Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.

Author:

Gregoire Timothy G.1234,Ståhl Göran1234,Næsset Erik1234,Gobakken Terje1234,Nelson Ross1234,Holm Sören1234

Affiliation:

1. School of Forestry and Environmental Studies, Yale University, 360 Prospect Street, New Haven, CT 06511-2104, USA.

2. Department of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden.

3. Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432, Ås, Norway.

4. 614.4/Biosperic Science Branch, NASA-Goddard Space Flight Center, Greenbelt, MD 20771, USA.

Abstract

Inasmuch as LiDAR is becoming an increasingly prominent tool for forest inventory, it is timely to develop a framework to understand the statistical properties of LiDAR-based estimates. A model-assisted approach to estimation and inference when using LiDAR as a tool to inventory aboveground forest biomass is presented. An empirical example is also presented, yet the article’s focus is largely methodological. The sampling plan in the example is viewed as a two-stage design, with slightly different primary sampling units between the profiling and scanning laser surveys. A regression estimator is presented that uses biomass data from the Norwegian National Forest Inventory as the response variable and laser-derived variables as covariates. A major thrust of this article is the presentation of the variance of the estimators of total biomass and biomass per hectare as well as variance estimators.

Publisher

Canadian Science Publishing

Subject

Ecology,Forestry,Global and Planetary Change

Reference19 articles.

1. Andersen, H.E., and Breidenbach, J. 2007. Statistical properties of mean stand biomass estimators in a LiDAR-based double sampling forest survey design.InProceedings of the ISPRS Workshop Laser Scanning 2007 and Silvilaser 2007, Espoo, Finland. Vol. XXXVI. Part 3/W52.Edited byP. Rönholm, H. Hyppä, and J. Hyppä. International Society for Photogrammetry and Remote Sensing, Headquarters: Beijing, PR China. pp. 8–13.

2. Area-based lidar-assisted estimation of forest standing volume

3. Gregoire, T.G., and Valentine, H.T. 2008. Sampling strategies for natural resources and the environment. Chapman & Hall/CRC, Boca Raton, Fla.

4. Marklund, L.G. 1988. Biomass functions for pine, spruce and birch in Sweden. Department of Forest Survey, Swedish University of Agricultural Sciences, Umeå, Sweden. [In Swedish.]

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