Suchergebnisse

Forest management planning is increasingly relying on airborne laser scanning (ALS) in forest inventory. The area-based method to interpret ALS data requires sample plots measured in the field. The aim of this study was to assess and trace the impacts of the positioning errors of field plots along the entire forest management planning process, from their effect on forest inventory results to the outcome of forest management planning. This research links plot positioning errors with the spatio-temporal allocation of forest treatments and calculates the inoptimality losses arising from plot positioning errors in ALS-based forest inventory. The study area was a forest management unit in Central Spain. Growing stock attributes were predicted for a grid of square-shaped cells. Alternative management schedules were simulated for the grid cells by using growth and yield models. Then, a spatial forest planning problem aiming at maximizing timber production with even-flow cuttings was formulated. Spatial objective variables were used to cluster management prescriptions into dynamic treatment units. We used simulated annealing to conduct spatial optimization. First, the true plot locations were used and then the whole process was repeated with normally distributed random errors with standard deviation equal to 2.5, 5 and 10 m, resulting in an average error of 1.47, 3.06 and 8.34 m, respectively. Increasing the level of positioning errors resulted in higher variability in the estimated growing stock attributes and in the achieved values of management goals. Sub-optimal prescriptions caused by the tested plot positioning errors caused up to 4.62% losses in timber production and up to 3.35% losses in utility. The losses increased with increasing plot positioning error. ; This research was funded by the University of Eastern Finland, School of Forest Sciences and research consortium projects FORBIO (proj. 14970) and ADAPT (proj. 14907), funded by the Academy of Finland and led by Heli Peltola, at the School of Forest Sciences, University of Eastern Finland (UEF). Sergio de-Miguel was funded by the European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie (IF-EF No. 655815)

The purpose of this study was to assess the effect of using alternative types of forest inventory units (FIUs) in multi-objective forest planning. The research was carried out in a Mediterranean forest area in central Spain. The study area was divided, alternatively, into pixels (square cells) and segments of two different sizes (small and large), which represented the tested FIU types. Airborne laser scanning data (ALS) and field sample plots were combined using the area-based approach to estimate forest attributes for each FIU. Dynamic treatment units were created using cellular automaton optimization aiming at maximizing timber production during a 60-year plan with periodical even-flow cuttings both with and without the aim of creating aggregated harvest blocks. The hypothesis was that the use of segments would enhance the clustering of harvests, as compared to cells, and provide dynamic treatment units more suitable for forestry practice. The results showed that segment-based planning created compact harvest blocks even without the use of spatial objective variables in optimization. The spatial layout of the solution for large segments was the most efficient in the absence of spatial objective variables. The FIU type that performed the best in maximizing timber production was the small segments. For the three tested FIU types, the inclusion of spatial objective variables further improved the clustering of harvests, especially during the latter half of the 60-year planning period. Segmentation acted as a first-phase clustering that made spatial optimization easier and faster. In the case of square cells, the clustering of harvests was greatly improved by the inclusion of spatial goals. The forest planning system and the spatial optimization method proposed in this study maximize the utility of fine-grained ALS data. ; Open access funding provided by University of Eastern Finland (UEF) including Kuopio University Hospital. This research was supported by the University of Eastern Finland, School of Forest Sciences and research consortium projects FORBIO (Proj. 14970) and ADAPT (Proj. 14907), funded by the Academy of Finland and led by Prof. Heli Peltola, at the School of Forest Sciences, University of Eastern Finland (UEF). Sergio de-Miguel was supported by the European Union's Horizon 2020 MultiFUNGtionality Marie Sklodowska-Curie (IF-EF No 655815).

Aim of study: To analyze the influence of harvesting costs on the distribution and type of cuttings when forest management planning is based on the dynamic treatment units (DTUs) approach. Area of study: A Mediterranean pine forest in Central Spain. Materials and methods: Airborne laser scanning data were used in area-based approach to predict stand attributes and delineate segments that were used as calculation units. Predicted stand attributes and existing models for diameter distribution and individual-tree growth were used to simulate alternative management schedules for each segment for a 60-year planning horizon divided into three 20-year periods. Three alternative forest planning problems were formulated. They aimed to maximize or minimize net income, or maximize timber production with a constant flow of harvested timber. Spatial goals were used in all cases to enhance the clustering of treatments. Main results: Maxizing timber production without considering harvesting costs can be costly, even close to the plan that minimized net incomes. Maximizing net incomes led to frequent use of final felling instead of thinnings, placing cuttings near forest roads and creating more compact DTUs than obtained in the plan that maximized timber production. Research highlights: Compared to previous studies on DTUs, this study integrated felling and forwarding costs, which depended on distance to road and stand attributes, in the process of creating DTUs by means of spatial optimization. ; University of Eastern Finland; Academy of Finland (projects FORBIO-14970 and ADAPT-14907); European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie (IF-EF No 655815 to SdM).