Calibrating Predicted Diameter Distribution with Additional Information
Abstract:The diameter distribution of the growing stock is an essential starting point in many forest management planning problems. There are several methods for predicting the diameter distribution of a stand, varying from methods which utilize theoretical distribution functions to nonparametric methods. Usually the predicted diameter distribution is scaled so that the stem number corresponds to the measured value. However, if stem number and basal area are both known, it may be difficult to predict a distribution that gives correct estimates for both these characteristics. Such diameter distributions can be obtained using an approach adopted from sampling theory—calibration estimation. In this study, the diameter distributions of Scots pine were predicted with two different methods, the Weibull and percentile based methods, and then calibrated with additional information. The calibration reduced the RMSE of stand variables computed from the predicted distribution. FOR. SCI. 46(3): 390–396.
Keywords: Diameter distribution prediction; Weibull; calibration estimation; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; goal programming; linear programming; natural resource management; natural resources; nonlinear optimization; percentiles
Document Type: Miscellaneous
Affiliations: 1: Researcher Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44 Kannus, FIN, 69101, Finland, Fax: +358-6-8743201 firstname.lastname@example.org 2: Researcher Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68 Joensuu, FIN, 80101, Finland,
Publication date: August 1, 2000
- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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