4.7 Article

Allometric Scaling and Resource Limitations Model of Tree Heights: Part 1. Model Optimization and Testing over Continental USA

Journal

REMOTE SENSING
Volume 5, Issue 1, Pages 284-306

Publisher

MDPI
DOI: 10.3390/rs5010284

Keywords

tree height; allometric scaling law; resource limitations; GLAS; model optimization

Funding

  1. National Natural Science Foundation of China [40801139, 41175077]
  2. China Scholarship Council
  3. Fulbright Foundation

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A methodology to generate spatially continuous fields of tree heights with an optimized Allometric Scaling and Resource Limitations (ASRL) model is reported in this first of a multi-part series of articles. Model optimization is performed with the Geoscience Laser Altimeter System (GLAS) waveform data. This methodology is demonstrated by mapping tree heights over forested lands in the continental USA (CONUS) at 1 km spatial resolution. The study area is divided into 841 eco-climatic zones based on three forest types, annual total precipitation classes (30 mm intervals) and annual average temperature classes (2 degrees C intervals). Three model parameters (area of single leaf, alpha, exponent for canopy radius, eta, and root absorption efficiency, gamma) were selected for optimization, that is, to minimize the difference between actual and potential tree heights in each of the eco-climatic zones over the CONUS. Tree heights predicted by the optimized model were evaluated against GLAS heights using a two-fold cross validation approach (R-2 = 0.59; RMSE = 3.31 m). Comparison at the pixel level between GLAS heights (mean = 30.6 m; standard deviation = 10.7) and model predictions (mean = 30.8 m; std. = 8.4) were also performed. Further, the model predictions were compared to existing satellite-based forest height maps. The optimized ASRL model satisfactorily reproduced the pattern of tree heights over the CONUS. Subsequent articles in this series will document further improvements with the ultimate goal of mapping tree heights and forest biomass globally.

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