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Articles by Olli Leino
Category : Research article
article id 354,
category
Research article
(2006).
Inventory of sparse forest populations using adaptive cluster sampling.
Silva Fennica
vol.
40
no.
1
article id 354.
https://doi.org/10.14214/sf.354
Keywords:
coarse woody debris;
adaptive cluster sampling;
simple random sampling;
drought damage;
efficiency
Abstract |
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Author Info
In many studies, adaptive cluster sampling (ACS) proved to be a powerful tool for assessing rare clustered populations that are difficult to estimate by means of conventional sampling methods. During 2002 and 2003, severe drought-caused damage was observed in the park forests of the City of Helsinki, Finland, especially in barren site pine and spruce stands. The aim of the present study was to examine sampling and measurement methods for assessing drought damage by analysing the effectiveness of ACS compared with simple random sampling (SRS). Horvitz-Thompson and Hansen-Hurwitz estimators of the ACS method were used for estimating the population mean and variance of the variable of interest. ACS was considerably more effective than SRS in assessing rare clustered populations such as those resulting from drought damage. The variances in the ACS methods were significantly smaller and the inventory efficiency in the field better than in SRS.
-
Talvitie,
University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland
E-mail:
mervi.talvitie@helsinki.fi
- Leino, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ol@nn.fi
- Holopainen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ah@nn.fi
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