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dc.contributor.authorRickards, Adam
dc.date.accessioned2020-01-07T20:29:43Z
dc.date.available2020-01-07T20:29:43Z
dc.date.created2019
dc.date.issued2019
dc.identifier.urihttp://knowledgecommons.lakeheadu.ca:7070/handle/2453/4561
dc.description.abstractRoad network modelling has great potential to reduce forest road construction and planning costs. Forest roads are the essential means to access forest resources and are one of the most expensive factors in forest operations. Route optimization models have been used recently to aid in pre-planning of forest road networks. Modern technology is increasing the feasibility of these models. LiDAR data is becoming less expensive and more freely available aiding in the accuracy of road network models. LiDAR has the potential to greatly reduce the costs of forest roads through selection of optimal route locations. LiDAR will also reduce the manual planning and design of forest roads further reducing costs. The objective of this study is to model forest road locations. Model parameters calculate distance and slope as the factors in selecting locations. The study tested the same areas with three data types 50 m2 cell resolution DEM, 5 m2 cell resolution DEM, and 2 point per metre LiDAR. The test cases in this study found that using LiDAR data gave the best location. Overall there is potential using these data and models to assist in the pre-planning of forest roads.en_US
dc.language.isoen_USen_US
dc.subjectRoad network modellingen_US
dc.subjectForest roadsen_US
dc.subjectLiDARen_US
dc.subjectArcGISen_US
dc.titleForest road location modelling with Dijkstra’s shortest path and ArcGISen_US
dc.typeThesisen_US
etd.degree.nameHonours Bachelor of Science in Forestryen_US
etd.degree.levelBacheloren_US
etd.degree.disciplineNatural Resources Managementen_US
etd.degree.grantorLakehead Universityen_US


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