2 research outputs found
Mapping vulnerable urban areas affected by slow-moving landslides using Sentinel-1InSAR 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 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.Postprint (published version
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 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.This work is supported by the Spanish Ministry of Economy and Competitiveness and EU
FEDER funds under projects ESP2013-47780-C2-2-R and ESP2013-47780-C2-1-R. Sentinel-1 data were provided
by the European Space Agency (ESA).Peer reviewe