A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors

被引:52
作者
Merlin, Olivier [1 ]
Al Bitar, Ahmad [1 ]
Walker, Jeffrey P. [2 ]
Kerr, Yann [1 ]
机构
[1] Ctr Etud Spatiales Biosphere CESBIO, Toulouse, France
[2] Univ Melbourne, Melbourne, Vic 3010, Australia
基金
澳大利亚研究理事会;
关键词
Disaggregation; Soil moisture; Fractal; Scaling; Multi-sensor; NAFE; SMOS; MODIS; ASTER; ANCILLARY DATA; EVAPORATION; EFFICIENCY; IMAGERY; SPACE;
D O I
10.1016/j.rse.2009.06.012
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:2275 / 2284
页数:10
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