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ValInSAR: A Systematic Approach for the Validation of Differential SAR Interferometry in Land Subsidence Areas

Authors :
Juan M Lopez-Sanchez
Roberta Bonì
Claudia Meisina
Pablo Ezquerro
María I. Navarro-Hernández
Guadalupe Bru
Roberto Tomás Jover
Gerardo Herrera
Javier Valdes-Abellan
Universidad de Alicante. Departamento de Ingeniería Civil
Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal
Universidad de Alicante. Instituto Universitario de Investigación Informática
Ingeniería del Terreno y sus Estructuras (InTerEs)
Ingeniería Hidráulica y Ambiental (INGHA)
Señales, Sistemas y Telecomunicación
Source :
RUA. Repositorio Institucional de la Universidad de Alicante, Universidad de Alicante (UA)
Publication Year :
2022
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2022.

Abstract

Land subsidence is a natural or anthropogenic process triggering the settlement of the Earths surface. When this phenomenon is induced by groundwater withdrawal, compaction of unconsolidated sediments causes land displacement. Differential Interferometric Synthetic Aperture Radar (DInSAR) is widely used nowadays to monitor subsidence over extensive areas. However, validation of DInSAR measurements with in-situ techniques is lacking in many case studies, reducing the reliability of further analyses. The aim of this study is to propose a systematic methodology to validate DInSAR measurements with in-situ techniques to obtain reliable subsidence measurements. The paper provides a literature review of the most common approaches to validate DInSAR measurements and a description of the proposed systematic methodology, which is supported by a MATLAB open-source code. The methodology allows the analysis of both DInSAR-based velocity and displacement time series. We propose a set of statistics to assess the accuracy of the DInSAR estimates. For this purpose, RMSE parameters have been normalised with the range and the average of the in-situ deformation values. Moreover, combining these normalised parameters with the Pearson correlation coefficient (R2) a classification scheme is recommended for accepting/rejecting the DInSAR data for further analyses. This methodology has been applied in three study areas characterised by very well-documented subsidence processes: The Alto Guadalentn valley and Murcia city in Spain, and San Luis Potos in Mexico. María I. Navarro-Hernández is funded by the PRIMA programme supported by the European Union under grant agreement No 1924, project RESERVOIR. It also has been supported by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI) and the European funds for Regional Development (EFRD) under project PID2020-117303GB-C22. The research was carried out in the framework of ESA-MOST China DRAGON-5 project (ref. 59339).

Details

ISSN :
21511535 and 19391404
Volume :
15
Database :
OpenAIRE
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Accession number :
edsair.doi.dedup.....4c35d79f44f0670e1d955f43a9d32ec0