Integrating Multiple Services in the Numerical Analysis of Landscape Design

Pukkala, Timo

doi:10.1007/978-1-4020-6759-4_6

Cited by 12 publications

(19 citation statements)

References 19 publications

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“…Forest management planning systems linking georeferenced forest stand data, projection models and an LP model are powerful tools allowing decision makers to explore trade-offs between multiple objectives and analyse the economic consequences of alternative developments (Carlsson 1999). Methodologies for multi-objective forest management planning have been developed to support forest owners in decision making, that is, long-term strategic planning at the forest holding level (see Kangas et al 2015;Pukkala 2008;2016). These require spatially explicit information on production possibilities, such as forest attributes, habitats and recreation, at the same scale, traditionally at the forest stand level (Pukkala 2008).…”

Section: Nfi and Forestry Scenario Modellingmentioning

confidence: 99%

“…Methodologies for multi-objective forest management planning have been developed to support forest owners in decision making, that is, long-term strategic planning at the forest holding level (see Kangas et al 2015;Pukkala 2008;2016). These require spatially explicit information on production possibilities, such as forest attributes, habitats and recreation, at the same scale, traditionally at the forest stand level (Pukkala 2008).…”

Section: Nfi and Forestry Scenario Modellingmentioning

confidence: 99%

“…The production of raster maps on forest attributes has been implemented as a part of operational NFIs, for example, in Finland and Sweden (Tomppo et al 1998;2008;Reese et al 2003) and tested in many other countries (e.g. Trotter et al 1997;Franco-Lopez et al 2001;McRoberts at al.…”

Section: Remote Sensing In Forest Inventorymentioning

confidence: 99%

“…2002;Maselli et al 2005;Gjertsen 2007;Koukal et al 2007;Scheuber 2010). In Finland, the Multi-Source National Forest Inventory (MS-NFI) system based on satellite imagery (see Tomppo et al 2008) provides raster maps of different forest attributes and forest statistics for municipalities every other year (Tomppo et al 1998;2008;2014a;Mäkisara et al 2016). In Sweden raster maps are produced approximately every fifth year (Fridman et al 2014).…”

Section: Remote Sensing In Forest Inventorymentioning

confidence: 99%

“…Tomppo et al 1998;2008;. The method has been continuously developed, and new features have been implemented within the operational MS-NFI.…”

Section: Estimation Of Forest Attributesmentioning

confidence: 99%

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Multi-source forest inventory data for forest production and utilization analyses at different levels

Haakana¹

2017

Diss. For.

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National forest inventory (NFI) data are commonly used in national and regional scenario analyses on forest production and utilization possibilities. There is an increased demand for similar analyses at the sub-regional level, and further, to incorporate spatially explicit data into the analyses. However, the fairly sparse network of NFI sample plots allows analyses only for large areas. The present dissertation explored whether satellite imagery, NFI sample plot data and the k nearest neighbour estimation method can be employed in generating spatial forest data for scenario analyses at the local level. The method was first applied in the area of two villages in Eastern Finland to quantify the effects of administrative land use and technical land-form constraints on timber production. Secondly, the impacts of three alternative regional felling strategies on suitable habitat for the Siberian flying squirrel (Pteromys volans) were assessed.As a scenario analysis tool, the Finnish forestry dynamics model MELA was used. Management units for simulations of forest development and management activities were delineated by means of image segmentation and digital maps on restriction areas, and new weights for NFI sample plots, that is, the representativeness in these units, were estimated by means of satellite image data. The performance of different segmentation methods and different spectral features in the estimation were examined. Image segments corresponding to forest stands enabled the use of patch-and landscape-level models in the prediction of suitable habitat.Satellite image-based estimation of new NFI sample plot weights was found to be a feasible method for generating forest data for scenario analyses in areas smaller than is possible with the plot data only, for example, for municipalities. Satellite imagery with large geographic coverage and continuous NFI field measurements provide cost-efficient data sources for versatile impact and scenario analyses at the local level.

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