This article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events.For earthquakes we use peak ground...This article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events.For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator.For volcanoes we employ volcanic ash data as a proxy for local damages.Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images.We demonstrate the use of these indices with a case study of Indonesia,a country frequently exposed to earthquakes and volcanic eruptions.The results show that the indices capture the areas with the highest damage,and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014.The indices were constructed using a combination of software programs—ArcGIS/Python,Matlab,and Stata.We also outline what potential freeware alternatives exist.Finally,for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.展开更多
文摘This article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events.For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator.For volcanoes we employ volcanic ash data as a proxy for local damages.Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images.We demonstrate the use of these indices with a case study of Indonesia,a country frequently exposed to earthquakes and volcanic eruptions.The results show that the indices capture the areas with the highest damage,and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014.The indices were constructed using a combination of software programs—ArcGIS/Python,Matlab,and Stata.We also outline what potential freeware alternatives exist.Finally,for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.
