Earthquakes constitute one of the most relevant natural hazards on wide areas, involving both economical and social aspects. In the last years, lots of resources have been involved in developing methods for a quick response management and for mapping macroseismic damage information of urban estate; macroseismic data are especially critical either for social and scientific aspects. Turkey’s Marmara earthquake in 1999 demonstrated that seismologic community doesn’t have sufficient resources, organization and procedures to completely classify the damage on widely damaged urban areas. Thanks to the new documentation possibilities offered for instance by digital image acquisition and visual reality scenery georeferenced by GPS, a wide variety of techniques can be used in loci to help post survey damage assessment and macroseismic evaluation, but in the most relevant earthquakes, such as the Marmara’s one, these surveys are not sufficient to take all the information, due to time and resources limits. In this sense, image remote sensing techniques could play an important role to quickly detect damage distribution, also before starting of rescue operation, and therefore supplying a view of earthquake effects. Various techniques of data processing are useful to enhance damage information, and furthermore the increasing availability of high-resolution data leads to new possibilities in the integration of field survey with remote sensing. This work presents results in information extraction from Medium Resolution to Very High Resolution satellite imagery both for rapid damage assessment purpose and damage information extraction, using classical and object-oriented approaches. In particular, object oriented approach is useful to integrate different images, because is less affected by registration problems, and the improved space of states of the object could improve classification accuracy than probabilistic method. Cases of study presented are Marmara (1999) and Boumerdes (2003) earthquakes, where geometrical registration and radiometrical enhancement problems are faced up. These experimental studies are leading to the opportunity, in the future, to integrate classical damage survey and image oriented semi-automatic interpretation.

Image change detection on urban area: the earthquake case

BITELLI, GABRIELE;GUSELLA, LUCA;MOGNOL, ALESSANDRO
2004

Abstract

Earthquakes constitute one of the most relevant natural hazards on wide areas, involving both economical and social aspects. In the last years, lots of resources have been involved in developing methods for a quick response management and for mapping macroseismic damage information of urban estate; macroseismic data are especially critical either for social and scientific aspects. Turkey’s Marmara earthquake in 1999 demonstrated that seismologic community doesn’t have sufficient resources, organization and procedures to completely classify the damage on widely damaged urban areas. Thanks to the new documentation possibilities offered for instance by digital image acquisition and visual reality scenery georeferenced by GPS, a wide variety of techniques can be used in loci to help post survey damage assessment and macroseismic evaluation, but in the most relevant earthquakes, such as the Marmara’s one, these surveys are not sufficient to take all the information, due to time and resources limits. In this sense, image remote sensing techniques could play an important role to quickly detect damage distribution, also before starting of rescue operation, and therefore supplying a view of earthquake effects. Various techniques of data processing are useful to enhance damage information, and furthermore the increasing availability of high-resolution data leads to new possibilities in the integration of field survey with remote sensing. This work presents results in information extraction from Medium Resolution to Very High Resolution satellite imagery both for rapid damage assessment purpose and damage information extraction, using classical and object-oriented approaches. In particular, object oriented approach is useful to integrate different images, because is less affected by registration problems, and the improved space of states of the object could improve classification accuracy than probabilistic method. Cases of study presented are Marmara (1999) and Boumerdes (2003) earthquakes, where geometrical registration and radiometrical enhancement problems are faced up. These experimental studies are leading to the opportunity, in the future, to integrate classical damage survey and image oriented semi-automatic interpretation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/930
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