文献类型: 外文期刊
作者: Yin, Dameng 1 ; Wang, Le 1 ; Lu, Ying 1 ; Shi, Chen 4 ;
作者机构: 1.SUNY Buffalo, Dept Geog, 105 Wilkeson Quad, Buffalo, NY 14261 USA
2.Chinese Acad Agr Sci, Inst Crop Sci, Beijing 100081, Peoples R China
3.Chinese Acad Agr Sci, Natl Nanfan Res Inst Sanya, Sanya 572024, Peoples R China
4.Capital Normal Univ, Coll Resources Environm & Tourism, Beijing 100048, Peoples R China
关键词: Mangrove; Growth rate; Multi-temporal; Unmanned aerial vehicle; LiDAR; Individual tree
期刊名称:REMOTE SENSING OF ENVIRONMENT ( 影响因子:13.5; 五年影响因子:14.2 )
ISSN: 0034-4257
年卷期: 2024 年 303 卷
页码:
收录情况: SCI
摘要: 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 UAVLiDAR 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.
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