位置:成果数据库 > 期刊 > 期刊详情页
Retrieving dry snow density with SIR-C polarimetric SAR data
  • 分类:TN957.52[电子电信—信号与信息处理;电子电信—信息与通信工程]
  • 作者机构:Chinese Acad Sci, Inst Remote Sensing Applicat, Lab Remote Sensing Informat Sci, Beijing 100101, Peoples R China
  • 相关基金:This work was supported by the Key Program of the Chinese Academy of Sciences (Grant Nos. KZ95T-03 and KZCX2-703); the National Natural Science Foundation of China (Grant Nos. 40001015 and 49989001); and the National Key Basic Research Program (Grant N
中文摘要:

For a given incidence angle at the snow surface, a greater snow density causes a greater change in the incidence angle at the snow-ground interface; for a given snow density, however, a larger incidence angle at the snow surface results in a greater change in the refractive angle in the snow layer, by comparing the difference of incidence angle at the snow-ground interface and the air-snow interface with different snow density. Algorithm for estimating dry snow density used backscattering measurements with polarimetric SAR at L-band frequency is developed based on simulation of the surface backscattering components ghh,and gvv using the IEM model and regression analysis. The comparison of the estimated snow density from SAR L-band images with that from field measurements during the SIR-C/X-SAR overpass shows root means square error of 0.050 g/cm3. It shows that this algorithm can be accurately used to estimate dry snow density distribution.

英文摘要:

For a given incidence angle at the snow surface, a greater snow density causes a greater change in the incidence angle at the snow-ground interface; for a given snow density, however, a larger incidence angle at the snow surface results in a greater change in the refractive angle in the snow layer, by comparing the difference of incidence angle at the snow-ground interface and the air-snow interface with different snow density. Algorithm for estimating dry snow density used backscattering measurements with polarimetric SAR at L-band frequency is developed based on simulation of the surface backscattering componentsσ g hh andσ g vv using the IEM model and regression analysis. The comparison of the estimated snow density from SAR L-band images with that from field measurements during the SIR-C/X-SAR overpass shows root means square error of 0.050 g/cm3. It shows that this algorithm can be accurately used to estimate dry snow density distribution.

同期刊论文项目
同项目期刊论文