Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data
Landslides are widespread natural hazards that generate considerable damage and economic losses worldwide. Detecting terrain movements caused by these phenomena and characterizing affected urban areas is critical to reduce their impact. Here we present a fast and simple methodology to create maps of...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/9/9/876 |
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| author | Marta Béjar-Pizarro Davide Notti Rosa M. Mateos Pablo Ezquerro Giuseppe Centolanza Gerardo Herrera Guadalupe Bru Margarita Sanabria Lorenzo Solari Javier Duro José Fernández |
| author_facet | Marta Béjar-Pizarro Davide Notti Rosa M. Mateos Pablo Ezquerro Giuseppe Centolanza Gerardo Herrera Guadalupe Bru Margarita Sanabria Lorenzo Solari Javier Duro José Fernández |
| author_sort | Marta Béjar-Pizarro |
| collection | DOAJ |
| description | Landslides are widespread natural hazards that generate considerable damage and economic losses worldwide. Detecting terrain movements caused by these phenomena and characterizing affected urban areas is critical to reduce their impact. Here we present a fast and simple methodology to create maps of vulnerable buildings affected by slow-moving landslides, based on two parameters: (1) the deformation rate associated to each building, measured from Sentinel-1 SAR data, and (2) the building damage generated by the landslide movement and recorded during a field campaign. We apply this method to Arcos de la Frontera, a monumental town in South Spain affected by a slow-moving landslide that has caused severe damage to buildings, forcing the evacuation of some of them. Our results show that maximum deformation rates of 4 cm/year in the line-of-sight (LOS) of the satellite, affects La Verbena, a newly-developed area, and displacements are mostly horizontal, as expected for a planar-landslide. Our building damage assessment reveals that most of the building blocks in La Verbena present moderate to severe damages. According to our vulnerability scale, 93% of the building blocks analysed present high vulnerability and, thus, should be the focus of more in-depth local studies to evaluate the serviceability of buildings, prior to adopting the necessary mitigation measures to reduce or cope with the negative consequences of this landslide. This methodology can be applied to slow-moving landslides worldwide thanks to the global availability of Sentinel-1 SAR data. |
| first_indexed | 2024-12-24T03:26:03Z |
| format | Article |
| id | doaj.art-4d9e174769f444afb57da1eaf28eff09 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-24T03:26:03Z |
| publishDate | 2017-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-4d9e174769f444afb57da1eaf28eff092022-12-21T17:17:19ZengMDPI AGRemote Sensing2072-42922017-08-019987610.3390/rs9090876rs9090876Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR DataMarta Béjar-Pizarro0Davide Notti1Rosa M. Mateos2Pablo Ezquerro3Giuseppe Centolanza4Gerardo Herrera5Guadalupe Bru6Margarita Sanabria7Lorenzo Solari8Javier Duro9José Fernández10Geohazards InSAR Laboratory and Modeling Group (InSARlab), Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, SpainNational Research Council of Italy, Research Institute for Geo-Hydrological Protection (CNR-IRPI), Strada delle Cacce 73, 10135 Torino, ItalyGeohazards InSAR Laboratory and Modeling Group (InSARlab), Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, SpainGeohazards InSAR Laboratory and Modeling Group (InSARlab), Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, SpainDARES TECHNOLOGY, Esteve Terradas, 1, Edif. RDIT, Parc UPC-PMT, 08860 Castelldefels, Barcelona, SpainGeohazards InSAR Laboratory and Modeling Group (InSARlab), Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, SpainInstitute of Geosciences (CSIC, UCM), Facultad C. Matemáticas, 28040 Madrid, SpainGeohazards InSAR Laboratory and Modeling Group (InSARlab), Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, SpainEarth Sciences Department, University of Firenze, Via La Pira 4, 50121 Florence, ItalyDARES TECHNOLOGY, Esteve Terradas, 1, Edif. RDIT, Parc UPC-PMT, 08860 Castelldefels, Barcelona, SpainInstitute of Geosciences (CSIC, UCM), Facultad C. Matemáticas, 28040 Madrid, SpainLandslides are widespread natural hazards that generate considerable damage and economic losses worldwide. Detecting terrain movements caused by these phenomena and characterizing affected urban areas is critical to reduce their impact. Here we present a fast and simple methodology to create maps of vulnerable buildings affected by slow-moving landslides, based on two parameters: (1) the deformation rate associated to each building, measured from Sentinel-1 SAR data, and (2) the building damage generated by the landslide movement and recorded during a field campaign. We apply this method to Arcos de la Frontera, a monumental town in South Spain affected by a slow-moving landslide that has caused severe damage to buildings, forcing the evacuation of some of them. Our results show that maximum deformation rates of 4 cm/year in the line-of-sight (LOS) of the satellite, affects La Verbena, a newly-developed area, and displacements are mostly horizontal, as expected for a planar-landslide. Our building damage assessment reveals that most of the building blocks in La Verbena present moderate to severe damages. According to our vulnerability scale, 93% of the building blocks analysed present high vulnerability and, thus, should be the focus of more in-depth local studies to evaluate the serviceability of buildings, prior to adopting the necessary mitigation measures to reduce or cope with the negative consequences of this landslide. This methodology can be applied to slow-moving landslides worldwide thanks to the global availability of Sentinel-1 SAR data.https://www.mdpi.com/2072-4292/9/9/876landslidesInSARSentinel-1building damages |
| spellingShingle | Marta Béjar-Pizarro Davide Notti Rosa M. Mateos Pablo Ezquerro Giuseppe Centolanza Gerardo Herrera Guadalupe Bru Margarita Sanabria Lorenzo Solari Javier Duro José Fernández Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data Remote Sensing landslides InSAR Sentinel-1 building damages |
| title | Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data |
| title_full | Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data |
| title_fullStr | Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data |
| title_full_unstemmed | Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data |
| title_short | Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data |
| title_sort | mapping vulnerable urban areas affected by slow moving landslides using sentinel 1 insar data |
| topic | landslides InSAR Sentinel-1 building damages |
| url | https://www.mdpi.com/2072-4292/9/9/876 |
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