Abstract

Abstract Abstract Land suitability evaluation in a raster GIS environment is conceptualized as a multiple-criteria decision-making (MCDM) problem. A combination of MCDM techniques selected for implementing the methodology included value and priority assessment techniques for scaling the interval and ordinal data respectively, and compromise programming (CP) to aggregate the unidimensional evaluations. The contribution of the proposed methodology to handle problems of scaling and dependence that often affect expert-based suitability analyses is discussed. A case-study of habitat evaluation for the endangered Mount Graham red squirrel is presented. The multiple-criteria models resulting from the CP analysis of an expert's perception of the habitat preference structure of the red squirrel are compared with data of actual habitat use. The predictive power of the models is good and sensitivity analysis based on the distance-metric parameter p of CP reveals some interesting differences between alternative strategies for data aggregation.