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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. [ABSTRACT FROM AUTHOR]

This study presents a novel integrated decision model for optimal planning oil palm value chains (OPVC) incorporating decisions to minimise biodiversity losses by limiting the expansion of oil palm plantations as needed and generate value from its waste products. The model can answer the following types of question: What is the best way to deploy OPVC in terms of both economic and environmental factors wherein objectives are integrated systematically by experts? How can the demands for palm oil and palm-based materials and energy products be satisfied with and without considering additional land for plantation? Which conversion technologies will be needed, when and where should these be deployed? How can the resources be managed subject to utilisation, production, import, export and transportation constraints? The planning model developed involves two components: (1) a decision framework using fuzzy analytic hierarchy process (FAHP) to incorporate experts' knowledge in planning and design under uncertainty and (2) a mixed integer linear program (MILP) to determine the optimal expert-based OPVC design. The framework was applied to different scenarios for the Malaysian palm oil industry. Results show that the demand for crude palm oil (CPO) in Malaysia can be fully satisfied while the international demand can be satisfied by about 60% in 2050. However, in order to minimise environmental impacts and risks of biodiversity losses, the contribution of Malaysia towards satisfying global demand for palm oil should be kept to a minimum. Moreover, the current plantations can satisfy future CPO demand after 5 to 10 years, after which best practices to improve palm oil yield and alternatives comparable to palm oil will be needed. The framework can potentially contribute to the development of better policies in the future through the proposed systematic approach in dealing with sustainability issues in the palm oil industry. [ABSTRACT FROM AUTHOR]

This paper aims to determine the suitable places for a radioactive waste repository in Peninsular Malaysia to implement a permanent disposal facility for disposal sealed radioactive sources (DSRS). The sole Malaysia interim waste storage that stores a large proportion of DSRS was expected to be occupied by 2025 fully. Currently, the nation's licensing board promoted the borehole disposal facility to resolve the full capacity dilemma. The potential sites were determined by the geographical information system (GIS) based Weight Linear Combination (WLC) analysis, integrating the improved Analysis Hierarchical Process (improved AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) approaches. The sensitivity analysis was applied to identify the main contributing factors for corresponding Peninsular Malaysia selection. Ten parametric criteria and three exclusion criteria are applied to assess the potential areas and screen out the unfavorable regions, respectively. Results indicated the final composite map presents 435 areas of very high suitability class with 17.5% coverage from the total suitability class. The top 5 largest candidates with high potentiality are Jerantut & Ulu Lepar, Bandar Tun Razak, Pertang & Simpang, Pertang, Tanjung Ipoh, and Labis, where come from three provinces: Pahang, Negeri Sembilan and Johor. By TOPSIS model, the ranks for these five candidates are Jerantut & Ulu Lepar, Bandar Tun Razak, Tanjung Ipoh, Labis and Simpang Pertang. The model revealed that the suitability ranks is proportional to its area sizes in the approximate values of criteria. The three main contributing factors in Peninsular Malaysia are hydrogeology, seismicity and lithology, which are strongly recommended to involve in other corresponding site selection project. • Top five candidates for radioactive waste disposal site in Malaysia are Jerantut & Ulu Lepar, Bandar Tun Razak, Tanjung Ipoh, Labis and Simpang Pertang. • Three main contributing factors for site selection in Malaysia are hydrogeology, seismicity and lithology. • The suitability index rank is proportional to the area sizes in the consideration of area factor. [ABSTRACT FROM AUTHOR]

Abstract: A systematic approach was used to develop an integrated plan to determine the optimal land use suitability for future sustainable development in the coastal area of the Kuala Langat District, Selangor, Malaysia based on different planning scenarios. Use of the multi criteria evaluation (MCE) especially Analytic Network Process (ANP) allowed for the integration of expert opinion on social, economic and environmental criteria within the planning framework and provided an efficient spatial approach for coastal land use development. Scenario analysis resulted in a series of suitability maps for conservation, tourism, residential and industrial development. Three scenarios addressing economic and social development, environmental conservation and sustainable development were defined and evaluated. Four land uses were considered: namely, residential, conservation, tourism and industry. By evaluating various scenarios, existing plans and guidelines, land availability and current uses, the optimum suitability for coastal land uses towards sustainable development was proposed. However, only one optimal land suitability map was proposed for the sustainable development scenario. The spatial scenario planning framework developed in this research is an example of an effective, integrated decision-making framework. The methodology is brief, a set of guidelines and recommendations is included for organising, and expressing the complexities found in oastal area. To date, there is no published application of an ANP in spatial planning for coastal land uses or for related fields. It is hoped that this approach can be employed for land use suitability assessments at both the local and the structure-plan level. [Copyright &y& Elsevier]

λ 0 -measure is a special type of fuzzy measure. In the context of multi-attribute decision making (MADM), the measure can be used together with Choquet integral to model the interdependencies that usually present between the decision attributes. Unfortunately, the range of techniques available to estimate λ 0 -measure values is too limited i.e., only four techniques are available to this date. Besides, the review on literature shows that each of these existing techniques either requires some initial data from the decision-makers or misrepresents the actual interdependencies held by the attributes. Thus, an alternate unsupervised technique is needed for the estimation of λ 0 -measure values. This study has developed such a technique by integrating the idea of distance correlation and Shannon entropy. In this technique, the two inputs required to estimate λ 0 -measure values, namely, the interdependence degrees and fuzzy densities are determined by utilizing the distance correlation measures and entropy weights, respectively. An evaluation to rank the websites owned by five different hospitals located in Sabah, Malaysia, was conducted to illustrate the usage of the technique. A similar evaluation was also performed with a few selected MADM techniques for comparison purposes, where the proposed technique is found to have produced the most consistent ranking. From the literature perspective, this study has contributed an alternate unsupervised technique that can estimate λ 0 -measure values without necessitating any additional data from the decision-makers, and at the same time can better capture the interdependencies held by the attributes. [ABSTRACT FROM AUTHOR]

Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts' opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control. [ABSTRACT FROM AUTHOR]