  Cost Surfaces are a quantitative means of assigning social, environmental,
and engineering costs that impact movement across landscapes. Cost surfaces are
a crucial aspect of route optimization and least cost path (LCP) calculations
and are used in a wide range of disciplines including computer science,
landscape ecology, and energy infrastructure modeling. Linear features present
a key weakness to traditional routing calculations along costs surfaces because
they cannot identify whether moving from a cell to its adjacent neighbors
constitutes crossing a linear barrier (increased cost) or following a corridor
(reduced cost). Following and avoiding linear features can drastically change
predicted routes. In this paper, we introduce an approach to address this
"adjacency" issue using a search kernel that identifies these critical barriers
and corridors. We have built this approach into a new Java-based open-source
software package called CostMAP (cost surface multi-layer aggregation program),
which calculates cost surfaces and cost networks using the search kernel.
CostMAP not only includes the new adjacency capability, it is also a versatile
multi-platform package that allows users to input multiple GIS data layers and
to set weights and rules for developing a weighted-cost network. We compare
CostMAP performance with traditional cost surface approaches and show
significant performance gains, both following corridors and avoiding barriers,
using examples in a movement ecology framework and pipeline routing for carbon
capture, and storage (CCS). We also demonstrate that the new software can
straightforwardly calculate cost surfaces on a national scale.
