Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images

Author:

Pasolli L.12,Notarnicola C.2ORCID,Bruzzone L.1,Bertoldi G.3ORCID,Della Chiesa S.34,Hell V.3,Niedrist G.34,Tappeiner U.34,Zebisch M.2,Del Frate F.5,Vaglio Laurin G.5

Affiliation:

1. Department of Information Engineering and Computer Science, University of Trento, Via Sommarive, 14, 38123 Trento, Italy

2. EURAC-Institute for Applied Remote Sensing, Viale Druso, 1, 39100 Bolzano, Italy

3. EURAC-Institute for Alpine Environment, Viale Druso, 1, 39100 Bolzano, Italy

4. Institute of Ecology, University of Innsbruck, Sternwartestr. 15, 6020 Innsbruck, Austria

5. Department of Computer Science, Systems and Production Engineering, Tor Vergata University, Via del Politecnico, 1, 00133 Rome, Italy

Abstract

Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely sensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However, especially in the Alps, the presence of vegetation and the heterogeneity of topography may significantly affect the microwave signal, thus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil moisture in an alpine catchment is investigated. We first carry out a sensitivity analysis of the SAR signal to the moisture content of soil and other target properties (e.g., topography and vegetation). Then we propose a technique for estimating soil moisture based on the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms of accuracy over point measurements and effectiveness in handling spatially distributed data.

Publisher

Hindawi Limited

Subject

Earth-Surface Processes,Soil Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3