Objective 3: To develop a least cost pathway (LCP) model to identify the least cost route to the UAV launch port
A least cost pathway analysis was used to identify the least cost route to the site determined from the MCE model from Thunder Bay for transportation of goods for the UAV launch port. Least-cost pathway analysis works to determine the easiest method (least-cost) of moving from a given point to another utilizing distance from the point combined with additional determined costs. It combines numerical values tied to spatial data using weights so that the surface of a specified study site can be represented with values that indicate the expected cost required to cross an area (Bell et al., 2002; Newhard et al., 2008). This will consider the variables of land cover, slope, rivers, and roads. For much of the criteria, the constraint maps created for the MCE step can be used with an inverted scale where "each cell representing the low suitability had the highest friction for road routing" (Mahini & Abedian, 2014). Constraint criteria given a value of 0 as an exclusion zone in the MCE are assgined the maximum value of 7637 derived by determining the amount of cells in the diagonal of the map extent. This makes exclusion zones act as absolute barriers in the least-cost pathway analysis. Similarly, through this method, those evaluation criteria ranked highly for suitability have a low cost to traverse. Next, the friction maps were combined to create an accumulated cost surface upon which, in ArcGIS, first a cost distance function is performed to determine costs accumating away from a source input and a backlink raster that defines the next cell on the least accumlative cost path (ESRI, 2016). From here, these outputs were inputed into the least-cost pathway algorithm performed within ArcGIS to determine the least cost pathway to the UAV launch site from Thunder Bay (Mahini & Abedian, 2014).