Identifying species from the air: UAVs and the very high resolution challenge for plant conservation

被引:110
作者
Baena, Susana [1 ,2 ]
Moat, Justin [1 ,2 ]
Whaley, Oliver [1 ]
Boyd, Doreen S. [2 ]
机构
[1] Royal Bot Gardens, Richmond, Surrey, England
[2] Univ Nottingham, Sch Geog, Nottingham, England
来源
PLOS ONE | 2017年 / 12卷 / 11期
关键词
AERIAL VEHICLE UAV; INDIVIDUAL TREE CROWNS; REMOTELY-SENSED DATA; DELINEATION ALGORITHM; LIDAR; IMAGERY; CLASSIFICATION; BIODIVERSITY; RECOGNITION; FORESTS;
D O I
10.1371/journal.pone.0188714
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The Pacific Equatorial dry forest of Northern Peru is recognised for its unique endemic biodiversity. Although highly threatened the forest provides livelihoods and ecosystem services to local communities. As agro-industrial expansion and climatic variation transform the region, close ecosystem monitoring is essential for viable adaptation strategies. UAVs offer an affordable alternative to satellites in obtaining both colour and near infrared imagery to meet the specific requirements of spatial and temporal resolution of a monitoring system. Combining this with their capacity to produce three dimensional models of the environment provides an invaluable tool for species level monitoring. Here we demonstrate that object based image analysis of very high resolution UAV images can identify and quantify keystone tree species and their health across wide heterogeneous landscapes. The analysis exposes the state of the vegetation and serves as a baseline for monitoring and adaptive implementation of community based conservation and restoration in the area.
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页数:21
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