT estimation has higher accuracy than that of maximum or minimum NSAT for each LST source.
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The Accuracy Comparison of Near Surface Air Temperature Estimation Using Different Land Surface Temperature Sources

doi: 10.13203/j.whugis20210541
Funds:

The National Natural Science Foundation of China (42001382, 42041006, 41941019)

Abstract: Objectives: Near surface air temperature (NSAT) is a key parameter in the land-atmosphere interaction process. Sparse NSAT observations from in-situ stations usually cannot fully describe the spatial distribution of NSAT, so estimating NSAT by land surface temperature (LST) and auxiliary variables has become an effective approach to obtain the spatial distribution of NSAT. Although there are some multisource LST products published, i.e., the LST from MODIS, Landsat, and Global Land Data Assimilation System (GLDAS), the applicability of each LST product in NSAT estimation still needs further investigation. Methods: Taken Yellow River Basin as the study region, summer NSAT from 2003 to 2019 was estimated based on the GEE (Google Earth Engine) platform with RF (Random Forest) algorithm in this study, and the mean, maximum and minimum NSAT was estimated in two scales (i.e., 30-m and 1000-m) using three LST data sources (Landsat, MODIS and GLDAS). The observed LST from in-situ stations over Yellow River Basin Region were compared with the estimated NSAT by the ten-cross validation method to evaluate the accuracy of different LST sources when estimating NSAT. Results: The results indicate that:1) In terms of mean NSAT, the differences of accuracy of the three LST sources are small. 2) In terms of the maximum and minimum NSAT, the GLDAS LST shows the significant higher accuracy than MODIS and Landsat LST. 3) The RMSEs of estimated mean NSAT are smaller than maximum and minimum NSAT estimation when using the same LST source. 4) For the spatial distribution of accuracy, the stations with higher error mainly located in the southern or western of the study region. Conclusions: The temporal resolution of LST source is significantly important in NSAT estimation. The GLDAS LST shows the highest accuracy in this study especially for extreme NSAT estimation. Besides, the mean NSAT estimation has higher accuracy than that of maximum or minimum NSAT for each LST source.

XU Huihui, GAO Meiling, LI Zhenhong, HU Yufeng. The Accuracy Comparison of Near Surface Air Temperature Estimation Using Different Land Surface Temperature Sources[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210541
Citation: XU Huihui, GAO Meiling, LI Zhenhong, HU Yufeng. The Accuracy Comparison of Near Surface Air Temperature Estimation Using Different Land Surface Temperature Sources[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210541
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