LiDAR-Based Wet Areas Mapping in the Oil Sands

Devon partnered with the University of New Brunswick to refine and apply a LiDAR-based Wet Areas Mapping (WAM) tool in northeastern Alberta’s flat, wet boreal landscape. Originally developed for forestry applications, the tool was adapted to support oil sands facility and access road planning while minimizing hydrological impacts. The project assessed culvert placement, LiDAR-derived tree height, soil and vegetation indices, wetland connectivity, and the overall value of WAM. This work aimed to improve land-use decisions by accurately identifying flow channels, wet areas, and depth-to-water (DTW) conditions at high spatial resolution.

The WAM tool effectively maps hydrologically sensitive areas and supports “surprise-free” planning for industrial and reclamation activities. LiDAR-derived cartographic depth-to-water (DTW) models outperformed traditional soil wetness indices in predicting soil moisture and wetland connectivity. DTW was strongly correlated with vegetation type, soil drainage, and chemical properties, enabling high-resolution mapping of ecological gradients. These findings confirm the tool’s value for environmental planning, precision land management, and hydrologic modeling in boreal landscapes.