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Abstract
In order to address policy issues relating to biodiversity, productivity, and sustainability, we need detailed understanding of forest vegetation at broad geographic and time scales. Most existing maps developed from satellite imagery describe only general characteristics of the upper canopy. Detailed vegetation data are available from regional grids of field plots, but the data are not spatially complete—they do not cover an entire area of interest. Regardless of these limitations, forest policymakers and stakeholders want information about current forest conditions that is spatially explicit (mappable), spans all ownerships, and is rich in detail, including tree species, sizes, and densities. Scientists studying regional vegetation patterns and dynamics require similar data for their research. The Gradient Nearest Neighbor method for mapping vegetation is a breakthrough for regional assessments. Field plot, remotely sensed, and environmental data are integrated into a single digital map. At the regional scale, the method shows an impressive level of accuracy, suggesting its potential for strategic regional planning across ownerships.
Citation
Duncan, Sally. 2003. Seeing the trees for the forest: mapping vegetation biodiversity in coastal Oregon forests. Science Findings 56. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 1-5
