Journal article
Detecting successional changes in tropical forest structure using GatorEye drone‐borne lidar
Biotropica, Vol.52, pp.1156-1168
2020
Abstract
Drone-based remote sensing is a promising new technology that combines the benefits of ground-based and satellite-derived forest monitoring by collecting fine-scale data over relatively large areas in a cost-effective manner. Here, we explore the potential of the GatorEye drone-lidar system to monitor tropical forest succession by canopy structural attributes including canopy height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, canopy Shannon index (an index of LAD), leaf area index (LAI), and understory LAI. We focus on these variables' relationship to
Details
- Title
- Detecting successional changes in tropical forest structure using GatorEye drone‐borne lidar
- Authors
- Danilo Roberti Alves Almeida (Corresponding Author) - University of Sao PauloAngelica Maria Almeyda Zambrano (Author) - University of FloridaEben North Broadbent (Author) - University of FloridaAmanda L Wendt (Author) - Earth UniversityPaul Foster (Author) - Reserva Ecologica BijagualBenjamin E Wilkinson (Author) - University of FloridaCarl Salk (Author) - University of Agricultural Sciences Alnarp SwedenDaniel de Almeida Papa (Author) - Embrapa Acre Rio Branco BrazilScott Christopher Stark (Author) - Michigan State UniversityRuben Valbuena (Author) - Bangor UniversityEric Bastos Gorgens (Author) - Universidade Federal dos Vales do Jequitinhonha e MucuriCarlos Alberto Silva (Author) - University of Maryland, College ParkPedro Henrique Santin Brancalion (Author) - University of Sao PauloMatthew Fagan (Author) - University of Maryland, College ParkPaula Meli (Author) - Universidad de La FronteraRobin Chazdon (Author) - University of the Sunshine Coast, Queensland, Tropical Forests & People Research Centre
- Publication details
- Biotropica, Vol.52, pp.1156-1168
- Publisher
- Wiley-Blackwell Publishing, Inc.
- DOI
- 10.1111/btp.12814
- ISSN
- 1744-7429
- Organisation Unit
- Tropical Forests & People Research Centre; University of the Sunshine Coast, Queensland; Forest Research Institute
- Language
- English
- Record Identifier
- 99482303702621
- Output Type
- Journal article
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