Shadow Buildings analysis for seismic damage assesment

After a natural disaster occurrence, such as earthquakes, the remote sensing often remains a substantial way to detect the extent of disaster. It allows the implementation of a real time post-disaster management plans, mobilization of emergency, coordination of seeking, rescue and mapping the damage...

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Published in2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS) pp. 123 - 128
Main Authors Saadi, Samira, Abbes, Khadidja, Amara, Baya Nait
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.04.2024
Subjects
Buildings
Disasters
Earthquakes
Satellites
Software
Time-frequency analysis
Urban areas
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Summary:After a natural disaster occurrence, such as earthquakes, the remote sensing often remains a substantial way to detect the extent of disaster. It allows the implementation of a real time post-disaster management plans, mobilization of emergency, coordination of seeking, rescue and mapping the damage spatial distribution.With the advent of the very high resolution satellites, the opportunities to improve the frequency and quality of urban data have emerged. The very high resolution satellites, whose discrimination power of objects on the ground can help to quickly develop useful tools to various stakeholders in post disaster crisis.This paper aims to develop an automatic process for detecting buildings height, throughits shadow form Quick Bird images analysis. The extraction of the building shadow is performed through a panchromatic channel, the size of the shadow and the height of the building are then extracted from a developed program under Matlab software. This method has the main advantage of being independent of time and season and the skill of the photo interpreter.The method is used for the detection of post-earthquake construction damages that occurred after Boumerdes earthquake of May 21 st 2003. Six buildings are considered and the results show a good agreement with the in situ observations.
DOI:10.1109/M2GARSS57310.2024.10537497