| Summary: | Forest industry corporations use quality management systems in their wood procurement operations. Spatial quality data are used to improve the quality of wood harvesting and to achieve environmental sustainability. Some studies have proposed new management systems based on LiDAR. The main aim of this study was to investigate how efficiently planning systems can select areas for wood harvesting a priori with respect to avoiding harvesting damage caused by forest machinery. A literature review revealed the possibility of using GISs, and case studies showed the criteria required to predict the required quality levels. Terrestrial LiDAR can be utilized in authorities’ quality control systems, but it is inefficient for preplanning without terrestrial gamma-ray data collection. Airborne LiDAR and gamma-ray information about forest soils can only be used for planning larger regions at the forest level because the information includes too much uncertainty to allow it to be used for planning in small-sized areas before wood harvesting operations involving wood procurement. In addition, airborne LiDAR is not accurate enough, even at the forest level, for the planning of wood procurement systems because wood harvesting remains challenging without field measurements. Therefore, there is a need for the use of manual ground-penetrating radar for determining the peat layer thickness and the depth to the groundwater table.
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