Monitoring the dynamics of snow and glaciers in the Indian Himalaya has always attracted the attention of the remote sensing community. The snow water equivalent (SWE) represents the amount of water contained in the snowpack, and it is a product of snow depth (SD) and snow density (${\rho }_s$). The estimation of SD at high spatial and temporal resolution is still a challenge, especially in rugged mountainous terrain, like the Himalayas. In this paper, bistatic TerraSAR-X quad-polarization data is used to retrieve the SD using the Polarimetric SAR Interferometry (PolInSAR) coherences. The PolInSAR coherence at hv polarization shows a linear relationship with SD, which is verified with the field data. This relationship is utilized for the retrieval of SD using the proposed algorithm. Spatially variable ${\rho }_s$ is used to retrieve the SWE. The coefficient of determination ($R^2$) values of the retrieved SD on 8 January 2016 and 19 January 2016 are 0.62 and 0.80, respectively. Likewise, it is 0.61 and 0.72 for retrieved SWE. The root mean square error (RMSE) in SD on 8 January 2016 and 19 January 2016 are 7.00 cm and 5.48 cm, respectively; for SWE, it is 2.02 cm and 1.48 cm, respectively.

监测印度喜马拉雅山中冰雪和冰川的动态一直吸引着遥感界的关注。雪水当量（SWE）表示雪堆中包含的水量，是雪深（SD）和雪密度（${\rho }_s$）。在高时空分辨率下估算SD仍然是一个挑战，特别是在喜马拉雅山等崎mountain的山区。在本文中，双极化TerraSAR-X四极化数据用于通过极化SAR干涉测量（PolInSAR）相干来检索SD。hv极化时的PolInSAR相干性与SD呈线性关系，这已通过现场数据验证。利用所提出的算法将该关系用于SD的检索。空间可变${\rho }_s$用于检索SWE。确定系数（${\mathrm{[R}}^2$）在2016年1月8日和2016年1月19日检索到的SD值分别为0.62和0.80。同样，检索到的SWE分别为0.61和0.72。SD在2016年1月8日和2016年1月19日的均方根误差（RMSE）分别为7.00 cm和5.48 cm; 对于SWE，分别为2.02厘米和1.48厘米。