Soil moisture monitoring in mountain areas by using high‐resolution SAR images: results from a feasibility study
Soil moisture monitoring in mountain areas by using high‐resolution SAR images: results from a feasibility study
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DOI：
10.1111/ejss.12189
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发表时间：
2014-11
影响因子：
4.2
通讯作者：
L. Pasolli;C. Notarnicola;G. Bertoldi;S. Della Chiesa;G. Niedrist;L. Bruzzone;U. Tappeiner;M. Zebisch
中科院分区：
文献类型：
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作者：
L. Pasolli;C. Notarnicola;G. Bertoldi;S. Della Chiesa;G. Niedrist;L. Bruzzone;U. Tappeiner;M. Zebisch
本文介绍了一个为期两年的试验结果进行了山区土壤水分遥感图像反演。特别是，使用了全极化合成孔径雷达RADARSAT和单极化ASAR图像。在对意大利北部北方Südtirol地区Alto Adige试验区进行SAR采集期间，进行了广泛的实地测量，以确定该地区土壤湿度变化、植被覆盖和土壤特性的特征。该地区设有17个气象站，每小时提供土壤湿度信息。针对这一复杂环境下SAR图像土壤水分反演问题，提出了一种基于支持向量回归（SVR）技术和辅助数据融合的改进算法。所选方法还结合了创新的多目标模型选择策略。结果表明，使用极化特征，如水平-水平极化（HH）和水平-垂直极化（HV）通道，提高了SMC在山区调查的估计，特别是因为HV通道有助于解开植被对雷达信号的影响。均方根误差（RMSE）表明土壤水分值的反演精度约为5%，这是很好的遥感数据估计土壤水分的要求。开展这项工作的主要目的是，鉴于即将进行的哨兵1号使命，利用高分辨率图像证明山区土壤水分反演的可行性。
This paper presents the results of a two‐year experiment carried out in mountain areas on soil moisture retrieval from remotely sensed images. In particular, fully polarimetric synthetic aperture radar (SAR) RADARSAT and single polarization ASAR images were used. During acquisitions of SAR over the test area in Alto Adige, Südtirol region, northern Italy, extensive field measurements were carried out to characterize the area in terms of soil moisture variability, vegetation cover and soil properties. The area is equipped with 17 meteorological stations that also provide information on soil moisture on an hourly basis. To deal with the process of soil moisture retrieval from SAR images in this challenging environment, an advanced algorithm based on the support vector regression (SVR) technique and the integration of ancillary data were successfully proposed. The selected method was also combined with an innovative multi‐objective strategy for model selection. The results indicate that the use of polarimetric features such as horizontal‐horizontal polarization (HH) and horizontal‐vertical polarization (HV) channels improves the estimation of SMC in the mountain area investigated, in particular because the HV channel contributes to disentangling the effect of vegetation on the radar signal. The root mean square error (RMSE) indicates accuracy of retrieval for soil moisture values of around 5%, which is well within the requirements for estimating soil moisture from remotely sensed data. This work was carried out with the main aim of demonstrating the feasibility of soil moisture retrieval in mountain areas with high‐resolution images in view of the upcoming Sentinel 1 mission.