期刊
REMOTE SENSING OF ENVIRONMENT
卷 113, 期 10, 页码 2275-2284出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2009.06.012
关键词
Disaggregation; Soil moisture; Fractal; Scaling; Multi-sensor; NAFE; SMOS; MODIS; ASTER
资金
- Australian Research Council [LE0453434, LE0560930, DP0557543, DP0343778]
- CRC for Catchment Hydrology
- French program Terre-Ocean-Surface-Atmosphere
- Centre National de la Recherche Scientifique
- Australian Research Council [LE0560930] Funding Source: Australian Research Council
A sequential model is developed to disaggregate microwave-derived soil moisture from 40 km to 4 km resolution using MODIS (Moderate Imaging Spectroradiometer) data and subsequently from 4 km to 500 m resolution using ASTER (Advanced Scanning Thermal Emission and Reflection Radiometer) data. The 1 km resolution airborne data collected during the three-week National Airborne Field Experiment 2006 (NAFE'06) are used to simulate the 40 km pixels, and a thermal-based disaggregation algorithm is applied using 1 km resolution MODIS and 100 m resolution ASTER data. The downscaled soil moisture data are subsequently evaluated using a combination of airborne and in situ soil moisture measurements. A key step in the procedure is to identify an optimal downscaling resolution in terms of disaggregation accuracy and sub-pixel soil moisture variability. Very consistent optimal downscaling resolutions are obtained for MODIS aboard Terra, MODIS aboard Aqua and ASTER, which are 4 to 5 times the thermal sensor resolution. The root mean square error between the 500 m resolution sequentially disaggregated and ground-measured soil moisture is 0.062 vol./vol. with a bias of -0.045 vol./vol. and values ranging from 0.08 to 0.40 vol./vol. (C) 2009 Elsevier Inc. All rights reserved.
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