The Significance of Spatial Resolution: Identifying Forest Cover from Satellite Data
Abstract:The objective of this study was to determine if decreasing pixel size increases overall accuracy with which forest species can be separated using satellite data. Classification accuracy achieved with Landsat Thematic Mapper (TM) channels 2, 3, and 4 were compared with results from SPOT-XS. Reference data prepared from enlarged prints of aerial photographs and field checks included 19 cover types, nine of which were coniferous. Results with SPOT-XS alone yielded an overall accuracy of 70.1 percent, and with Landsat TM 57.1 percent at species level. Overall accuracy increased by 3 percent when either SPOT-XS or Landsat TM data were integrated with SPOT-PAN data.
Keywords: biometrics; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; land use; natural resource management; natural resources; remote sensing
Document Type: Miscellaneous
Affiliations: 1: Forester USDA Forest Service, Savannah River, PO Box 700 Ellenton, SC, 29809, firstname.lastname@example.org 2: Professor Emeritus School of Natural Resources and Environment, University of Michigan, Ann Arbor
Publication date: 2001-06-01
- 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.
2015 Impact Factor: 1.476
Ranking: 22 of 66 in forestry
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