Landscapes can be simplified into two-dimensional raster surface representations, where each cell is coded with a number that represents some combination of land cover and site conditions present at that location. Mobile species will interact with the landscape, traversing across it, utilizing resources, and taking shelter depending on those conditions and thus the cell attributes can be converted into values of relative friction, producing a surface that characterizes the ease of mobility, likelihood of use, or the likelihood of some other spatial process being executed at each cell within a landscape. Our experiment relies on 1000s of simulated landscapes, presented as friction surfaces, produced using replicates with randomization to cover the full spectrum of composition and configuration parameterizations. Then, a least-cost path process is performed for every possible pair of edge-located starting and ending points for a landscape transit and the path and summary metrics for each are recorded. All possible paths are then overlain to identify the relative utilization of each cell within a landscape. Locations with high utilization are termed pinch-points, as paths will converge to pass through specific cell locations. We assess the density and distribution of these pinch-points at different spatial scales and then test their correlation with underlying hyper-local configurational elements of the landscape to assess the scale and structure combinations that lead to both pinch-points and under-utilized areas. We intend to illustrate and quantify the influence that landscape configuration has on landscape utilization and dynamic processes.