This study proposes an integrated Geographic Information System (GIS)Fuzzy Multi-Criteria Decision Making (F-MCDM)model to assess the impacts of flood on residential property prices. Triangular Fuzzy numbers was implemented to address limitationssuch as uncertainty, bias and ambiguity inherent in the conventional Analytic Network Process (ANP) flood model criteria ranking thereby improving the accuracy and reliability of the susceptibility model. The developed Fuzzy-ANP’s (F-ANP) pair-wise comparison technique was used to rankthe relative importance of nine flood conditioning criteria based on experts’ input. Utilizing GIS and re-mote sensing data and techniques on Kelantan, a perennially flooded state in Malaysia, FANP based criterion maps weregenerated and aggregated to produce flood susceptibility maps of the area, showing the flood vulnerability levels of different locations. A 10-year inventory of real estate prices from the National Property Information Centre (NAPIC), Malaysia was analyzed to investigate the trend in market prices of residential properties situated in the high flood probable zones highlighted by the spatial F-ANP model. Model validation results showed that 59.42% and 36.23% of past flood events fall within the very high and high susceptible locations ofthe susceptibility map respectively, confirming its high accuracy. A weak positive correlation also exists between the highly susceptible flood class and housing locations vs market prices. We conclude that the ensemble GIS-FANP flood susceptibility modelcan produce maps capable of conveying accurate risk information to a broad range of stakeholders thereby facilitating decision making. However, other factors such as supply and demand, construction cost, macro-economy and micro-economy tend to also exert some influence on real estate prices, together with location in hazard-prone areas.

中文翻译：

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利用地理空间技术和Fuzzy-ANP评估洪水灾害风险与房地产价格相关性的改进洪水敏感性模型

这项研究提出了一个综合的地理信息系统（GIS）模糊多准则决策（F-MCDM）模型，以评估洪水对住宅房地产价格的影响。实施了三角模糊数以解决常规分析网络过程（ANP）洪水模型标准排名中固有的局限性，例如不确定性，偏差和模糊性，从而提高了敏感性模型的准确性和可靠性。使用已开发的Fuzzy-ANP（F-ANP）的成对比较技术，根据专家的输入对九种洪水条件的相对重要性进行排名。利用GIS和远程监测马来西亚常年遭受洪水的吉兰丹州的遥感数据和技术，生成并汇总了基于FANP的标准图，以绘制该地区的洪水敏感性图，显示不同位置的洪水脆弱性级别。对马来西亚国家房地产信息中心（NAPIC）的十年房地产价格进行了分析，以调查空间F-ANP模型突出显示的高洪灾区中住宅物业的市场价格趋势。模型验证结果表明，过去洪水事件的59.42％和36.23％分别位于磁化率图的极高和极易感位置，这证实了其准确性。在高度敏感的洪水类别和住房位置与市场价格之间还存在弱的正相关性。我们得出的结论是，集合GIS-FANP洪水敏感性模型可以生成能够向广泛的涉众传达准确的风险信息的地图，从而有助于决策。