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Proceedings Paper

GIS-based flood risk model evaluated by Fuzzy Analytic Hierarchy Process (FAHP)
Author(s): Tharapong Sukcharoen; Jingnong Weng; Charoenkalunyuta Teetat
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Paper Abstract

Over the last 2-3 decades, the economy of many countries around the world has been developed rapidly but it was unbalanced development because of expecting on economic growth only. Meanwhile it lacked of effective planning in the use of natural resources. This can significantly induce climate change which is major cause of natural disaster. Hereby, Thailand has also suffered from natural disaster for ages. Especially, the flood which is most hazardous disaster in Thailand can annually result in the great loss of life and property, environment and economy. Since the flood management of country is inadequate efficiency. It is unable to support the flood analysis comprehensively. This paper applied Geographic Information System and Multi-Criteria Decision Making to create flood risk model at regional scale. Angthong province in Thailand was used as the study area.

In practical process, Fuzzy logic technique has been used to improve specialist’s assessment by implementing with Fuzzy membership because human decision is flawed under uncertainty then AHP technique was processed orderly. The hierarchy structure in this paper was categorized the spatial flood factors into two levels as following: 6 criteria (Meteorology, Geology, Topography, Hydrology, Human and Flood history) and 8 factors (Average Rainfall, Distance from Stream, Soil drainage capability, Slope, Elevation, Land use, Distance from road and Flooded area in the past). The validity of the pair-wise comparison in AHP was shown as C.R. value which indicated that the specialist judgment was reasonably consistent. FAHP computation result has shown that the first priority of criteria was Meteorology. In addition, the Rainfall was the most influencing factor for flooding. Finally, the output was displayed in thematic map of Angthong province with flood risk level processed by GIS tools. The map was classified into: High Risk, Moderate Risk and Low Risk (13.20%, 75.58%, and 11.22% of total area).

Paper Details

Date Published: 25 October 2016
PDF: 9 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 999809 (25 October 2016); doi: 10.1117/12.2240268
Show Author Affiliations
Tharapong Sukcharoen, BeiHang Univ. (China)
Jingnong Weng, BeiHang Univ. (China)
Charoenkalunyuta Teetat, Chulalongkorn Univ. (Thailand)


Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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