Adaptive Cluster Sampling for Forest Inventories
Adaptive 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.