PROJECT TITLE :

Detection of Inland Open Water Surfaces Using Dual Polarization L-Band Radar for the Soil Moisture Active Passive Mission

ABSTRACT:

A twin-copolarization algorithm to classify inland open water bodies free of flooded vegetation using an L-band radar is presented and evaluated, with a view to applying the tactic to the Soil Moisture Active Passive (SMAP) mission for hydrological science and soil moisture retrieval applications. Past radar-based water body detection algorithms have applied a threshold to one-polarization measurement, with water body detection declared if the observed cross section is less than the desired threshold. But, such strategies are subject to ambiguities associated with scene variability and terrain slopes, making a universal threshold price difficult to derive and complicating the world application of such strategies. As a result of SMAP will provide measurements in each HH and VV polarizations, the copolarization ratio is additionally out there for water body detection. A threshold of −3 dB applied to the HH/VV polarization ratio is found effective in detecting water bodies at 40° incidence angle based on analysis of theoretical model predictions and measurements from airborne artificial aperture radar and therefore the spaceborne Aquarius scatterometer. When the water surface is calm and its radar response is very little (i.e., at the radar thermal noise level), the HH/VV ratio technique fails. But, a mix of an HH/VV threshold (at −three dB) and an HH threshold (at −twenty five dB) is shown to allow water body classification even in this example. This proposed “combined” algorithm is assessed in four totally different geophysical situations. The ensuing water body detection error is shown to be less than 10% for these cases, which satisfies SMAP necessities to permit accurate soil moisture retrieval, and also the corresponding false alarm rate is smaller than 2%. The robustness of the proposed approach to subpixel heterogeneity has been conjointly investigated. The performance of the algorithm remains sensitive to the noise level of the radar observatio- s: for SMAP, a radar noise-equivalent sigma0 of −28.5 dB or less is required so as to facilitate acceptable performance.


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