Calculating Least-Cost Pathways in QGIS

In conservation and crime prevention, knowing where something happens is only half the story. The harder question is how people get there. Least-Cost Pathway (LCP) analysis helps answer that.

At its core, LCP modelling identifies the routes that minimise effort, risk, or resistance between two points. In wildlife-crime work, those “costs” can be physical—steep slopes, dense vegetation, rivers—or human, such as proximity to patrol bases or roads where detection risk increases. The model doesn’t tell us where a snare will be set or a hunter will walk, but it highlights the paths they may be most likely to use given the landscape and their objectives.

When combined with terrain and vegetation data, LCP analysis allows us to move beyond dots on a map. Instead of treating each incident in isolation, we can visualise the corridors of movement that connect them: the routes that link poachers to entry points, to water sources, to snaring zones, and back to villages or markets. These routes often follow subtle patterns invisible in patrol data alone.

For law enforcement and field managers, this kind of analysis can guide patrol planning, identify natural chokepoints for detection, and expose overlooked access routes where risk is highest but coverage is low. It also helps test assumptions—revealing whether existing patrol tracks actually align with likely movement paths or miss them entirely.

In this section, I’ll show how least-cost models can be built from the simple spatial layers of slope and vegetation, and how they can be interpreted in practice. The aim isn’t to make the perfect model, but to show how mapping how people move through space can turn static data into actionable intelligence.