Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan

Central Asia, and in particular Tajikistan, is one of the most geologically hazardous areas in the world, particularly in terms of seismicity, floods, and landslides. The majority of landslides that occur in the region are seismically induced. A notable site is the Baipaza landslide, which has been...

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Main Authors: Francesco Poggi, Olga Nardini, Simone Fiaschi, Roberto Montalti, Emanuele Intrieri, Federico Raspini
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/17/12/2003
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author Francesco Poggi
Olga Nardini
Simone Fiaschi
Roberto Montalti
Emanuele Intrieri
Federico Raspini
author_facet Francesco Poggi
Olga Nardini
Simone Fiaschi
Roberto Montalti
Emanuele Intrieri
Federico Raspini
author_sort Francesco Poggi
collection DOAJ
description Central Asia, and in particular Tajikistan, is one of the most geologically hazardous areas in the world, particularly in terms of seismicity, floods, and landslides. The majority of landslides that occur in the region are seismically induced. A notable site is the Baipaza landslide, which has been subject to deformation since the 1960s, with the most recent collapse occurring in 2002. The potential collapse of the landslide represents a significant risk to the nearby Baipaza hydroelectric dam, situated 5 km away, and has the potential to create widespread challenges for the entire region. The objective of this work is to provide a comprehensive characterization of the Baipaza landslide through the utilization of satellite remote-sensing techniques, exploiting both Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical images freely available from the European Space Agency’s (ESA) Copernicus project. The employment of these two techniques enables the acquisition of insights into the distinctive characteristics and dynamics of the landslide, including the displacement rates up to 246 mm/year in the horizontal component; the precise mapping of landslide boundaries and the identification of distinct sectors with varying deformation patterns; and an estimation of the volume involved within the landslide, which is approximately of 1 billion m<sup>3</sup>.
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spelling doaj-art-487bb9d9dd0a47d69f76675d2863d7f12025-06-25T14:23:24ZengMDPI AGRemote Sensing2072-42922025-06-011712200310.3390/rs17122003Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, TajikistanFrancesco Poggi0Olga Nardini1Simone Fiaschi2Roberto Montalti3Emanuele Intrieri4Federico Raspini5Department of Earth Sciences, University of Florence, DST UNIFI, Via Giorgio La Pira 4, 50121 Florence, ItalyDepartment of Earth Sciences, University of Florence, DST UNIFI, Via Giorgio La Pira 4, 50121 Florence, ItalyTRE ALTAMIRA, 475 W Georgia St #410, Vancouver, BC V6B 4M9, CanadaTRE ALTAMIRA, C/de Còrsega, 381, 08037 Barcelona, SpainDepartment of Earth Sciences, University of Florence, DST UNIFI, Via Giorgio La Pira 4, 50121 Florence, ItalyDepartment of Earth Sciences, University of Florence, DST UNIFI, Via Giorgio La Pira 4, 50121 Florence, ItalyCentral Asia, and in particular Tajikistan, is one of the most geologically hazardous areas in the world, particularly in terms of seismicity, floods, and landslides. The majority of landslides that occur in the region are seismically induced. A notable site is the Baipaza landslide, which has been subject to deformation since the 1960s, with the most recent collapse occurring in 2002. The potential collapse of the landslide represents a significant risk to the nearby Baipaza hydroelectric dam, situated 5 km away, and has the potential to create widespread challenges for the entire region. The objective of this work is to provide a comprehensive characterization of the Baipaza landslide through the utilization of satellite remote-sensing techniques, exploiting both Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical images freely available from the European Space Agency’s (ESA) Copernicus project. The employment of these two techniques enables the acquisition of insights into the distinctive characteristics and dynamics of the landslide, including the displacement rates up to 246 mm/year in the horizontal component; the precise mapping of landslide boundaries and the identification of distinct sectors with varying deformation patterns; and an estimation of the volume involved within the landslide, which is approximately of 1 billion m<sup>3</sup>.https://www.mdpi.com/2072-4292/17/12/2003landslideSAR interferometrySentinel-1COSI-CorrSentinel-2
spellingShingle Francesco Poggi
Olga Nardini
Simone Fiaschi
Roberto Montalti
Emanuele Intrieri
Federico Raspini
Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan
Remote Sensing
landslide
SAR interferometry
Sentinel-1
COSI-Corr
Sentinel-2
title Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan
title_full Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan
title_fullStr Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan
title_full_unstemmed Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan
title_short Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan
title_sort multi sensor satellite analysis for landslide characterization a case of study from baipaza tajikistan
topic landslide
SAR interferometry
Sentinel-1
COSI-Corr
Sentinel-2
url https://www.mdpi.com/2072-4292/17/12/2003
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