Terrain mobility estimation using TWI and airborne gamma-ray data

Since one purpose of forestry laws and certification standards is to guide loggers to minimize the damage caused by forest operations, information regarding internal variations in site trafficability is needed for both economic and ecological reasons. The aim of this work was to test the prediction of terrain mobility from open data sources in Finland. New Lidar-based data sources were available for calculating terrain features and a gamma-ray-based soil wetness parameter. Rut depths were measured and can bus data were collected from a forwarder in two logging areas. Net power at the forwarder's drive shaft, total resistance and rolling resistance were calculated from the can bus data and augmented by means of a digital elevation model (DEM), soil data, aerogeophysical gamma-ray radiation data and a topographic wetness index (TWI). The rut depth was explained best either by TWI calculated from a 2 m grid DEM or the combination of a 16 m grid TWI, gamma radiation from thorium and engine net power (r² = 0.20-0.33). In the areas concerned here the gamma-ray results may have detected the soil type more precisely than the soil type class, and the gamma radiation from thorium may also have detected wet places inside the site type, labelled as sandy till, and will therefore have explained the variation in rut depth.