CostMAP: An open-source software package for developing cost surfaces

Authors: Brendan Hoover*, University of Texas, Austin and Los Alamos National Laboratory , Sean Yaw, Montana State University , Richard Middleton, Los Alamos National Laboratory
Topics: Geographic Information Science and Systems, Quantitative Methods
Keywords: GIS, cost surfaces, movement ecology, carbon capture, and storage, Baird’s Tapir
Session Type: Paper
Day: 4/5/2019
Start / End Time: 5:00 PM / 6:40 PM
Room: Roosevelt 0, Marriott, Exhibition Level
Presentation File: No File Uploaded


Cost values are a crucial aspect of least cost path (LCP) calculations in a wide range of disciplines including computer science, landscape ecology, and energy infrastructure modeling. In particular, cost surfaces are used for routing problems such as pipelines and transmission lines, roads, communications systems, and animal movement analysis. A fundamental weakness for routing with cost surfaces arises when incorporating weighted linear features as barriers (such as rivers) or corridors (such as existing rights of way). Cost surfaces typically take the form of raster grids, where movement is limited to adjacent cells of the same resolution. Consequently, cost surface calculations usually weigh linear features as present or absent and cannot identify whether moving from one cell to another is crossing a linear barrier (increased cost) or following a linear corridor (reduced cost). In addition to impacting cost, following and avoiding linear features can and does entirely change predicted routes. We introduce an approach to address this adjacency issue using a search kernel that identifies these critical barriers and corridors. We also present a Java-based open-source software package called the CostMAP (cost surface multilayer-aggregation program), which calculates cost surfaces and cost networks using the search kernel. CostMAP is 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 using examples in a movement ecology framework and pipeline routing for carbon capture, and storage.

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