Paper
26 October 2011 Object-based detection of destroyed buildings based on remotely sensed data and GIS
Author Affiliations +
Abstract
The paper describes an object-based method to detect destroyed buildings as a consequence of an earthquake. The investigation is based on the analysis of remotely sensed raster and vector-based data. The methodology includes three main steps: generation of features defining the states of buildings, classification of building state and data import in GIS. This paper concentrates on the first step of the three, the generation of features. The appropriately selected features are indispensable for the following successful classification. The described methodology is applied to remotely sensed images of areas that had been subject to an earthquake. Our preliminary results confirm the potential of the proposed approach for detection of the building state. The change detection methodology has been developed solely with Open Source Software. GRASS GIS is involved for vector and raster data processing and presentation. Programming languages Python and Bash are used to develop new GRASS-modules.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Natalia Sofina, Manfred Ehlers, and Ulrich Michel "Object-based detection of destroyed buildings based on remotely sensed data and GIS", Proc. SPIE 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II, 81810D (26 October 2011); https://doi.org/10.1117/12.898469
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Buildings

Raster graphics

Image segmentation

Geographic information systems

Earthquakes

Edge detection

Algorithm development

RELATED CONTENT


Back to Top