单采集单配置SAR数据反演土壤表面参数的优化方法

IF 2 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Comptes Rendus Geoscience Pub Date : 2019-04-01 DOI:10.1016/j.crte.2018.11.005
Arsalan Ghorbanian, Mahmod Reza Sahebi, Ali Mohammadzadeh
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引用次数: 8

摘要

本研究提出了一种利用单采集单配置合成孔径雷达(SAR)系统获取土壤表面参数的新方法。土壤表面参数如土壤湿度和表面粗糙度是许多环境研究的关键要素,包括地球表面水循环、能量交换、农业和地质。遥感技术,特别是SAR数据,通常用于检索大面积的土壤表面参数。针对SAR数据反演土壤表面参数,提出了几种后向散射模型。然而,这些后向散射模型通常需要多配置SAR数据,包括多极化、多频率和多入射角。本文提出了一种利用单采集单配置SAR数据检索土壤表面参数的方法。其创新之处是利用单采集单配置SAR数据,利用遗传算法(GA)优化方法检索土壤表面参数;我们使用修正的Dubois模型(MDM)作为HH偏振的后向散射模型。对来自魁北克(Radarsat-1)、安大略省(SIR-C)和俄克拉荷马州(AIRSAR)的三个HH偏振和C波段数据集进行了分析。然后将土壤湿度和土壤表面粗糙度的检索值与具有相应参数的地面真值进行比较。我们采用了不同的标准,包括平均绝对误差(MAE)、均方根误差(RMSE)、性能系数(CP)和相关系数来考察所提出方法的性能。这一分析表明,遗传算法在土壤表面参数的检索方面具有一定的能力。基于我们的研究结果,该方法提供了一种可行的替代方法,可以在只有单采集单配置SAR数据时检索土壤表面参数。
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Optimization approach to retrieve soil surface parameters from single-acquisition single-configuration SAR data

This study suggests a novel approach to the retrieval of soil surface parameters using a single-acquisition single-configuration synthetic-aperture radar (SAR) system. Soil surface parameters such as soil moisture and surface roughness are key elements for many environmental studies, including Earth surface water cycles, energy exchange, agriculture, and geology. Remote sensing techniques, especially SAR data, are commonly used to retrieve such soil surface parameters over large areas. Several backscattering models have been proposed for soil surface parameters retrieval from SAR data. However, commonly, these backscattering models require multi configuration SAR data, including multi-polarization, multi-frequency, and multi-incidence angle. Here we propose a methodology that employs single-acquisition single-configuration SAR data for the retrieval of soil surface parameters. The originality is to use single-acquisition single-configuration SAR data to retrieve the soil surface parameters using an optimization approach by the genetic algorithm (GA); we have used the modified Dubois model (MDM) in HH polarization as the backscattering model. Three HH polarization and C band data sets from Quebec (Radarsat-1), Ontario (SIR-C), and Oklahoma (AIRSAR) were analyzed. The retrieved values of soil moisture and soil surface roughness were then compared to ground truth measurements with corresponding parameters. We employed diverse criteria, including the mean absolute error (MAE), the root mean square error (RMSE), the coefficient of performance (CP), and the correlation coefficient to investigate the performance of the proposed methodology. This analysis suggests the capability of the GA for the retrieval of soil surface parameters. Based on our findings, this method presents a viable alternative approach to the retrieval of soil surface parameters when only single-acquisition single-configuration SAR data is available.

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来源期刊
Comptes Rendus Geoscience
Comptes Rendus Geoscience 地学-地球科学综合
CiteScore
2.80
自引率
14.30%
发文量
68
审稿时长
5.9 weeks
期刊介绍: Created in 1835 by physicist François Arago, then Permanent Secretary, the journal Comptes Rendus de l''Académie des sciences allows researchers to quickly make their work known to the international scientific community. It is divided into seven titles covering the range of scientific research fields: Mathematics, Mechanics, Chemistry, Biology, Geoscience, Physics and Palevol. Each series is led by an editor-in-chief assisted by an editorial committee. Submitted articles are reviewed by two scientists with recognized competence in the field concerned. They can be notes, announcing significant new results, as well as review articles, allowing for a fine-tuning, or even proceedings of symposia and other thematic issues, under the direction of invited editors, French or foreign.
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