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- W2984774552 abstract "Land surface temperature (LST) is an important parameter for series land surface processes, models and applications. The accuracy of LST directly influenced its application. Therefore, a reasonable validation method is meaningful to assess the accuracy of LST datasets. In this study, an in-situ observation representativeness assessment method was proposed. Based on this method, the JPSS VIIRS LST product was validated against in-situ LST at 7 ground sites over the Heihe River Basin during the HiWATER experiments period. Results show that about 70%, 28%, 43%, 68%, 42%, 35% and 25% of the FOV LST for ARS, DMS, DSL, EBO, HHL, JYL, and SDQ are able to well represent the corresponding LST of VIIRS pixels, respectively and determined the representativeness period of each site. The VIIRS LST has a high correlation with the in-situ LST with an accuracy of 2.30 K - 5.76 K at daytime and 1.26 K-2.68 K at nighttime, respectively." @default.
- W2984774552 created "2019-11-22" @default.
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- W2984774552 date "2019-07-01" @default.
- W2984774552 modified "2023-09-26" @default.
- W2984774552 title "VIIRS LST Product Validation Based on Spatial Representativeness Evaluation of the Ground Measurements" @default.
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- W2984774552 doi "https://doi.org/10.1109/igarss.2019.8900611" @default.
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