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合成孔径雷达反演裸土表面土壤湿度中的土壤粗糙度参数化问题

On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar.

作者信息

Verhoest Niko E C, Lievens Hans, Wagner Wolfgang, Álvarez-Mozos Jesús, Moran M Susan, Mattia Francesco

机构信息

Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, B-9000 Ghent, Belgium.

Christian Doppler Laboratory, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology (TU Wien), Gusshausstraβe 27-29, 1040 Vienna, Austria.

出版信息

Sensors (Basel). 2008 Jul 15;8(7):4213-4248. doi: 10.3390/s8074213.

Abstract

Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale.

摘要

合成孔径雷达已显示出在区域尺度上获取土壤湿度图的巨大潜力。然而,由于后向散射信号由多种地表特征决定,使用单一配置图像进行土壤湿度反演是一个不适定问题。除非有准确的地表粗糙度参数值,否则从雷达后向散射中反演土壤湿度通常会提供不准确的估计。土壤粗糙度的特征尚未得到充分理解,当使用不同的测量方法时,同一地表可获得大范围的粗糙度参数值。本文进行了文献综述,总结了在对土壤粗糙度进行参数化时遇到的问题以及所报告的这些误差对反演土壤湿度的影响。针对解决粗糙度参数化问题以及研究这些粗糙度问题对土壤湿度反演精度和尺度的影响提出了一些建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffbd/3697171/a17e35495c88/sensors-08-04213f1.jpg

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