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Proceedings Paper

Spatial downscaling of FY3B soil moisture based on MODIS land surface temperature and NDVI
Author(s): Jiahui Sheng; Peng Rao; Hanlu Zhu
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Paper Abstract

Soil moisture (SM) is a key variable in controlling the water, carbon, and energy exchange processes of land atmosphere interface. One of the widely used approaches to retrieve soil moisture is based on satellite remote sensing technology. However, these spatiotemporally continuous soil moisture products retrieved from microwave remote sensing data are not able to meet the accuracy requirement of flood prediction and irrigation management due to the coarse spatial resolution. As one of the relatively new passive microwave products, The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product was retrieved from passive microwave brightness temperature data based on the Qp model. However, it has rarely been applied at the catchment and regional scale due to the coarse resolution with 25- km grid. In this study, the Fengyun-3B soil moisture product was downscaled from 25-km to 1-km based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. The downscaling approach uses MODIS land surface temperature (LST) and normalized difference vegetation index (NDVI) to construct soil evaporative efficiency (SEE). The 1-km SM was then estimated based on the difference value of high resolution and average SEE in original FY3B pixel. The downscaling method was applied to every Fengyun-3B pixel in the Naqu area on the Tibetan Plateau to retrieve the downscaled 1-km resolution FY3B soil moisture product. The downscaling results were validated using the in-situ soil moisture from Soil Moisture/ Temperature Monitoring Network on the central Tibetan Plateau (TP-STMNS) in August 2015. The validation results revealed that the downscaling approach showed promising results. We can conclude that the downscaled FY3B SM product better characterize the spatial and temporal continuity and have higher consistency with validation soil moisture data. The approach proposed in this study are applicable to bare surface or sparse vegetation covered land surface.

Paper Details

Date Published: 9 October 2019
PDF: 7 pages
Proc. SPIE 11156, Earth Resources and Environmental Remote Sensing/GIS Applications X, 1115609 (9 October 2019);
Show Author Affiliations
Jiahui Sheng, Key Lab. of Infrared System Detection and Imaging Technology (China)
Shanghai Institute of Technical Physics, CAS (China)
Univ. of Chinese Academy of Sciences (China)
Peng Rao, Key Lab. of Infrared System Detection and Imaging Technology (China)
Shanghai Institute of Technical Physics, CAS (China)
Hanlu Zhu, Key Lab. of Infrared System Detection and Imaging Technology (China)
Shanghai Institute of Technical Physics, CAS (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 11156:
Earth Resources and Environmental Remote Sensing/GIS Applications X
Karsten Schulz; Ulrich Michel; Konstantinos G. Nikolakopoulos, Editor(s)

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