Abstract
Although double sampling has been shown to be an effective method to estimate timber volume in forest inventories, only a limited body of research has tested the effectiveness of double sampling on forest biomass estimation. From forest biomass inventories collected over 9,683 ha using systematic point sampling, we examined how a double sampling scheme would have affected precision and efficiency in these biomass inventories. Our results indicated that double sample methods would have yielded biomass estimations with similar precision as systematic point sampling when the small sample was ≥ 20% of the large sample. When the small to large sample time ratio was 3:1, relative efficiency (a combined measure of time and precision) was highest when the small sample was a 30% subsample of the large sample. At a 30% double sample intensity, there was a < 3% deviation from the original percent margin of error and almost half the required time. Results suggest that double sampling can be an efficient tool for natural resource managers to estimate forest biomass.
Document Type
Article
Publication Date
5-3-2012
Digital Object Identifier (DOI)
https://doi.org/10.3390/f3020179
Funding Information
The authors would thank the University of Kentucky, Department of Forestry and the Mountain Association for Community and Economic Development (MACED) for supporting this project.
Repository Citation
Parrott, David L.; Lhotka, John M.; Fei, Songlin; and Shouse, B. Scott, "Improving Woody Biomass Estimation Efficiency Using Double Sampling" (2012). Forestry and Natural Resources Faculty Publications. 13.
https://uknowledge.uky.edu/forestry_facpub/13
Included in
Forest Sciences Commons, Natural Resource Economics Commons, Natural Resources and Conservation Commons, Natural Resources Management and Policy Commons
Notes/Citation Information
Published in Forests, v. 3, issue 2, p. 179-189.
© 2012 by the authors; licensee MDPI, Basel, Switzerland.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).