Using GIS-based continuous methods for assessing agricultural land-use potential in sloping areas

The dynamic nature of land qualities both in space and in time suggests that, whatever the stages of the development of an area, it is always crucial to assess land qualities in terms of their potential and suitability for specific kinds of land use on a sustainable basis. In this paper we demonstrate an integrated method of biophysical land-suitability assessment, which combines two basic land-evaluation principles: allowing trade-offs among evaluation criteria, and a limiting condition approach. Decision criteria consist mainly of biophysical parameters, based on internal and external groups of land properties. Internal variables include various physical and chemical characteristics of soils, whereas external variables are those of topographic attributes. A fuzzy set methodology was employed to calculate values of a membership function, MF (0 less than or equal to MF less than or equal to 1.0), of each land variable. These fuzzy membership values were then combined to produce land-suitability indices, LSIs (0 less than or equal to LSIs less than or equal to 1.0), which can be used to assess the potential of land for a nominated land-use type. The analysis procedure implements a convex combination, which permits trade-offs between criteria of the same group, and a multiplicative function, which takes no account of compensation between groups (internal and external variables). A limiting condition approach is also incorporated in this system to resolve shortcomings found when using a convex combination technique alone. The results show that LSIs are consistent with categorical classes generated from applying the well-established method based on the Food and Agriculture Organisation framework for land evaluation. However, the LSIs, as derived from a cell-by-cell operation, produce more detailed subdivisions of land in terms of their potential for a given purpose. The main advantages of using this model include: (1) it minimises subjectivity in the evaluation procedure; (2) it takes into account the combined effects of the factors considered, while preserving information on biophysical constraints for a given purpose; and (3) it is amenable to further computer-based applications, especially for use in geographical information systems.