A conceptual model for defining and assessing land management units using a fuzzy modeling approach in GIS environment.
Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A submodel of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.
Baja
Sumbangan
S
Division of Geography, School of Geosciences, University of Sydney, NSW 2006, Australia. sbaja@mail.usyd.edu.au
Chapman
David M
DM
Dragovich
Deirdre
D
D003247:Conservation of Natural Resources; D003657:Decision Making; D004777:Environment; D004784:Environmental Monitoring; D017143:Fuzzy Logic; D040362:Geographic Information Systems; D008962:Models, Theoretical