An assessment on the off-road trafficability using a quantitative rule method with geographical and geological data

COMPUTERS & GEOSCIENCES(2023)

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摘要
The assessment of off-road trafficability is an important issue in special military or disaster relief operations. It is affected by geographical and geological environmental factors, and the factor sensitivity changes with space. Previous research used a qualitative manual rule method and geographical factors to assess off-road trafficability in terms of land coverage and terrain factors. However, this caused problems because the factors were not comprehensive, the method was qualitative, and there was a great deal of noise in the assessment results. To solve these problems, we developed a quantitative rule method to comprehensively assess the obstacles caused by geographical and geological factors to off-road trafficability. First, we reviewed remote sensing images of various factors in the study area, searched for traffic rules, and quantified them using the analytic hierarchy process-weighted information content (AHP-WIC) method. Then, the corresponding relationship between rules and off-road trafficability is established by the clustering method, and it is divided into multiple types of motion (generally>2 types). Finally, we used the improved watershed method to filter off-road trafficability map noise. The results showed that the geological environment (including geological hazards, joint & structure, topographic position index, rock structure, etc.) can seriously hinder off-road trafficability but has not been considered in previous research. For complex field environments, the proposed method can adaptively establish the classification relationship between rules and off-road trafficability. Additionally, the improved watershed method can effectively filter the noise generated by the rule method.
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关键词
Off-road trafficability,Quantitative rule,Analytic hierarchy process-weighted information content (AHP-WIC) method,Improved-watershed filtering,Geographical and geological data
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