Rockshare estimation in forest road excavation using the Ordinal Logistic Regression (OLR) and the Analytical Hierarchy Process (AHP)

The rock proportion of the subsoil directly influences on the cost of embankment in forest road construction. Therefore, developing a reliable framework for rock ratio estimation prior the road planning may lead to more light excavation and less cost operation. According to the ordinal nature of hardness classes of the soil in executive branches, the purpose of present research is to model the ratio of rocks in the subsoil as a function of terrain slope and geology information using Ordinal Logistic Regression Model. To do so, first, the geological units were weighted using the Analytical Hierarchy Process (AHP). The obtained priorities and terrain slope data were feed to the model. To evaluate effects of change in link functions, five types of link functions were adapted. The results showed that the Probit function gives the best determination coefficient and parallel lines test for our model. To show the applicability of the proposed approach, the optimum model was applied to a mountainous forest in where additional forest road network should be constructed in the next periods