Downscaling ESA CCI Soil Moisture Based on Soil and Vegetation Component Temperatures Derived From MODIS Data
Author:
Affiliation:
1. School of Geomatics, Anhui University of Science & Technology, Huainan, China
2. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
Funder
Natural Science Foundation
Anhui Higher Education Institutions of China
National Key R&D Program of China
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/9656571/09723620.pdf?arnumber=9723620
Reference49 articles.
1. A method to downscale soil moisture to fine resolutions using topographic, vegetation, and soil data
2. Controls on topographic dependence and temporal instability in catchment-scale soil moisture patterns
3. A Change Detection Algorithm for Retrieving High-Resolution Soil Moisture From SMAP Radar and Radiometer Observations
4. High-resolution change estimation of soil moisture using L-band radiometer and Radar observations made during the SMEX02 experiments
5. Characterizing subpixel variability of low resolution radiometer derived soil moisture using high resolution radar data
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1. Generating surface soil moisture at the 30 m resolution in grape-growing areas based on stacked ensemble learning;International Journal of Remote Sensing;2024-07-22
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