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Evaluation of A Physically-Based Passive Microwave Land Surface Temperature Retrieval Algorithm Using MODIS Data

Authors :
Xiaoguang Jiang
Si-Bo Duan
Cheng Huang
Pei Leng
Hua Wu
Yazhen Jiang
Zhao-Liang Li
Maofang Gao
Xiao-Ping Zhang
Xiao-Jing Han
Caixia Gao
Source :
IGARSS
Publication Year :
2019
Publisher :
IEEE, 2019.

Abstract

Passive microwave data are much less affected by clouds than TIR data for the retrieval of land surface temperature (LST), providing its unique advantages in global mapping of LST. In this study, a physically-based algorithm for LST retrieval was applied to AMSR2 global brightness temperature data. The performances of this algorithm applied on different land cover types were further evaluated against nighttime MYD11A1 thermal infrared LST products. The results showed that (i) the overall accuracy of the algorithm is about 5.42 K by root mean square error (RMSE) and 2.99 K by bias against MODIS LST during nighttime; (ii) the algorithm overestimates the LST over all land types. The overestimation is most evident over barren/sparsely vegetated surfaces. The algorithm shows that the algorithm has a robust performance comparing with MODIS LST and could be applied to estimate LST effectively.

Details

Database :
OpenAIRE
Journal :
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Accession number :
edsair.doi...........4caf17b7c37539d277c707b16b8a8aad
Full Text :
https://doi.org/10.1109/igarss.2019.8900145