Version 1
: Received: 6 September 2019 / Approved: 7 September 2019 / Online: 7 September 2019 (01:19:04 CEST)
How to cite:
Poreh, D.; Pirasteh, S. InSAR and Landsat ETM+ incorporating with CGPS and SVM to Determine Subsidence Rates and Effects on Mexico City. Preprints2019, 2019090082. https://doi.org/10.20944/preprints201909.0082.v1
Poreh, D.; Pirasteh, S. InSAR and Landsat ETM+ incorporating with CGPS and SVM to Determine Subsidence Rates and Effects on Mexico City. Preprints 2019, 2019090082. https://doi.org/10.20944/preprints201909.0082.v1
Poreh, D.; Pirasteh, S. InSAR and Landsat ETM+ incorporating with CGPS and SVM to Determine Subsidence Rates and Effects on Mexico City. Preprints2019, 2019090082. https://doi.org/10.20944/preprints201909.0082.v1
APA Style
Poreh, D., & Pirasteh, S. (2019). InSAR and Landsat ETM+ incorporating with CGPS and SVM to Determine Subsidence Rates and Effects on Mexico City. Preprints. https://doi.org/10.20944/preprints201909.0082.v1
Chicago/Turabian Style
Poreh, D. and Saied Pirasteh. 2019 "InSAR and Landsat ETM+ incorporating with CGPS and SVM to Determine Subsidence Rates and Effects on Mexico City" Preprints. https://doi.org/10.20944/preprints201909.0082.v1
Abstract
This study presents an analysis of subsidence rates and their effects on Mexico City. Mexico City is well known for its subsidence as a result of excess water withdrawal for many years. This study focuses on this problem utilizing the integration of Interferometric Synthetic Aperture Radar (InSAR), Continuous Global Positioning Systems (CGPS), and optical remote sensing data. Fifty-two ENVISAT-ASAR, nine GPS stations, and one Landsat ETM+ image from Mexico City area have been analyzed to prepare a better understanding of the subsidence rates and its effects on Mexico City’s commune. This study has utilized InSAR methods. It includes differential interferometry and Persistent Scatter Interferometry (PSI) to monitor the existing subsidence in the Mexico City area. The InSAR data covers the temporal baseline between 2002 until June 2010, and the GPS data include temporal baseline from 1998 until 2012. Maximum of 352 mm annually change in Line Of Sight (LOS) direction is in agreement with the previous geodetic studies. InSAR data have been compared with CGPS data at the same time interval. 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 populated density area. This method performed comparing the subsidence rates with populated area buildings. This integrated study shows that the fastest subsidence zone (i.e., areas greater than 100 mm/yr) in the over mentioned temporal baseline occurs in the high and sparsely populated areas
Keywords
Mexico City; subsidence; InSAR; GPS; PSI; SVM
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
