Abstract
Canopy height is a key variable in tropical forest functioning and for regional carbon inventories. We investigate the spatial structure of the canopy height of a tropical forest, its relationship with environmental physical covariates, and the implication for tropical forest height variation mapping. Making use of high-resolution maps of LiDAR-derived Digital Canopy Model (DCM) and environmental covariates from a Digital Elevation Model (DEM) acquired over 30,000 ha of tropical forest in French Guiana, we first show that forest canopy height is spatially correlated up to 2500 m. Forest canopy height is significantly associated with environmental variables, but the degree of correlation varies strongly with pixel resolution. On the whole, bottomland forests generally have lower canopy heights than hillslope or hilltop forests. However, this global picture is very noisy at local scale likely because of the endogenous gap-phase forest dynamic processes. Forest canopy height has been predictively mapped across a pixel resolution going from 6 m to 384 m mimicking a low resolution case of 3 points·km − 2 . Results of canopy height mapping indicated that the error for spatial model with environment effects decrease from 8.7 m to 0.91 m, depending of the pixel resolution. Results suggest that, outside the calibration plots, the contribution of environment in shaping the global canopy height distribution is quite limited. This prevents accurate canopy height mapping based only on environmental information, and suggests that precise canopy height maps, for local management purposes, can only be obtained with direct LiDAR monitoring.
Highlights
The height of a tropical forest canopy is a key feature of the functioning and dynamics of a tropical forest ecosystem [1]
We investigated the spatial structure of canopy height variations and its relationship with the environment across spatial scales of 6 to 384 m using high-resolution maps of Light Detection and Ranging (LiDAR)-derived digital canopy height and elevation for 30,000 ha of tropical forests in French Guiana
Our results show that forest height can be estimated using points sampled from LiDAR waveforms (Figure 6), but when high-resolution mapping is needed it fails mostly because the environmental heterogeneity, at this scale, is too low to deeply shape the forest canopy height variation
Summary
The height of a tropical forest canopy is a key feature of the functioning and dynamics of a tropical forest ecosystem [1]. In the global change context, precise knowledge of forest canopy height is a prerequisite to accurately predict the aboveground forest biomass, a key component of the terrestrial carbon cycle [5]. At the individual tree level, forest canopy height is an important parameter to improve tree allometric equations [6]. Alternative strategies to independently measure canopy height from the field or via remote sensing tools would greatly improve the accuracy of tree aboveground biomass estimates [7]. At the forest landscape level, carbon mapping relies very often on forest height mapping derived from remote sensing products [8]
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