A method for incorporating the within‐stand variation into forest management planning

Pukkala, Timo

doi:10.1080/02827589009382611

Cited by 14 publications

(10 citation statements)

References 6 publications

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“…The reason behind this effect is the concave relationship between stand density and tree growth, and the non-linear relationship between tree size and growth. As a consequence of these relationships, the volume growth of a heterogeneous stand is smaller than that of a homogeneous stand (Pukkala 1990). When segments are used in planning they are assumed to be homogeneous and described with only one set of stand variables.…”

Section: Discussionmentioning

confidence: 99%

“…Using ALS raster data in forest planning 1589 already long time ago. For example, Pukkala (1990) noted that growth predictions may be smaller when they are based on the individual relascope plots measured in visual compartment inventory, compared to a case where the field data are condensed into a single set of growing stock variables, which is the usual practice in visual compartment inventory. The thinning removal may be larger if thinning is simulated separately for individual field plots.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, the use of large segments omits the within-stand spatial variation in site and growing stock characteristics, which may cause bias. It may be hypothesized that pre-planning aggregation leads to overestimated growth prediction due to the concave relationship between stand density and increment (Pukkala 1990). This may lead to overestimated net present value and wood production.…”

Section: Introductionmentioning

confidence: 99%

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Using ALS raster data in forest planning

Pukkala

2019

J. For. Res.

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Raster type of forest inventory data with site and growing stock variables interpreted for small squareshaped grid cells are increasingly available for forest planning. In Finland, there are two sources of this type of lattice data: the multisource national forest inventory and the inventory that is based on airborne laser scanning (ALS). In both cases, stand variables are interpreted for 16 m 9 16 m cells. Both data sources cover all private forests of Finland and are freely available for forest planning. This study analyzed different ways to use the ALS raster data in forest planning. The analyses were conducted for a grid of 375 9 375 cells (140,625 cells, of which 97,893 were productive forest). The basic alternatives were to use the cells as calculation units throughout the planning process, or aggregate the cells into segments before planning calculations. The use of cells made it necessary to use spatial optimization to aggregate cuttings and other treatments into blocks that were large enough for the practical implementation of the plan. In addition, allowing premature cuttings in a part of the cells was a prerequisite for compact treatment areas. The use of segments led to 5-9% higher growth predictions than calculations based on cells. In addition, the areas of the most common fertility classes were overestimated and the areas of rare site classes were underestimated when segments were used. The shape of the treatment blocks was more irregular in cell-based planning. Using cells as calculation units instead of segments led to 20 times longer computing time of the whole planning process than the use of segments when the number of grid cells was approximately 100,000.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using ALS raster data in forest planning

Pukkala

2019

J. For. Res.

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“…Previous research and theoretical reasoning (Pukkala 1990;Pukkala and Kolström 1991) have shown that increasing within-stand variation in stand density and tree size decreases the volume increment of the stand, compared to homogeneous stands with the same average stand basal area and mean diameter. When the growing stock is described only with the average stand balsa area and mean diameter, it can be expected that growth predictors will be overestimated, the most in the most heterogeneous stands.…”

Section: Complicationsmentioning

confidence: 95%

Delineating forest stands from grid data

Pukkala

2020

For. Ecosyst.

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Background: Forest inventories are increasingly based on airborne laser scanning (ALS). In Finland, the results of these inventories are calculated for small grid cells, 16 m by 16 m in size. Use of grid data in forest planning results in the additional requirement of aggregating management prescriptions into large enough continuous treatment units. This can be done before the planning calculations, using various segmentation techniques, or during the planning calculations, using spatial optimization. Forestry practice usually prefers reasonably permanent segments created before planning. These segments are expected to be homogeneous in terms of site properties, growing stock characteristics and treatments. Recent research has developed methods for partitioning grids of ALS inventory results into segments that are homogeneous in terms of site and growing stock characteristics. The current study extended previous methods so that also the similarity of treatments was considered in the segmentation process. The study also proposed methods to deal with biases that are likely to appear in the results when grid data are aggregated into large segments. Methods: The analyses were conducted for two datasets, one from southern and the other from northern Finland. Cellular automaton (CA) was used to aggregate the grid cells into segments using site characteristics with (1) growing stock attributes interpreted from ALS data, (2) predicted cutting prescriptions and (3) both stand attributes cutting prescriptions. The CA was optimized for each segmentation task. A method based on virtual stands was used to correct systematic errors in variable estimates calculated for segments. Results: The segmentation was rather similar in all cases. The result is not surprising since treatment prescriptions depend on stand attributes. The use of virtual stands decreased biases in growth prediction and in the areas of different fertility classes. Conclusions: Automated stand delineation was not sensitive to the type of variables that were used in the process. Virtual stands are an easy method to decrease systematic errors in calculations.

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“…This component of the approach thus combines random and systematic search components. Pukkala et al (1995), , , Pukkala and Kangas (1996), Kangas (1999) and PykaHiinen (2000) reported research and application results that show that this approach can effectively address multiobjective forest management problems while conveying the geographical location of management options. For example, it has been used in Finland to address interactive planning of private non-industrial forestry; public participation in forest management scheduling; risk and attitude toward risk in forest planning; and biodiversity, recreation and aesthetics considerations in forest management scheduling.…”

Section: Introduction To Heuristic Designmentioning

confidence: 96%

Heuristics in Multi-Objective Forest Management

Borges¹,

Hoganson

Falcão³

2002

Managing Forest Ecosystems

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Abstract. Heuristics have been used extensively to support forest management scheduling in the last two decades. The need for spatial definition, and the combined shortcomings of available technology and traditional mathematical programming approaches, sparked interest in alternative forest management scheduling techniques in the early 1980s. Concerns with the environmental impacts of forest management options further encouraged the development of heuristics to address adjacency relationships in harvesting decisions. More recently, heuristics have been used to target other multi-objective management issues. Namely, they have been used to provide information to help sustain both traditional forest products flows (e.g. timber and cork) and landscape structural characteristics (e.g., mosaic elements such as patch number and size, amounts of edge or interior space). In this chapter, we describe the current state of the art of heuristic application in forest management scheduling. Heuristic approaches are presented and discussed in the framework of forest management scheduling needs. Results from some heuristic research efforts are used to outline the application potential and shortcomings of these techniques.

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A method for incorporating the within‐stand variation into forest management planning

Cited by 14 publications

References 6 publications

Using ALS raster data in forest planning

Using ALS raster data in forest planning

Delineating forest stands from grid data

Heuristics in Multi-Objective Forest Management

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