Open access publications in the SLU publication database

Abstract

Reliable and accurate soil moisture maps are needed to minimise the risk of soil disturbance during logging operations. Depth-to-water (DTW) maps extracted from digital elevation models have shown potential for identifying water flow paths and associated wet and moist areas, based on surface topography. We have examined whether DEMs from airborne LiDAR data with varying point density can improve performance of DTW maps in planning logging operations. Soil moisture content was estimated on eight sites after logging operations and compared to DTW maps created from DEMs with resolutions of 2 m, 1 m, and 0.5 m. Different threshold values for wet soil (1 m and 1.5 m depth to water) were also tested. The map performances, measured by accuracy (ACC) and Matthews Correlation Coefficient (MCC), changed slightly (79%, 81% and 82% and 0.33, 0.26 and 0.30 respectively) when DEM resolutions varied from 2 m to 1 m, and 0.5 m. The corresponding values when the DTW threshold value for wet/dry soil changed from 1 m to 1.5 m were 70%, 72%, 71% and 0.38, 0.41 and 0.39. LiDAR-based DEM resolutions of 1–2 m were found to be sufficient for extraction of DTW maps during planning of logging operations, when knowledge about soil hydrological features, associated wet and moist areas, and their connectivity is beneficial.