A Topographic Wetness Index for Forest Road Quality Assessment: An Application in the Lakeland Region of Finland

Abstract

Research Highlights: A Topographic Wetness Index calculated using LiDAR-derived elevation models can help in identifying unpaved forest roads that need maintenance. Materials and Methods: Low-pulse LiDAR data were used to calculate a Topographic Wetness Index to predict unpaved forest roads’ quality. Results: The results of this analysis and comparison of road-quality features derived from LiDAR data at resolutions of 1, 10 and 25 m for assessing road quality in the boreal forests of Finnish Lakeland show that the wetness index can predict road quality correctly in up to 70% of cases and up to 86% when combined with other auxiliary GIS-based variables. Conclusions: Road-quality assessments, using airborne LiDAR data, can greatly help forest managers to decide which sections of the ageing road network will benefit the most from maintenance, while reducing the need of field visits.