4.7 Article

Temperature-Based and Radiance-Based Validation of the Collection 6 MYD11 and MYD21 Land Surface Temperature Products Over Barren Surfaces in Northwestern China

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2020.2998945

关键词

Land surface temperature; MODIS; Atmospheric modeling; Land surface; Remote sensing; Soil; Land surface emissivity (LSE); land surface temperature (LST); Moderate Resolution Imaging Spectroradiometer (MODIS); split-window (SW) algorithm; validation

资金

  1. National Key Research and Development Program of China [2018YFA0605503]
  2. Chinese Natural Science Foundation [41930111, 41871258, 41901287]
  3. Youth Innovation Promotion Association CAS [2020127]
  4. Future Star Talent Plan of the Aerospace Information Research Institute of Chinese Academy of Sciences [Y920570Z1F]

向作者/读者索取更多资源

In this study, two MODIS land surface temperature products were evaluated using temperature-based and radiance-based methods over barren surfaces and sand dunes in Northwestern China. The results showed that the C6 MYD21 LST product has better accuracy and consistency than the C6 MYD11 product, especially in sand dune areas.
In this study, two collection 6 (C6) Moderate Resolution Imaging Spectroradiometer (MODIS) level-2 land surface temperature (LST) products (MYD11L2 and MYD21L2) from the Aqua satellite were evaluated using temperature-based (T-based) and radiance-based (R-based) validation methods over barren surfaces in Northwestern China. The ground measurements collected at four barren surface sites from June 2012 to September 2018 during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment were used to perform the T-based evaluation. Ten sand dune sites were selected in six large deserts in Northwestern China to carry out an R-based validation from 2012 to 2018. The T-based validation results indicate that the C6 MYD21 LST product has a better accuracy than the C6 MYD11 product during both daytime and nighttime. The LST is underestimated by the C6 MYD11 products at the four T-based sites during the daytime, with a mean bias of 2.82 K and a mean RMSE of 3.82 K, whereas the MYD21 LST product has a mean bias and RMSE of 0.51 and 2.53 K, respectively. The LST is also underestimated at night by the C6 MYD11 products at the four T-based sites, with a mean bias of 1.40 K and a mean RMSE of 1.72 K, whereas the MYD21 LST product has a mean bias and RMSE of 0.23 and 1.01 K, respectively. For the R-based validation, the MYD11 results are associated with large negative biases during both daytime and nighttime at three sand dune sites and biases within 1 K at the other seven sites, whereas the MYD21 results are more consistent at all ten sand dune sites, with a mean bias of 0.45 and 0.70 K for daytime and nighttime, respectively. The emissivities for these two products in MODIS bands 31 and 32 were compared with each other and then compared with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) emissivity and laboratory emissivity. The results indicate that the emissivities in MODIS bands 31 and 32 of MYD11 at the four T-based and three of the R-based validation sites are overestimated and result in LST underestimation, whereas the emissivities of MYD21 are more consistent with the laboratory emissivity. Besides, an experiment was carried out to demonstrate that the physically retrieved dynamic emissivity of the MYD21 product can be utilized to improve the accuracy of the split-window (SW) algorithm for barren surfaces, making it a valuable data source for retrieving LST from different remote sensing data.

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