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Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors techniqueAuthor(s): Ronald E. McRoberts; Mark D. Nelson; Daniel G. Wendt
Source: Remote Sensing of Environment. 82:457-468.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionFor two large study areas in Minnesota, USA, stratified estimation using classified Landsat Thematic Mapper satellite imagery as the basis for stratification was used to estimate forest area. Measurements of forest inventory plots obtained for a 12-month period in 1998 and 1999 were used as the source of data for within-stratum estimates. These measurements further served as calibration data for a k-Nearest Neighbors technique that was used to predict forest land proportion for image pixels. The continuum of forest land proportion predictions was separated into strata to facilitate stratified estimation. The k-Nearest Neighbors technique is carefully explained, five precautions are noted, and a plea is made for an objective approach to calibrating the technique. The variances of the stratified forest area estimates were smaller by factors as great as 5 than variances of the arithmetic mean calculated under the assumption of simple random sampling. In addition, when including all plots over a 5-year plot measurement cycle, the forest area precision estimates may be expected to satisfy national standards.
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CitationMcRoberts, Ronald E.; Nelson, Mark D.; Wendt, Daniel G. 2002. Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors technique. Remote Sensing of Environment. 82:457-468.
- Stratified estimates of forest area using the k-nearest neighbors technique and satellite imagery
- Forest/non-forest mapping using inventory data and satellite imagery
- Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery
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