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Rebuilding Spatial Forest Inventories from Aggregated Data

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The limited availability of data sets with a sufficiently high spatial scale and resolution can pose a significant challenge in the development and testing of new forest management and economics modeling approaches. This article describes and tests an algorithm for generating an ecologically and statistically consistent data set for the province of British Columbia by projecting publicly available aggregated forest inventory information back onto a landscape grid. The dispersal procedure assigns specific combinations of ecosystem, tree species, site quality, and age class parameters for each mapping tile, allowing for the use of standard growth and yield modeling procedures in simulating forest growth over time. Although ecosystem assignments were relatively accurate, significant location errors within forest management units remain for species, site quality, and age class assignments.
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Keywords: data disaggregation; forest inventory; predictive mapping

Document Type: Research Article

Publication date: 2010-09-01

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    The Journal of Forestry is the most widely circulated scholarly forestry journal in the world. In print since 1902, the Journal has received several national awards for excellence. The mission of the Journal of Forestry is to advance the profession of forestry by keeping forest management professionals informed about significant developments and ideas in the many facets of forestry: economics, education and communication, entomology and pathology, fire, forest ecology, geospatial technologies, history, international forestry, measurements, policy, recreation, silviculture, social sciences, soils and hydrology, urban and community forestry, utilization and engineering, and wildlife management. The Journal is published bimonthly: January, March, May, July, September, and November.

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