An Updated Review of Spatial Forest Planning: Approaches, Techniques, Challenges, and Future Directions

Abstract

Purpose of Review

The spatial forest planning concept has evolved as an essential component of the forest management planning process. The development of both exact and heuristic modeling techniques as analytical solution techniques have seen significant progress in application to spatial forest planning over the last two decades. This paper aims at providing a comprehensive review of the current state of spatial forest planning in both scope and depth, focusing on different approaches and techniques used, the challenges faced, and the potential future developments. For that purpose, we conduct a world-wide literature review and an extensive analysis of the status and trends over the past two decades in spatial forest planning.

Recent Findings

The literature review indicates that recent advancements have led to the development of new algorithms/formulations for addressing spatial constraints in forest planning with exact solution techniques. Nevertheless, it highlights further that heuristic techniques are still widely used, especially in large real-world problems that encompass multiple ecosystem services and constraints. Besides the provisioning services, there has been a noticeable increase in the proportion of regulating, supporting and cultural services addressed in objective functions of forest management planning models. Adjacency/green-up relationships, opening size, core area, wildlife habitat and the spatial arrangement of fuel treatments have been considered as indicators to address the provision of these services and spatial forest problem.

Summary

We pinpoint persistent challenges to using exact modeling techniques to address large real problems with multiple ecosystems services. We highlight further that determining the optimal combination and values of heuristic parameters and assessing the quality of heuristic solutions remains a central challenge. Finally, we highlight the potential of artificial intelligence to overcome computational obstacles to the application of both exact and heuristic techniques to spatially explicit forest management planning.