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Photo-based estimators for the Nevada photo-based inventoryAuthor(s): Paul L. Patterson
Source: Res. Pap. RMRS-RP-92. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 14 p.
Publication Series: Research Paper (RP)
Station: Rocky Mountain Research Station
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DescriptionThe U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis Program conducted the Nevada Photo-Based Inventory Pilot in an effort to improve precision in estimates of forest parameters, reduce field data collection costs on margin lands that are covered by slow growing woodland species, and address the potential of strategic-level inventory on lands not traditionally sampled. One part of the project involved the use of large-scale aerial photography instead of traditional field plot visits to produce three types of estimates: (1) area by a variety of forest and nonforest types; (2) percent cover of object types in the landscape; and (3) percent cover of object types within forest or nonforest type. In the context of the infinite sampling paradigm and using the support region construct, we construct the estimators used in the project, derive the variance of the estimator, and give an unbiased estimate of the variance. All estimates are constructed under the assumptions of a stratified sample of an infinite population with an independent simple random sample of each strata and a simple random sample of points in the support region around each sample point in the stratified sample.
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CitationPatterson, Paul L. 2012. Photo-based estimators for the Nevada photo-based inventory. Res. Pap. RMRS-RP-92. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 14 p.
Keywordsinfinite sampling, support region, inclusion field, photo-based inventory, large-scale aerial photography (LSP)
- Estimating two-way tables based on forest surveys
- Nevada Photo-Based Inventory Pilot (NPIP) photo sampling procedures
- Photo stratification improves northwest timber volume estimates.
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