Land evaluation plays an important role in land use planning. It provides critical information to support land use allocation. Land evaluation for sustainable land use must take into account several considerations including natural conditions, economic, social and environmental conditions. Therefore, sustainable land use evaluation is a multi-criteria decision analysis (MCDA).
MCDA implies techniques used to analyse a set of criteria providing decision makers with the priorities, or weights, of these criteria (Zopounidis and Pardalos, 2010). Many studies in this area have used the analytic hierarchy process technique, referred to as the AHP of Saaty (1980), to determine weights of criteria (Lu et al., 2007).
In the field of land evaluation, where decisions should be based on inputs from a group of experts coming from very different backgrounds (such as agronomists, economists), quite a number of studies applied AHP allowing individual decision making to determine the weights of considered criteria. The results of such studies are therefore quite subjective (Thapa and Murayama, 2008; Chen, Yu and Khan, 2010). To facilitate the involvement of experts from different backgrounds in land use evaluation process and reducing individual’s subjectivity, the AHP-group method (Lu et al., 2007), i.e. AHP in group decision making shall be utilised in this study.
The original AHP technique implicitly assumes a crisp environment where experts could assign exact numbers aij = 1/aji ๏ [1/9,1] ๏ [1,9] when comparing the relative importance of each pair of indicators (i, j). However, experts’ assessments have always involved certain ambiguity and uncertainty; consequently the evaluation results could not be accurate enough for decision making (Chen et al., 2011). To overcome the limitations of the original crisp AHP, this study proposes a combination of two techniques the AHP-group and the fuzzy logic to create a Fuzzy AHP-Group (FAHPG). This combined technique is used to assess the priority of different criteria, enabling more accurate capture of information generated during a multi-criteria decision analysis process.
This study therefore proposes an integration of the GIS and the FAHPG to create a new model for handling spatial MCDA/MCDM problems, particularly, the land use suitability analysis.
