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Evaluation of ESA Active, Passive and Combined Soil Moisture Products Using Upscaled Ground Measurements
Open AccessArticle

Toward High-Resolution Soil Moisture Monitoring by Combining Active-Passive Microwave and Optical Vegetation Remote Sensing Products with Land Surface Model

1
Institute of Industrial Science, The University of Tokyo, Kashiwa, Chiba 277-8574, Japan
2
Institute of Engineering Innovation, The University of Tokyo, Bunkyo-ku, Tokyo 113-8654, Japan
3
International Centre for Water Hazard and Risk Management (ICHARM), Tsukuba, Ibaraki 300-2621, Japan
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(18), 3924; https://doi.org/10.3390/s19183924
Received: 12 July 2019 / Revised: 4 September 2019 / Accepted: 9 September 2019 / Published: 11 September 2019
(This article belongs to the Special Issue Satellite Remotely Sensed Soil Moisture)
The assimilation of radiometer and synthetic aperture radar (SAR) data is a promising recent technique to downscale soil moisture products, yet it requires land surface parameters and meteorological forcing data at a high spatial resolution. In this study, we propose a new downscaling approach, named integrated passive and active downscaling (I-PAD), to achieve high spatial and temporal resolution soil moisture datasets over regions without detailed soil data. The Advanced Microwave Scanning Radiometer (AMSR-E) and Phased Array-type L-band SAR (PALSAR) data are combined through a dual-pass land data assimilation system to obtain soil moisture at 1 km resolution. In the first step, fine resolution model parameters are optimized based on fine resolution PALSAR soil moisture and moderate-resolution imaging spectroradiometer (MODIS) leaf area index data, and coarse resolution AMSR-E brightness temperature data. Then, the 25 km AMSR-E observations are assimilated into a land surface model at 1 km resolution with a simple but computationally low-cost algorithm that considers the spatial resolution difference. Precipitation data are used as the only inputs from ground measurements. The evaluations at the two lightly vegetated sites in Mongolia and the Little Washita basin show that the time series of soil moisture are improved at most of the observation by the assimilation scheme. The analyses reveal that I-PAD can capture overall spatial trends of soil moisture within the coarse resolution radiometer footprints, demonstrating the potential of the algorithm to be applied over data-sparse regions. The capability and limitation are discussed based on the simple optimization and assimilation schemes used in the algorithm. View Full-Text
Keywords: active-passive; data assimilation; microwave remote sensing; soil moisture; downscaling; disaggregation; PALSAR; AMSR-E; MODIS active-passive; data assimilation; microwave remote sensing; soil moisture; downscaling; disaggregation; PALSAR; AMSR-E; MODIS
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MDPI and ACS Style

Toride, K.; Sawada, Y.; Aida, K.; Koike, T. Toward High-Resolution Soil Moisture Monitoring by Combining Active-Passive Microwave and Optical Vegetation Remote Sensing Products with Land Surface Model. Sensors 2019, 19, 3924.

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