Purpose of Review: Mechanized logging operations with ground-based equipment commonly represent European production forestry but are well-known to potentially cause soil impacts through various forms of soil disturbances, especially on wet soils with low bearing capacity. In times of changing climate, with shorter periods of frozen soils, heavy rain fall events in spring and autumn and frequent needs for salvage logging, forestry stakeholders face increasingly unfavourable conditions to conduct low-impact operations. Thus, more than ever, planning tools such as trafficability maps are required to ensure efficient forest operations at reduced environmental impact. This paper aims to describe the status quo of existence and implementation of such tools applied in forest operations across Europe. In addition, focus is given to the availability and accessibility of data relevant for such predictions. Recent Findings: A commonly identified method to support the planning and execution of machine-based operations is given by the prediction of areas with low bearing capacity due to wet soil conditions. Both the topographic wetness index (TWI) and the depth-to-water algorithm (DTW) are used to identify wet areas and to produce trafficability maps, based on spatial information. Summary: The required input data is commonly available among governmental institutions and in some countries already further processed to have topography-derived trafficability maps and respective enabling technologies at hand. Particularly the Nordic countries are ahead within this process and currently pave the way to further transfer static trafficability maps into dynamic ones, including additional site-specific information received from detailed forest inventories. Yet, it is hoped that a broader adoption of these information by forest managers throughout Europe will take place to enhance sustainable forest operations.

Using hydrological models with a high temporal resolution to predict risk for rutting may be a possible method to improve planning of forwarder trails or to schedule logging operations in sites with low bearing capacity to periods when soil moisture content is at a minimum. We have studied whether descriptions of rut variations, collected in 27 logging sites, can be improved by using hydrological data, modeled by Swedish HYdrological Prediction for Environment (S-HYPE). Other explanatory variables, such as field-surveyed data and spatial data, were also used to describe rut variations within and across logging sites. The results indicated that inclusion of S-HYPE data led to only marginal improvement in explaining the observed variations of the ruts in terms of both “rut depths” within the logging sites and “proportion of forwarder trails with ruts” across the logging sites. However, application of S-HYPE data for adapting depth-to-water (DTW) maps to temporal changes of soil moisture content may be a way to develop more dynamic soil moisture maps for forestry applications.

Mechanised logging operations can leave negative impacts, like ruts, on forest soils. To avoid this, forestry planners and machine operators need decision support systems that can estimate soil trafficability and help to minimise soil impacts. The main objective of this thesis was to evaluate whether or how different data, stored in a geographic information system (GIS), can contribute to improved estimation of soil trafficability. Requirements for implementation of soil trafficability maps in forestry GIS applications were also described. A soil trafficability map, based on several GIS data using multi-criteria decision analysis (MCDA), was proposed in Paper I. Availability and implementation of soil trafficability maps, mainly depth-to-water (DTW) maps, in some European countries, was reviewed in Paper II. Effect of DTW map resolutions to predict soil moisture was evaluated in Paper IV, and the study showed that a spatial resolution of 1–2 m was sufficient. Risk for rutting was analysed in relation to field-measured and GIS data in Papers III, V and VI. GIS data included digital elevation models, DTW maps, hydrological data, soil type, and clay content maps. The results showed that planning forwarder trails and evaluating different alternatives can be improved by using a soil trafficability map. GIS data of high quality is required to achieve acceptable results. Easy or free access to soil trafficability maps facilitate their application in forestry operations. DTW maps, together with other data, can be used to estimate risk for rutting. Clay content maps and hydrological data, at current resolution, need further development but showed potential to predict risk for rutting. More studies are required to estimate temporal and spatial variability of soil trafficability maps. In conclusion, GIS-based decision support systems should be used for planning of logging operations to minimise risk for rutting.

Soil strength is an important parameter for planning of forest roads and harvesting operations. Locating roads to areas with high soil strength reduce both build and maintenance costs. Locating logging trails to high strength areas minimise soil disturbances, e.g., rutting and compaction of forest soils. GIS-based maps of soil type and soil moisture can be valuable tools to estimate soil strength. The aim of this study was to evaluate the use of soil moisture map, i.e., depth-to-water (DTW), maps and soil type maps, to estimate soil strength expressed as California bearing ratio (CBR). CBR, volumetric water content, and ground penetration depth were measured in 120 sample points, separated on three soil classes (clay-silt sediments, sand sediments, glacial till) and two soil moisture classes (wet, dry). In each point, soil samples were collected for validation of the soil type maps. There was a high conformance between soil moisture predicted by DTW maps and field measurements, but conformance of the soil type between maps and field estimates varied between soil types. For sediment soils, dry soils were consistently stronger than wet soils. Soil strength of glacial till soils was more complicated with a binary CBR distribution depending on soil stoniness. Glacial till soils possible to penetrate to 20 cm depth with the dynamic cone penetrometer had CBR values close to those for sand sediments. There is a potential to estimate soil strength from DTW and soil type maps, but these variables should preferably be complemented with other data.