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Remote Sens. 2013, 5(1), 202-223;

Allometric Scaling and Resource Limitations Model of Tree Heights: Part 2. Site Based Testing of the Model

Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA
State Key Laboratory of Remote Sensing Sciences, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China
School of Remote Sensing, Nanjing University of Information Science and Technology, Nanjing 210044, China
Bay Area Environmental Research Institute (BAERI)/NASA Ames Research Center, Moffett Field, CA 94035, USA
Department of Watershed Science, Utah State University, UT 84322, USA
Center for Ecological Analysis of Lidar, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
Department of Geography, Hunter College of CUNY, New York, NY 10065, USA
College of Urban and Environmental Sciences and Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
Biospheric Science Branch, NASA Ames Research Center, Moffett Field, CA 94035, USA
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Received: 12 November 2012 / Revised: 31 December 2012 / Accepted: 4 January 2013 / Published: 10 January 2013
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The ultimate goal of this multi-article series is to develop a methodology to generate continuous fields of tree height and biomass. The first paper demonstrated the need for Allometric Scaling and Resource Limitation (ASRL) model optimization and its ability to generate spatially continuous fields of tree heights over the continental USA at coarse (1 km) spatial resolution. The objective of this second paper is to provide an assessment of that approach at site scale, specifically at 12 FLUXNET sites where more accurate data are available. Estimates of tree heights from the Geoscience Laser Altimeter System (GLAS) waveform data are used for model optimization. Amongst the five possible GLAS metrics that are representative of tree heights, the best metric is selected based on how closely the metric resembles field-measured and Laser Vegetation Imaging Sensor tree heights. In the optimization process, three parameters of the ASRL model (area of single leaf, α; exponent for canopy radius, η; and root absorption efficiency, γ) are simultaneously adjusted to minimize the difference between model predictions and observations at the study sites (distances to valid GLAS footprints ≤ 10 km). Performance of the optimized ASRL model was evaluated through comparisons to the best GLAS metric of tree height using a two-fold cross validation approach (R2 = 0.85; RMSE = 1.81 m) and a bootstrapping approach (R2 = 0.66; RMSE = 2.60 m). The optimized model satisfactorily performed at the site scale, thus corroborating results presented in part one of this series. Future investigations will focus on generalizing these results and extending the model formulation using similar allometric concepts for the estimation of woody biomass. View Full-Text
Keywords: tree height; allometric scaling law; resource limitation; GLAS; model optimization tree height; allometric scaling law; resource limitation; GLAS; model optimization

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Choi, S.; Ni, X.; Shi, Y.; Ganguly, S.; Zhang, G.; Duong, H.V.; Lefsky, M.A.; Simard, M.; Saatchi, S.S.; Lee, S.; Ni-Meister, W.; Piao, S.; Cao, C.; Nemani, R.R.; Myneni, R.B. Allometric Scaling and Resource Limitations Model of Tree Heights: Part 2. Site Based Testing of the Model. Remote Sens. 2013, 5, 202-223.

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