Modelling the Terrain for Cross-Country Trafficability With Fuzzy Analytical Hierarchical Process in North-West Ethiopia

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Addis Ababa University


Cross-country movement is the art of predicting trafficability in off-road terrain. This is done by taking into consideration all factors that have a substantial impact on a vehicle‘s ability to cross various terrain, objects and obstructions of weather. A problem with CCM is that many of these factors take time to measure and map, because due to weather conditions and geological factors, they change over time. Criteria judgments also come with ambiguities and vagueness. This makes fuzzy logic a more natural approach to this kind of Multi-criteria Decision Analysis (MCDA) problems. Fifteen criteria were adopted in this method including slope, precipitation, soil type, stem diameter, soil texture, temperature, tree density, soil depth, elevation, road network, drainage, urban area, soil drainage, canopy height and land-use and land-cover. Results showed that there was no strong spatial correspondence between the outputs from the Boolean and Fuzzy methods with a spatial correlation of 0.57. Besides, a zonal cross tabulation of the two methods were strongly concurrence to each other in the GO and NO GO trafficability classes with 99.8% and 79.2% summarized in the same zone respectively. However, results of comparison also showed that there was a significant disagreement between the two methods in the VERY SLOW GO and SLOW GO classes with only 30.9% and 22.4% summarized in the same zone respectively. In the case study developed, the influence of the slope data layer, which was one of the fifteen factors used in this study. Literature shows that the incorporation of fuzzy logic to multi-criteria Analysis can improve the results in suitability analysis hence the study to explore these capabilities in the present study area. In conclusion, even though AHP is widely used in the decision analysis, it is not capable of modeling the uncertainties inherent in the criteria and the confidence of the decision maker. Fuzzy AHP is seen to perform better as it incorporates the techniques of AHP, fuzzy numbers and fuzzy extent analysis functions which are able to model the uncertainties inherent in the criteria and confidence of the decision maker since the process of decision making involves a range of criteria and a good amount of expert knowledge and judgments which in turn affect the outcome greatly.



Fuzzy Ahp, Weighted Linear Combination, Factor Weights, Cost Path Function, Routing