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Spatial and temporal soil moisture estimation from RADARSAT-2 imagery over Flevoland, The Netherlands

机译:根据荷兰弗莱福兰(Flevoland)的RADARSAT-2影像估算时空土壤湿度

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Both spatial and temporal soil moisture dynamics have a large impact on hydrologic processes in agricultural catchments. As acquiring ground measurements of soil moisture is labor intensive, it is often limited in space (to a few locations) and time (to a small number of campaigns). Remote sensing offers a useful alternative, as it allows for observing both across time and space. This study analyses the potential to retrieve spatial and temporal soil moisture information from a series of RADARSAT-2 HH- and VV-polarized C-band (5.405. GHz) backscatter observations over a large number of (nearly) bare soil agricultural fields in Flevoland, The Netherlands, acquired in the framework of AgriSAR 2009. The RADARSAT-2 backscatter observations are found to be strongly correlated with continuous soil moisture measurements recorded at two agricultural sites during the 2009 growing season, as well as with spatial soil moisture measurements conducted during three intensive field campaigns in August and September 2009. Furthermore, two different soil moisture retrieval approaches have been evaluated: a physically-based modeling approach and change detection technique. The physically-based approach makes use of the Integral Equation Model with input of effective surface roughness parameters that are updated every acquisition for each field. The soil moisture retrieval accuracy of this technique is calculated based on leave-one-out cross-validation, yielding an accuracy (RMSE) about 4. vol% for fields with medium surface roughness at both polarization schemes. For smoother fields covered by stubbles, the retrieval accuracy slightly deteriorates. The change detection technique relies on a normalization of the backscatter between dry and wet reference soil moisture measurements, yielding accuracies about 4. vol% both for fields characterized by medium roughness and stubble conditions. This study confirms the large potential of RADARSAT-2 data for the retrieval of spatial and temporal soil moisture dynamics.
机译:土壤水分的时空动态对农业流域的水文过程都有很大的影响。由于获取土壤水分的地面测量值需要大量劳动,因此通常在空间(几个位置)和时间(少量活动)上受到限制。遥感提供了一种有用的替代方法,因为它可以跨时空观察。这项研究分析了从Flevoland大量(近乎)裸露的农业领域的一系列RADARSAT-2 HH和VV极化C波段(5.405。GHz)反向散射观测值中检索时空土壤水分信息的潜力。 ,荷兰,是在AgriSAR 2009框架内获得的。发现RADARSAT-2反向散射观测结果与2009年生长期在两个农业地点记录的连续土壤湿度测量值以及在2009年进行的空间土壤湿度测量值密切相关在2009年8月和2009年9月进行了三场密集的野外运动。此外,还评估了两种不同的土壤水分取回方法:基于物理的建模方法和变化检测技术。基于物理的方法将积分方程模型与有效表面粗糙度参数的输入结合使用,该参数对于每个场的每次采集都会更新。该技术的土壤水分取回精度是基于留一法交叉验证计算的,在两种极化方案下,对于中等表面粗糙度的田地,其精度(RMSE)约为4. vol%。对于由残茬覆盖的较平滑场,检索精度会稍有下降。变化检测技术依赖于干和湿参考土壤水分测量值之间反向散射的归一化,对于以中等粗糙度和发茬条件为特征的田地,其准确度均为4. vol%。这项研究证实了RADARSAT-2数据在时空土壤水分动力学研究中的巨大潜力。

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