Assessing subsidence of Mexico City from InSAR and LandSat ETM+ with CGPS and SVM

Abstract This study presents an enhanced analysis of the subsidence rates and their effects on Mexico City. As a result excess water withdrawal, City is experiencing subsidence. We integrated analyzed Interferometric Synthetic Aperture Radar (InSAR), Continuous Global Positioning Systems (CGPS), optical remote sensing data to analyze City’s utilized 52 ENVISAT-ASAR, nine GPS stations, one Landsat ETM+ image from area understand better community. The finding this reveals high amount correlation (up 0.98) between two independent geodetic methods. also implemented Support Vector Machine (SVM) method based classify population density. used SVM compare Persistent Scatterer Interferometry (PSI) with buildings’ distribution densities. shows that fastest zone (i.e., areas greater than 100 mm/yr), which falls into above-mentioned temporal baseline, occurs in moderate building density areas.