A fuzzy-based tool for spatial reasoning: A Case study on soil erosion hazard prediction

Zuhal Akyurek 1 and Kıvanç Okalp 2
1 METU Civil Eng. Dept. 
06531 Ankara, Turkey
Tel.: + 90 312 2102481; Fax: + 90 312 210 7956
2 METU Geodetic and Geographic Information Technologies, Institute of Natural and Applied Sciences 
06531 Ankara , Turkey

Fuzzy set theory provides a formal system for representing and reasoning with uncertain information. Linguistic variable concept in a  fuzzy logic system enables to handle numerical data and linguistic knowledge simultaneously. Even L. A. Zadeh (1965), formulated the initial statement of fuzzy set theory, at first never expected fuzzy sets to be used in consumer products or in geographic information. A collection of objects of any kind form a classical set and the objects themselves are called elements or members of the set. Since classical set theory is used in conventional decision making systems to model uncertain real world, the natural variability in the environmental phenomena can not be modeled appropriately.  Because, pervasive imprecision of the real world  is unavoidably reduced to artificially precise spatial entities when the conventional crisp logic is used for modeling. In this study fuzzy sets and fuzzy logic algebra were used in predicting the soil erosion hazard. Annual soil loss rates were estimated using Universal Soil Loss Equation (USLE) that has been used for five decades all over the world. Fuzzification of the landscape elements used in the model was done using a Fuzzy Semantic Import modeling approach. FuzzyCell, which has been developed on a commercial GIS software namely, Arc-Map, was used to  implement the fuzzy algebra operators for determining the likelihood an area to low, moderate or high erosion hazard. The results were compared with the traditional USLE model results. When the results obtained from the traditional and fuzzified USLE implementation, it is observed that traditional USLE overestimates the areas prone to low level erosion risks and it overestimates the areas prone to high level erosion risk. Although the model provides qualitative estimations, it showed very useful to explore relationships and incorporate uncertainty in spatial decision making.

Keywords: fuzzy logic, spatial reasoning, uncertainty, soil erosion, USLE

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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