Satellite data analysis for earthquake damage assessment

Paolo Gamba; Andrea Marazzi; Eugenio Costamagna

doi:10.1117/12.298164

30 December 1997 Satellite data analysis for earthquake damage assessment

Paolo Gamba, Andrea Marazzi, Eugenio Costamagna

Proceedings Volume 3222, Earth Surface Remote Sensing; (1997) https://doi.org/10.1117/12.298164
Event: Aerospace Remote Sensing '97, 1997, London, United Kingdom

Abstract

This paper moves from the results of RADATT (rapid damage assessment telematic tool), a project funded by the European Commission -- DG XIII. The final goal of the developed system architecture was to sensibly reduce the effects of a devastating seismic event by providing the responsible agencies a rapid and reliable damage detection and estimation of the extent and location of the suffered area. This result has been accomplished by the integration, within a single user interface environment, of data access and standardization techniques, image processing tools, GIS technology, analytical modeling and communication tools. A two-phase operating model has been conceived. In the pre-event era, images and data about building and infrastructures are collected and analyzed exploiting GIS capabilities. Immediately after the occurrence of the earthquake, the system must be ready to receive near- real time satellite imagery of the affected area to be compared with the pre-event imagery data set. A correspondence between the integrated databases, within the GIS environment, and the real-time imagery is also established. The post-event imagery is then compared with the pre-event one, by means of different digital processing techniques to exploit the different resolution of satellite images. In this paper the capability of this quick change detection analysis, given the availability of the pre-event information in the GIS environment, is discussed.

Citation Download Citation

Paolo Gamba, Andrea Marazzi, and Eugenio Costamagna "Satellite data analysis for earthquake damage assessment", Proc. SPIE 3222, Earth Surface Remote Sensing, (30 December 1997); https://doi.org/10.1117/12.298164

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