A fuzzy decision making system for building damage map creation using high resolution satellite imagery
| Autor: | Farhad Samadzadegan, Peter Reinartz, H. Rastiveis |
|---|---|
| Přispěvatelé: | Guzzetti, Fausto, Malamud, Bruce |
| Jazyk: | němčina |
| Rok vydání: | 2013 |
| Předmět: |
Manual interpretation
Computer science High resolution fuzzy decision rules lcsh:TD1-1066 Rendering (computer graphics) Fuzzy inference system damage assessment Satellite imagery Computer vision lcsh:Environmental technology. Sanitary engineering Roof lcsh:Environmental sciences Fuzzy decision Data source lcsh:GE1-350 Photogrammetrie und Bildanalyse business.industry lcsh:QE1-996.5 lcsh:Geography. Anthropology. Recreation lcsh:Geology lcsh:G earthquake General Earth and Planetary Sciences Artificial intelligence business satellite images |
| Zdroj: | Natural Hazards and Earth System Sciences, Vol 13, Iss 2, Pp 455-472 (2013) |
| ISSN: | 1684-9981 |
| Popis: | Recent studies have shown high resolution satellite imagery to be a powerful data source for post-earthquake damage assessment of buildings. Manual interpretation of these images, while being a reliable method for finding damaged buildings, is a subjective and time-consuming endeavor, rendering it unviable at times of emergency. The present research, proposes a new state-of-the-art method for automatic damage assessment of buildings using high resolution satellite imagery. In this method, at the first step a set of pre-processing algorithms are performed on the images. Then, extracting a candidate building from both pre- and post-event images, the intact roof part after an earthquake is found. Afterwards, by considering the shape and other structural properties of this roof part with its pre-event condition in a fuzzy inference system, the rate of damage for each candidate building is estimated. The results obtained from evaluation of this algorithm using QuickBird images of the December 2003 Bam, Iran, earthquake prove the ability of this method for post-earthquake damage assessment of buildings. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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