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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Comparison between a multi-scattering and multi-layer snow scattering model and its parameterized snow backscattering model
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Comparison between a multi-scattering and multi-layer snow scattering model and its parameterized snow backscattering model

机译：多散射多层积雪模型与参数化积雪反向散射模型的比较

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Snow Water Equivalent (SWE) is a crucial parameter in the study of climatology and hydrology. Active microwave remote sensing is one of the most promising techniques for estimating the distribution of SWE at high spatial resolutions in large areas. Development of reliable and accurate inversion techniques to recover SWE is one of the most important tasks in current microwave researches. However, a number of snow pack properties, including snow density, particle size, crystal shape, stratification, ground surface roughness and soil moisture, affect the microwave scattering signals and need to be properly modeled and exploited. In this paper, we developed a multi-layer, multi-scattering model for dry snow based on recent theoretical advances in snow and surface modeling. In the proposed multi-layer model, Matrix Doubling method is used to account for scattering from each snow layer; and Advanced Integral Equation Model (AIEM) is incorporated into the model to describe surface scattering. Comparisons were made between the model predictions and field observations from NASA Cold Land Processes Field Experiment (CLPX) during Third Intensive Observation Period (IOP3) and SARALPS-2007 field experiment supported by ESA. The results indicated that model predictions were in good agreement with field observations. With the confirmed confidence, the analyses on multiple scattering, scatterer shape, and snow stratification effects were further made based on the model simulations. Furthermore, a parameterized snow backscattering model with a simple form and high computational efficiency was developed using a database generated by the multiplescattering model. For a wide range of snow and soil properties, this parameterized model agrees well with the multiple-scattering model, with the root mean square error 0.20 dB, 0.24 dB and 0.43 dB for VV, HH and VH polarizations, respectively. This simplified model can be useful for the development of SWE retrieval algorithm and for fast simulations of radar signals over snow cover in land data assimilation systems.
机译：雪水当量（SWE）是气候学和水文学研究中的关键参数。有源微波遥感技术是在大空间中以高空间分辨率估算SWE分布的最有前途的技术之一。开发可靠，准确的反演技术以回收SWE是当前微波研究中最重要的任务之一。但是，许多积雪的性质，包括积雪的密度，粒径，晶体形状，分层，地面粗糙度和土壤湿度，都会影响微波散射信号，因此需要进行适当的建模和开发。在本文中，我们基于积雪和表面建模的最新理论进展，开发了干燥积雪的多层，多散射模型。在所提出的多层模型中，矩阵加倍法用于解决每个雪层的散射。并在模型中加入了高级积分方程模型（AIEM）以描述表面散射。比较了第三次密集观测期（IOP3）的NASA冷陆过程实地实验（CLPX）和ESA支持的SARALPS-2007实地实验的模型预测与实地观测之间的比较。结果表明，模型预测与现场观测结果吻合良好。有了确定的信心，在模型仿真的基础上，进一步进行了多重散射，散射体形状和积雪分层效应的分析。此外，利用由多重散射模型生成的数据库，开发了具有简单形式和高计算效率的参数化雪反向散射模型。对于大范围的雪和土壤属性，此参数化模型与多重散射模型非常吻合，VV，HH和VH极化的均方根误差分别为0.20 dB，0.24 dB和0.43 dB。这个简化的模型对于开发SWE检索算法以及在陆地数据同化系统中快速模拟积雪覆盖的雷达信号非常有用。

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