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Adaptive Cluster Sampling for Forest InventoriesAuthor(s): Francis A. Roesch
Source: Forest Science.Vol. 39, No. 4, pp. 65-69
Publication Series: Miscellaneous Publication
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DescriptionAdaptive cluster sampling is shown to be a viable alternative for sampling forests when there are rare characteristics of the forest trees which are of interest and occur on clustered trees. The ideas of recent work in Thompson (1990) have been extended to the case in which the initial sample is selected with unequal probabilities. An example is given in which the initial sample of trees is selected with probability proportional to tree basal area. If a characteristic of interest is observed on a sample tree, additional trees within a fixed distance of the sample tree are also included in the sample.
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CitationRoesch, Francis A., Jr. 1993. Adaptive Cluster Sampling for Forest Inventories. Forest Science.Vol. 39, No. 4, pp. 65-69
Keywordsforest health, biodiversity, sequential sampling
- New methods for sampling sparse populations
- Assessing forest fragmentation metrics from forest inventory cluster samples
- Searching for American chestnut: the estimation of rare species attributes in a national forest inventory
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