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

REMOTE SENSING OF ENVIRONMENT

卷:113

Article

Merlin, Olivier¹  Al Bitar, Ahmad¹  Walker, Jeffrey P.²  Kerr, Yann¹ 

[1] Ctr Etud Spatiales Biosphere CESBIO, Toulouse, France

[2] Univ Melbourne, Melbourne, Vic 3010, Australia

关键词: Disaggregation;    Soil moisture;    Fractal;    Scaling;    Multi-sensor;    NAFE;    SMOS;    MODIS;    ASTER;   

DOI  :  10.1016/j.rse.2009.06.012

来源: Elsevier

【 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.

【 授权许可】

Free