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Title: Stratified estimation of forest inventory variables using spatially summarized stratifications
Author: McRoberts, R.E.; Wendt, D.G.; Liknes, G.C.;
Source: Silva Fennica. 39(4): 559-571.
Publication Series: Scientific Journal (JRNL)
Large area natural resource inventory programs typically report estimates for selected geographic areas such as states or provinces, counties, and municipalities. To increase the precision of estimates, inventory programs may use stratified estimation, with classified satellite imagery having been found to be an efficient and effective basis for stratification. For the benefit of users who desire additional analyses, the inventory programs often make data and estimation procedures available via the Internet. For their own analyses, users frequently request access to stratifications used by the inventory programs. When data analysis is via the Internet and stratifications are based on classifications of even medium resolution satellite imagery, the memory requirements for storing the stratifications and the online time for processing them may be excessive. One solution is to summarize the stratifications at coarser spatial scales, thus reducing both storage requirements and processing time. If the bias and loss of precision resulting from using summaries of stratifications is acceptably small, then this approach is viable.
Keywords: bias, classified satellite imagery, Internet, precision, variance
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McRoberts, R.E.; Wendt, D.G.; Liknes, G.C. 2005. Stratified estimation of forest inventory variables using spatially summarized stratifications
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