Skip to main content

Adaptive Cluster Sampling for Forest Inventories

The full text article is temporarily unavailable.

We apologise for the inconvenience. Please try again later.

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. For. Sci. 39(4):655-669.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Forest health; biodiversity; sequential sampling

Document Type: Journal Article

Affiliations: Mathematical Statistician, Institute for Quantitative Studies, Southern Forest Experiment Station, USDA Forest Service, Room T-10210, 701 Loyola Avenue, New Orleans, LA 70113

Publication date: 01 November 1993

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more