Travail de fin d'études: Towards predictive allometry for foliage biomass and leaf area in tree enriched areas of semi-deciduous forests in cameroon derived from handheld mobile lidar data

Abstract

In tropical rainforests, leaf area (LA) and leaf mass (LM) are essential metrics that influence key physiological processes and contribute to the assessment of forest productivity and carbon stocks. This study examines the relationship between structural parameters, LA and LM derived from both destructive sampling and handheld mobile laser scanning (HMLS) in tree-enriched areas of Central Africa. By using this combination of sampling methods, we developed predictive allometric models for LA and LM. The calibrated models for LM showed strong performance criteria with R² values ranging from 74% to 81.81% and lower values for LA ranging from 72.5% to 79.32%. Although the sample size in this study remains modest, our results highlight the potential of HMLS as a non-invasive and reliable method for estimating LA. Despite the promising results, the study notes limitations in the applicability of the models, particularly when it comes to extending the models to larger diameter trees.