By Jurg Andreas Stuckelberger
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Additional info for A Weighted-graph Optimization Approach for Automatic Location of Forest Road Networks
Both eﬀects resulted in a lot of switchbacks and therefore high life-cycle cost. Scenarios II and III shows nearly identical road routes in 000-BRH-SBU-AU and EGS-ROW-TAS. However, Scenario II connects the high level via access points AU-SBU-STO in less stable subsoil where as Scenario III made a connection via AU-OBO-ALP-STO in limestone layer, which is stable and therefore favorable. 5 contains key data for the scenarios. Again, Scenario I depicted current modeling practices, which assumed route-independent costs.
Nonetheless, our validation also revealed some uncertainty that requires further investigation. A ﬁrst problem consists of stream crossings for which we implemented only the ford-case. In some sites bridges may be more appropriate. A second problem is the road location near sharp terrain edges and small channels for which a 10 m × 10 m grid resolution is inappropriate to map these small-scale terrain features. Finally protective structures against natural hazards (rock fall, mudﬂow, avalanches) which result in additional cost, is a third problem to be investigated for extreme area conditions.
Such direct estimations rely more or less on data from past projects or programs, with readily available data. This approach has historically been dominant in preliminary road-network planning, serving as the basis for software packages such as PLANEX or NETWORK 2001. The second approach, using estimating relationships and formulae, calculates the cost of either individual components or the entire system, and is based on cost-driving technical parameters. Markow & Aw (1983) have identiﬁed relationships to predict the volume of earthwork needed, as well as the numbers of culverts and bridges per unit length.