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Allometric Scaling and Resource Limitations Model of Tree Heights: Part 3. Model Optimization and Testing over Continental China

1
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
2
Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA
3
School of Remote Sensing, Nanjing University of Information Science and Technology, Nanjing 210044, China
4
Survey Planning and Design Institute, State Forest Administration of China, Beijing 100714, China
5
Center for Ecological Analysis of Lidar, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA
6
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Remote Sens. 2014, 6(5), 3533-3553; https://doi.org/10.3390/rs6053533
Received: 7 February 2014 / Revised: 3 April 2014 / Accepted: 15 April 2014 / Published: 25 April 2014
The ultimate goal of our multi-article series is to demonstrate the Allometric Scaling and Resource Limitation (ASRL) approach for mapping tree heights and biomass. This third article tests the feasibility of the optimized ASRL model over China at both site (14 meteorological stations) and continental scales. Tree heights from the Geoscience Laser Altimeter System (GLAS) waveform data are used for the model optimizations. Three selected ASRL parameters (area of single leaf, α; exponent for canopy radius, η; and root absorption efficiency, γ) are iteratively adjusted to minimize differences between the references and predicted tree heights. Key climatic variables (e.g., temperature, precipitation, and solar radiation) are needed for the model simulations. We also exploit the independent GLAS and in situ tree heights to examine the model performance. The predicted tree heights at the site scale are evaluated against the GLAS tree heights using a two-fold cross validation (RMSE = 1.72 m; R2 = 0.97) and bootstrapping (RMSE = 4.39 m; R2 = 0.81). The modeled tree heights at the continental scale (1 km spatial resolution) are compared to both GLAS (RMSE = 6.63 m; R2 = 0.63) and in situ (RMSE = 6.70 m; R2 = 0.52) measurements. Further, inter-comparisons against the existing satellite-based forest height maps have resulted in a moderate degree of agreements. Our results show that the optimized ASRL model is capable of satisfactorily retrieving tree heights over continental China at both scales. Subsequent studies will focus on the estimation of woody biomass after alleviating the discussed limitations. View Full-Text
Keywords: tree height; allometric scaling law; resource limitation; model optimization; geoscience laser altimeter system (GLAS); national forest inventory (NFI) tree height; allometric scaling law; resource limitation; model optimization; geoscience laser altimeter system (GLAS); national forest inventory (NFI)
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Ni, X.; Park, T.; Choi, S.; Shi, Y.; Cao, C.; Wang, X.; Lefsky, M.A.; Simard, M.; Myneni, R.B. Allometric Scaling and Resource Limitations Model of Tree Heights: Part 3. Model Optimization and Testing over Continental China. Remote Sens. 2014, 6, 3533-3553.

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