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- Title
Allometric Scaling and Resource Limitations Model of Tree Heights: Part 3. Model Optimization and Testing over Continental China.
- Authors
Xiliang Ni; Taejin Park; Sungho Choi; Yuli Shi; Chunxiang Cao; Xuejun Wang; Lefsky, Michael A.; Simard, Marc; Myneni, Ranga B.
- Abstract
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.
- Subjects
CHINA; TREE height; ALLOMETRIC equations; SCALING laws (Statistical physics); GEOLOGY; LASER altimeters; FOREST reserves
- Publication
Remote Sensing, 2014, Vol 6, Issue 5, p3533
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs6053533