Paper
26 October 2011 Object-based rapid change detection for disaster management
Holger Thunig, Ulrich Michel, Manfred Ehlers, Peter Reinartz
Author Affiliations +
Abstract
Rapid change detection is used in cases of natural hazards and disasters. This analysis lead to quick information about areas of damage. In certain cases the lack of information after catastrophe events is obstructing supporting measures within disaster management. Earthquakes, tsunamis, civil war, volcanic eruption, droughts and floods have much in common: people are directly affected, landscapes and buildings are destroyed. In every case geospatial data is necessary to gain knowledge as basement for decision support. Where to go first? Which infrastructure is usable? How much area is affected? These are essential questions which need to be answered before appropriate, eligible help can be established. This study presents an innovative strategy to retrieve post event information by use of an object-based change detection approach. Within a transferable framework, the developed algorithms can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated normalized temporal change index (NTCI) panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas which are developing new for cases where rebuilding has already started. The results of the study are also feasible for monitoring urban growth.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Holger Thunig, Ulrich Michel, Manfred Ehlers, and Peter Reinartz "Object-based rapid change detection for disaster management", Proc. SPIE 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II, 81810N (26 October 2011); https://doi.org/10.1117/12.897581
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Algorithm development

Buildings

Remote sensing

Image segmentation

Accuracy assessment

Earth observing sensors

Earthquakes

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