Résumé
In recent years, LiDAR technology has provided accurate forest aboveground biomass (AGB) maps in severalforest ecosystems, including tropical forests. However, its ability to accurately map forest AGB changes in highbiomasstropical forests has seldom been investigated. Here, we assess the ability of repeated LiDAR acquisitionsto map AGB stocks and changes in an old-growth Neotropical forest of French Guiana. Using two similar aerialsmall-footprint LiDAR campaigns over a four year interval, spanning ca. 20 km2, and concomitant groundsampling, we constructed a model relating median canopy height and AGB at a 0.25-ha and 1-ha resolution.This model had an error of 14% at a 1-ha resolution (RSE = 54.7 Mg ha−1) and of 23% at a 0.25-ha resolution(RSE= 86.5 Mg ha−1). This uncertainty is comparable with values previously reported in other tropical forestsand confirms that aerial LiDAR is an efficient technology for AGB mapping in high-biomass tropical forests. Ourmap predicts a mean AGB of 340 Mg ha−1 within the landscape. We also created an AGB change map, andcompared it with ground-based AGB change estimates. The correlation was weak but significant only at the0.25-ha resolution. One interpretation is that large natural tree-fall gaps that drive AGB changes in a naturallyregenerating forest can be picked up at fine spatial scale but are veiled at coarser spatial resolution. Overall,both field-based and LiDAR-based estimates did not reveal a detectable increase in AGB stock over the studyperiod, a trend observed in almost all forest types of our study area. Small footprint LiDAR is a powerful tool todissect the fine-scale variability of AGB and to detect the main ecological controls underpinning forest biomassvariability both in space and time.