Assessing subsidence of Mexico City from InSAR and LandSat ETM plus with CGPS and SVM
Por:
Poreh, Davod, Pirasteh, Saied, Cabral-Cano, Enrique
Publicada:
5 mar 2021
Resumen:
This study presents an enhanced analysis of the subsidence rates and
their effects on Mexico City. As a result of excess water withdrawal,
Mexico City is experiencing subsidence. We integrated and analyzed
Interferometric Synthetic Aperture Radar (InSAR), Continuous Global
Positioning Systems (CGPS), and optical remote sensing data to analyze
Mexico City's subsidence. This study utilized 52 ENVISAT-ASAR, nine GPS
stations, and one Landsat ETM+ image from the Mexico City area to
understand better the subsidence rates and their effects on Mexico
City's community. The finding of this study reveals a high amount of
correlation (up to 0.98) between two independent geodetic methods. We
also implemented the Support Vector Machine (SVM) analysis method based
on Landsat ETM+ image to classify Mexico City's population density. We
used SVM to compare Persistent Scatterer Interferometry (PSI) subsidence
rates with the buildings' distribution densities. This integrated study
shows that the fastest subsidence zone (i.e., areas greater than 100
mm/yr), which falls into the above-mentioned temporal baseline, occurs
in high and moderate building distribution density areas.
Filiaciones:
Poreh, Davod:
Dipartimento di Ingegneria Elettrica edelle Tecnologie dell’Informazione, Universita degli Studi di, Napoli Federico II, Via Claudio, 21, Naples, 80125, Italy
Pirasteh, Saied:
Department of Surveying and Geoinformatics, Faculty of Geosciences and Environmental Engineering (FGEE), Southwest Jiaotong University, Chengdu, 611756, China
Cabral-Cano, Enrique:
Departamento de Geomagnetismo Expiración, Instituto de Geofísica, Universidad Nacional, Autónoma de México, Ciudad Universitaria, México D.F, 04510, Mexico
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