Jiancheng Shi

Development of an algorithm for estimating snow hydrological parameters in wet snow regions using combined C- and L-band satellite-based SAR data

Develops an algorithm for estimating snow parameter distributions using synthetic aperture radar (SAR) images. The study area is a part of the Hokuriku District of Japan that is well known for having wet snow from the beginning of the winter season. We develop an algorithm to estimate snow density and roughness distributions using RADARSAT images acquired in February. Furthermore, we show the possibility of inferring snow depths from combined parameters estimated with an L-band SAR image.

Estimation of snow hydrological parameters using single-parameter, multi-temporal SAR images

The objective of this study is to develop an algorithm for estimating snow parameter distributions using multi-temporal synthetic aperture radar (SAR) data and a numerical scattering model. Simultaneous Radarsat SAR observations were carried out during the two winter seasons The study area is a part of the Hokuriku District of Japan that is well known for having wet snow from the beginning of the winter season. We compared the results of simulated backscattering coefficients with the ground-truth data and observed backscattering coefficients. Since the agreement was good, we demonstrated the possibility of estimating roughness distributions of soil surface using images acquired just before the snowfall with an assumption. Furthermore, we estimated the distributions of snow depth and roughness using images after a snowfall and estimated soil roughness distributions.

Application of algorithms for estimating surface soil moisture and roughness parameters using CRL/NASDA airborne SAR (PI-SAR) data

The goal of this study is to develop an algorithm for estimating the surface soil moisture and surface roughness using polarimetric synthetic aperture radar (SAR) data. In this study, an algorithm was applied to polarimetric airborne SAR data to estimate distributions of surface soil moisture and roughness. To validate the estimated soil moisture, the authors simultaneously conducted an experiment in October 1999 in Tsukuba, Ibaragi Pref., Japan. Surface soil moisture was obtained by the time-domain reflectometry (TDR) method, and the horizontal profiles of the land surface height were measured by a comb-style instrument for calculating the surface roughness parameters in test sites. Because the problem is site-specific and depends upon the measurement accuracy of both the ground truth data, and the SAR system including speckle noise, the comparison results did not agree well with measured and inferred soil moisture.

Estimating soil moisture distribution using polarimetric airborne SAR

The goal of this study is to develop an algorithm for estimating the surface soil moisture and surface roughness using polarimetric Synthetic Aperture Radar (SAR) data. In this study, an algorithm was applied to polarimetric airborne SAR data to estimate distributions of surface soil moisture and roughness. To validate the estimated soil moisture, we simultaneously conducted an experiment in October 1999 in Tsukuba Science City, Ibaragi Prefecture of Japan. Surface soil moisture was obtained by the Time- Domain Reflectometry (TDR) method, and the horizontal profiles of the land surface height were measured by a comb- style instrument for calculating the surface roughness parameters in test sites. Because the problem is site- specific and depends upon the measurement accuracy of both the ground truth data, the SAR system including speckle noise, and the effects of vegetation and artificial constructions, such as buildings, houses, roads, and roadside trees, the comparison results did not agree well with measured and inferred soil moisture.