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Forest/non-forest mapping using inventory data and satellite imageryAuthor(s): Ronald E. McRoberts
Source: In: Proceedings of the ForestSAT Symposium, Edinbourgh, UK: Forest Research, Forestry Commission. [City, State: Publisher Unknown]. 9 p.
Publication Series: Scientific Journal (JRNL)
Station: North Central Research Station
PDF: View PDF (1.94 MB)
DescriptionFor two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and two prediction techniques, logistic regression and a k-Nearest Neighbours technique. The maps were used to increase the precision of forest area estimates by using them as the basis for stratified estimation. Estimates of mean proportion forest area were similar for all estimation methods, but the variances of stratified estimates were smaller than variances under an assumption of simple random sampling by factors as great as 6.
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CitationMcRoberts, Ronald E. 2002. Forest/non-forest mapping using inventory data and satellite imagery. In: Proceedings of the ForestSAT Symposium, Edinbourgh, UK: Forest Research, Forestry Commission. [City, State: Publisher Unknown]. 9 p.
Keywordsk-Nearest Neighbours, logistic model, stratification
- Stratified estimates of forest area using the k-nearest neighbors technique and satellite imagery
- Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors technique
- The effects of imperfect reference data on remote sensing-assisted estimators of land cover class proportions
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