Mangrove tree height growth monitoring from multi-temporal UAV-LiDAR

Abstract

Quantifying the mangrove height growth rate is important for understanding mangrove growth as well as its coupling with the other ecosystems and the climate. However, research on this topic has been limited due to the lack of multi-temporal data on mangrove tree height (TH) and methods for tree-level analysis. This study investigates the use of multi-year UAV-LiDAR data for mangrove TH growth characterization. We evaluated the UAV-LiDAR data by comparing it with field measured THs, observing a deviation ranging between −9 and +11 cm. Notably, the deviation was minimal at only 1 cm when comparing datasets collected using the same LiDAR sensor, indicating the validity of adopting multi-year UAV-LiDAR data for mangrove TH growth analysis. Methodologically, we assessed a tree-based approach and a grid-based approach. The tree-based approach is considered more feasible as it mirrors field measurements, allowing for direct comparisons with field surveys. In addition, statistically significant differences were revealed in TH growth rates among mangrove species and clumpiness groups (p < 0.001), while the invasion of Spartina alterniflora did not significantly affect the growth rates. This paper presents the inaugural effort in mangrove TH growth quantification using multi-temporal UAV-LiDAR data, showcasing the potential of this quickly emerging remote sensing technique in individual mangrove change analysis. We proposed a recommended framework for UAV-LiDAR-based TH growth rate measurement. The limitations and uncertainties embedded in the data sources, methodology, and results interpretation were also discussed.