Paper presented at the 16th European-African Regional Conference of the ISTVS
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Title: Digital precision planning tool for autonomous forest regeneration of mixed tree species
Authors: Erik Arvidsson, Magnus Karlberg, Karin Hjelm, and Håkan Lideskog
Abstract: Forest management planning often neglects within-site variation, focusing on decisions for entire forest stands, which impedes effective forest regeneration. Incorporating mixed species stands can mitigate risks associated with monocultures and offer numerous benefits. However, implementing mixed stands present challenges such as higher costs and complex management. This research aims to develop a method for precise and efficient forest regeneration planning in Swedish silviculture. The study developed digital tools to be used in forest regeneration planning and makes it suitable for deployment on autonomous vehicles. Traditional regeneration methods involving labour-intensive processes and soil disturbance have limitations, while autonomous vehicles show promise in improving energy efficiency and reducing soil damage. The aim is to increase site productivity by determining the spatial distribution of varied species in mixed stands using density constraints set by the user. The Digital Precision Planning Tool (DiPPT) developed in this study utilises existing site index maps to enhance biomass growth and select the most suitable species for each location. The tool considers species-specific site productivity and density constraints to create the planting map. Two approaches were developed: the Max function, which selects the species with the highest site productivity for each location, and an iterative process that optimises species-specific factors to meet user-defined density constraints. The DiPPT was validated using test sites provided by the forest company Sveaskog. Results show that the tool’s approach outperforms manual planning in terms of site productivity. The average site productivity using DiPPT is 10% higher compared to manual planning. The tool demonstrates its potential for optimising species placement and promoting species diversification in forests.
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