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

Baena, Susana; Moat, Justin; Whaley, Oliver; Boyd, Doreen S.

Abstract

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.

Citation

Baena, S., Moat, J., Whaley, O., & Boyd, D. S. (2017). Identifying species from the air: UAVs and the very high resolution challenge for plant conservation. PLoS ONE, 12(11), Article e0188714. https://doi.org/10.1371/journal.pone.0188714

• Journal Article Type: Article
• Acceptance Date: Nov 11, 2017
• Publication Date: Nov 27, 2017
• Deposit Date: Dec 15, 2017
• Publicly Available Date: Dec 15, 2017
• Journal: PLoS ONE
• Electronic ISSN: 1932-6203
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 11
• Article Number: e0188714
• DOI: https://doi.org/10.1371/journal.pone.0188714
• Public URL: https://nottingham-repository.worktribe.com/output/896946
• Publisher URL: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0188714
• Contract Date: Dec 15, 2017