Simo Poso 
,
Guangxing Wang,
Sakari Tuominen
Weighting alternative estimates when using multi-source auxiliary data for forest inventory
Poso S., Wang G., Tuominen S. (1999). Weighting alternative estimates when using multi-source auxiliary data for forest inventory. Silva Fennica vol. 33 no. 1 article id 669. https://doi.org/10.14214/sf.669
Abstract
Five auxiliary data sources (Landsat TM, IRS-IC, digitized aerial photographs, visual photo-interpretation and old forest compartment information) applying three study areas and three estimators, two-phase sampling with stratification, the k nearest neighbors and regression estimator, were examined. Auxiliary data were given for a high number of sample plots, which are here called first phase sample plots. The plots were distributed using a systematic grid over the study areas. Some of the plots were then measured in the field for the necessary ground truth. Each auxiliary data source in combination with field sample information was applied to produce a specific estimator for five forest stand characteristics: mean diameter, mean height, age, basal area, and volume of the growing stock. When five auxiliary data sources were used, each stand characteristic and each first phase sample plot were supplied with five alternative estimates with three alternative estimators. Mean square errors were then calculated for each alternative estimator using the cross validation method. The final estimates were produced by weighting alternative estimates inversely according to the mean square errors related to the corresponding estimator. The result was better than the final estimate of any of the single estimators. The improvement over the best single estimate, as measured in mean square error, was 16.9% on average for all five forest stand characteristics. The improvement was fairly equal for all five forest stand characteristics. Only minor differences among the accuracies of the three alternative estimators were recorded.
Keywords
remote sensing;
two-phase sampling;
forest inventory methods
-
Poso,
Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland
E-mail
simo.poso@helsinki.fi
- Wang, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland E-mail gw@nn.fi
- Tuominen, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland E-mail st@nn.fi
Received 30 April 1998 Accepted 10 February 1999 Published 31 December 1999
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Available at https://doi.org/10.14214/sf.669 | Download PDF
