|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|93247||160118||2013||11 صفحه PDF||سفارش دهید||دانلود رایگان|
Selection of rural buildings’ site is a complex process to solve a discordant relation with other components of rural landscapes and needs many diverse criteria to deal with its situation. This paper presents a multi-criteria spatial decision analysis approach using geographic information system (GIS) technique for evaluating the suitability of rural buildings site selection with a case study in Hervás (northern Extremadura region), Spain. The aim of the methodology is to evaluate the suitability of the study region in order to optimally site a new single dispersed tourism-related commercial building with landscapes. The analytical hierarchy process (AHP) is used to generate the alternative decisions using the multi-criteria evaluation techniques standardised by fuzzy membership functions. The parameters are categorised into three criteria groups, namely physical, environmental and economic criteria and then the weights are verified by a group discussion with the experts for final weight consensus making them more objective. With the aid of the simple additive weighting (SAW) method, the calculation of final grading values in multiple criteria problem is evaluated for the study region. The resulting land suitability is reported on a grading scale of 0–10, which is, respectively, from least to most suitable areas. Combination of a spatial clustering process reveals the most suitable areas for rural buildings siting with their landscapes. The proposed methodology is intended to solve the rural building integration problem with its landscape and to facilitate the flexible methodology implementation from decision alternatives involved in the decision making process.
► We propose a rural building siting model for integrating its current environment.
► We characterise multi-criteria evaluation methods from different decision problems.
► We apply a comparative analysis of AHP and SAW clustering procedures.
► Results showing the methods in this research are an efficient and flexible approach.
► The methods can extend and yield different decision alternatives.
Journal: Land Use Policy - Volume 32, May 2013, Pages 108–118