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Evaluation of Different Radiative Transfer Models for Microwave Backscatter Estimation of Wheat Fields
Remote Sensing ( IF 5 ) Pub Date : 2020-09-17 , DOI: 10.3390/rs12183037
Thomas Weiß , Thomas Ramsauer , Alexander Löw , Philip Marzahn

This study aimed to analyze existing microwave surface (Oh, Dubois, Water Cloud Model “WCM”, Integral Equation Model “IEM”) and canopy (Water Cloud Model “WCM”, Single Scattering Radiative Transfer “SSRT”) Radiative Transfer (RT) models and assess advantages and disadvantages of different model combinations in terms of VV polarized radar backscatter simulation of wheat fields. The models are driven with field measurements acquired in 2017 at a test site near Munich, Germany. As vegetation descriptor for the canopy models Leaf Area Index (LAI) was used. The effect of empirical model parameters is evaluated in two different ways: (a) empirical model parameters are set as static throughout the whole time series of one growing season and (b) empirical model parameters describing the backscatter attenuation by the canopy are treated as non-static in time. The model results are compared to a dense Sentinel-1 C-band time series with observations every 1.5 days. The utilized Sentinel-1 time series comprises images acquired with different satellite acquisition geometries (different incidence and azimuth angles), which allows us to evaluate the model performance for different acquisition geometries. Results show that total LAI as vegetation descriptor in combination with static empirical parameters fit Sentinel-1 radar backscatter of wheat fields only sufficient within the first half of the vegetation period. With the saturation of LAI and/or canopy height of the wheat fields, the observed increase in Sentinel-1 radar backscatter cannot be modeled. Probable cause are effects of changes within the grains (both structure and water content per leaf area) and their influence on the backscatter. However, model results with LAI and non-static empirical parameters fit the Sentinel-1 data well for the entire vegetation period. Limitations regarding different satellite acquisition geometries become apparent for the second half of the vegetation period. The observed overall increase in backscatter can be modeled, but a trend mismatch between modeled and observed backscatter values of adjacent time points with different acquisition geometries is observed.

中文翻译:

不同辐射传输模型对麦田微波反向散射的评估

这项研究旨在分析现有的微波表面(哦,Dubois,水云模型“ WCM”,积分方程模型“ IEM”)和顶篷(水云模型“ WCM”,单散射辐射转移“ SSRT”)辐射转移(RT)在小麦田的VV极化雷达反向散射模拟方面,对不同的模型组合进行了建模并评估了不同模型组合的优缺点。这些模型由2017年在德国慕尼黑附近的测试地点获得的现场测量结果驱动。叶面积指数(LAI)被用作树冠模型的植被描述符。经验模型参数的效果通过两种不同的方式进行评估:(a)在一个生长季节的整个时间序列中将经验模型参数设置为静态,并且(b)将描述冠层反向散射衰减的经验模型参数在时间上视为非静态。将模型结果与每1.5天观察一次的密集Sentinel-1 C波段时间序列进行比较。利用的Sentinel-1时间序列包括以不同的卫星采集几何体(不同的入射角和方位角)采集的图像,这使我们能够评估不同采集几何体的模型性能。结果表明,总的LAI作为植被描述符与静态经验参数相结合,仅在植被期的前半年才适合麦田的Sentinel-1雷达反向散射。随着LAI的饱和和/或麦田的冠层高度,无法对观测到的Sentinel-1雷达反向散射的增加进行建模。可能的原因是谷物内部变化的影响(结构和每叶面积的水分含量)及其对反向散射的影响。但是,具有LAI和非静态经验参数的模型结果在整个植被期内都很好地拟合了Sentinel-1数据。在植被期的后半段,关于不同卫星采集几何形状的限制变得显而易见。可以对观察到的反向散射的总体增加进行建模,但是可以观察到,具有不同采集几何形状的相邻时间点的建模和观察到的反向散射值之间的趋势不匹配。可能的原因是谷物内部变化的影响(结构和每叶面积的水分含量)及其对反向散射的影响。但是,具有LAI和非静态经验参数的模型结果在整个植被期内都很好地拟合了Sentinel-1数据。在植被期的后半段,有关不同卫星采集几何形状的限制变得很明显。可以对观察到的反向散射的总体增加进行建模,但是可以观察到具有不同采集几何形状的相邻时间点的建模和观察到的反向散射值之间的趋势不匹配。可能的原因是谷物内部变化的影响(结构和每叶面积的水分含量)及其对反向散射的影响。但是,具有LAI和非静态经验参数的模型结果在整个植被期内都很好地拟合了Sentinel-1数据。在植被期的后半段,关于不同卫星采集几何形状的限制变得显而易见。可以对观察到的反向散射的总体增加进行建模,但是可以观察到具有不同采集几何形状的相邻时间点的建模和观察到的反向散射值之间的趋势不匹配。在植被期的后半段,有关不同卫星采集几何形状的限制变得很明显。可以对观察到的反向散射的总体增加进行建模,但是可以观察到具有不同采集几何形状的相邻时间点的建模和观察到的反向散射值之间的趋势不匹配。在植被期的后半段,有关不同卫星采集几何形状的限制变得很明显。可以对观察到的反向散射的总体增加进行建模,但是可以观察到,具有不同采集几何形状的相邻时间点的建模和观察到的反向散射值之间的趋势不匹配。
更新日期:2020-09-18
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