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

Abstract

Abstract: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 (R 2 = 0.85; RMSE = 1.81 m) and a bootstrapping approach (R 2 = 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.

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

“…Theoretically, gpCntRngOff 1 is assumed to represent the ground level elevation within a GLAS field-of-view, while SigBegOff refers to the highest point of a surface. Amongst five possible GLAS height metrics representative of tree heights [25], we used the best metric that closely resembled field-measured and Laser Vegetation Imaging Sensor tree heights (R 2 = 0.70; RMSE = 4.42 m; [25]): that is, "SigBegOff -gpCntRngOff 1" with correction of the potential bias [40] (Equation (1)). …”

“…Information of the model optimization and evaluation is provided in Section 4 followed by results and discussion (Section 5) and concluding remarks (Section 6). The second paper of this series [25] examines in detail how the same procedures work at a local scale, specifically at several FLUXNET sites. Future articles in the series will consolidate these results and extend them to biomass estimation.…”

Evaluating Vegetation Growing Season Changes in Northeastern China by Using GIMMS LAI3g Data

“…The LAI dataset used in this study is LAI3g, which is derived based on the third-generation NDVI (NDVI3g) [22][23][24], from the Advanced Very High Resolution Radiometer (AVHRR) carried by the National Oceanic and Atmospheric Administration (NOAA), produced by the Global Inventory Monitoring and Modeling Studies (GIMMS), at a spatial resolution of 1/12 degree (about 8 km) and 15-day interval, spanning from January 1982 to December 2011 [29].…”

A combined GLAS and MODIS estimation of the global distribution of mean forest canopy height

“…For example, Shi et al (2013) and Choi et al (2013) used the Allometric Scaling and Resource Limitations (ASRL) model, which predicts potential maximum tree height using a combination of allometric scaling laws and energy budgets constrained by local resource limitations. Shi et al (2013) mapped tree height over forested land in the continental United States at a spatial resolution of 1 km using the optimized ASRL model.…”