首页> 外文会议>International Geoscience and Remote Sensing Symposium >Validation of physical model and radar retrieval algorithm of snow water equivalent using SnowSAR data
【24h】

Validation of physical model and radar retrieval algorithm of snow water equivalent using SnowSAR data

机译:利用SnowSAR数据验证雪水当量物理模型和雷达检索算法

获取原文

摘要

We validate an absorption based radar retrieval algorithm of snow water equivalent (SWE) using X- and Ku-band backscatter with airborne SAR data. The bicontinuous dense media radiative transfer (Bic-DMRT) model is first applied to generate a look-up table of snow properties against backscattering at X- and Ku-bands. In the retrieval algorithm, the background scattering is subtracted from the total scattering giving the volume scattering of snow. With the look-up table, we generate regression equations between multiple and single scattering and correlations between the scattering albedo and optical thickness at the two bands. With these relationships and the volume scattering of the snowpack, the best solution for the radar observation is found using a priori constrained least-squares cost function. Next, the absorption loss of the snowpack is derived from the solution, which is directly proportional to the SWE. We have applied the algorithm to airborne SAR observations from Finland and Canada. The retrieval algorithm is shown to be effective, achieving root mean square error (RMSE) of ~19 mm for both SnowSAR data, which is smaller than the 20mm RMSE requirement of SCLP.
机译:我们使用机载SAR数据,使用X波段和Ku波段后向散射验证了基于吸收率的雪水当量(SWE)雷达检索算法。首先,使用双连续密集介质辐射传输(Bic-DMRT)模型来生成雪属性查找表,以防X和Ku波段的反向散射。在检索算法中,从总散射中减去背景散射,得出雪的体积散射。使用查找表,我们生成了多次散射和单次散射之间的回归方程,以及两个波段的散射反照率和光学厚度之间的相关性。通过这些关系和积雪的体积散射,可以使用先验约束最小二乘成本函数找到雷达观测的最佳解决方案。接下来,从解中得出积雪的吸收损失,该损失与SWE成正比。我们已将该算法应用于来自芬兰和加拿大的机载SAR观测。该检索算法被证明是有效的,对于两个SnowSAR数据均实现了约19 mm的均方根误差(RMSE),该均方根误差小于SCLP的20mm RMSE要求。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号