Mangrove Biodiversity Assessment Using UAV Lidar and Hyperspectral Data in China’s Pinglu Canal Estuary

Abstract

Mangrove forests are a valuable resource for biological and species diversity, and play a critical role in maintaining biodiversity. However, traditional plant biodiversity survey methods, which rely on labor-intensive field surveys, are not suitable for large-scale continuous spatial observations. To overcome this challenge, we propose an innovative framework for mangrove biodiversity assessment and zoning management based on drone low-altitude remote sensing, integrating data such as vertical structure features and spectral diversity features extracted from on-site measurements, airborne LiDAR, and hyperspectral data. This study focuses on the Maowei Sea mangrove community, located in the estuary of China’s first Pinglu Canal since the founding of the People’s Republic of China. Using the proposed framework, we construct an evaluation index for mangrove biodiversity at the levels of species diversity, ecosystem diversity, and landscape diversity, achieving a quantitative calculation of mangrove biodiversity and an evaluation of spatial distribution patterns. The results show that the biodiversity index of mangroves ranges from 0 to 0.63, with an average value of 0.29, and high-biodiversity areas are primarily concentrated in the southwest of the study area, while low-value areas are mainly located in the north. We also select the elevation and offshore distance of mangrove growth for the spatial zoning of biodiversity. The core area of biodiversity occupies the smallest area, at 2.32%, and is mainly distributed in areas with an elevation of 1.43–1.59 m and an offshore distance of 150.08–204.28 m. Buffer zones and experimental zones account for a significant proportion, with values of 35.99% and 61.69%, respectively. Compared to traditional methods for monitoring mangrove biodiversity, such as community field-sample surveys, the proposed method using unmanned-aerial-vehicle LiDAR and hyperspectral coupling technology to assess mangrove biodiversity and establish a zoning management framework is more conducive to formulating mangrove biodiversity conservation strategies. The study provides a feasible solution for the large-scale biodiversity mapping of mangroves in the Maowei Sea at the estuary of the Pinglu Canal.

Hyperspectral Analysis and Regression Modeling of SPAD Measurements in Leaves of Three Mangrove Species

“…Compared to other remote sensing platforms, UAVs have high temporal and spatial resolution imaging capabilities, which are cost-effective and highly adaptable [60]. Many researchers have confirmed that combining UAV hyperspectral data with LiDAR data can effectively improve inversion accuracy [61,62], which will also be a new trend in studying SPAD inversion.…”

Coupling UAV Hyperspectral and LiDAR Data for Mangrove Classification Using XGBoost in China’s Pinglu Canal Estuary

“…Characterized by species and structural diversity, ecosystem complexity, and spatial and temporal variability, these factors collectively influence the growth of different mangrove species [3][4][5][6]. Analyzing the distribution of species within mangrove ecosystems elucidates their biodiversity by evaluating biomass and carbon storage capacities [7,8]. However, the extent of mangrove ecosystems has gradually diminished in recent years owing to human activities, particularly those associated with agricultural production [9,10].…”