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Research article - Peer-reviewed, 2022

Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry

Hoffmann, Stephan; Schoenauer, Marian; Heppelmann, Joachim; Asikainen, Antti; Cacot, Emmanuel; Eberhard, Benno; Hasenauer, Hubert; Ivanovs, Janis; Jaeger, Dirk; Lazdins, Andis; Mohtashami, Sima; Moskalik, Tadeusz; Nordfjell, Tomas; Sterenczak, Krzysztof; Talbot, Bruce; Uusitalo, Jori; Vuillermoz, Morgan; Astrup, Rasmus


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.


Depth-to-water; Remote sensing; Digital terrain models; European forestry; Precision forestry; Trafficability prediction

Published in

Current Forestry Reports
2022, volume: 8, number: 1, pages: 55-71

Authors' information

Hoffmann, Stephan
Norwegian Institute of Bioeconomy Research
Mohtashami, Sima
Forestry Research Institute of Sweden, Skogforsk
Schoenauer, Marian
University of Gottingen
Heppelmann, Joachim
Norwegian Institute of Bioeconomy Research
Asikainen, Antti
Natural Resources Institute Finland (Luke)
Eberhard, Benno
University of Natural Resources and Life Sciences, Vienna
Hasenauer, Hubert
University of Natural Resources and Life Sciences, Vienna
Ivanovs, Janis
Latvian State Forest Research Institute Silava
Jaeger, Dirk
University of Gottingen
Lazdins, Andis
Latvian State Forest Research Institute Silava
Moskalik, Tadeusz
Warsaw University of Life Sciences
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Sterenczak, Krzysztof
Forest Research Institute
Talbot, Bruce
Stellenbosch University
Uusitalo, Jori
University of Helsinki
Astrup, Rasmus
Norwegian Institute of Bioeconomy Research
Vuillermoz, Morgan
Technological Institute for Forestry, Cellulose, Construction Timber and Furniture (FCBA)
Cacot, Emmanuel

Sustainable Development Goals

SDG13 Climate action
SDG9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation

UKÄ Subject classification

Remote Sensing
Forest Science

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