Spatio-Temporal Ontology for Change Analysis of Flood Affected Areas Using Remote Sensing Images
نویسندگان
چکیده
This article presents ST-IIM (Spatio-Temporal Image Information Mining) – an ontology to model the spatio-temporal changes during a flood disaster event. It is integrated with the image ontology to represent the various characteristics of Remote Sensing (RS) images. The goal is to query, detect and monitor disaster affected areas from multi-temporal images by automatic reasoning. The spatial and temporal aspects were modeled using DL-safe rules based on qualitative topological relationships and Allen's interval algebra respectively. This enables to draw inferences about the temporal changes and evolution of the Land Use/Cover (LU/LC) classes during the disaster event for rapid disaster response and recovery activities.
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تاریخ انتشار 2016