Detecting successional changes in tropical forest structure using GatorEye drone‐borne lidar

Autor: Paula Meli, Carlos A. Silva, Matthew E. Fagan, Robin L. Chazdon, Benjamin E. Wilkinson, Angelica M. Almeyda Zambrano, Paul Foster, Daniel de Almeida Papa, Eben N. Broadbent, Danilo Roberti Alves de Almeida, Amanda L. Wendt, Eric Bastos Gorgens, Ruben Valbuena, Scott C. Stark, Pedro H. S. Brancalion, Carl Salk
Přispěvatelé: Danilo Roberti Alves de Almeida, Universdade de São Paulo (USP/ESALQ) / University of Florida, Angelica Maria Almeyda Zambrano, University of Florida, Eben North Broadbent, University of Florida, Amanda L. Wendt, Organization for Tropical Studies / EARTH University, Paul Foster, Reserva Ecológica Bijagual / University of Michigan, Benjamin E. Wilkinson, University of Florida, Carl Salk, University of Agricultural Sciences, DANIEL DE ALMEIDA PAPA, CPAF-AC, Scott Christopher Stark, Michigan State University, Ruben Valbuena, Bangor University, Eric Bastos Gorgens, Universidade Federal do Vale do Jequitinhonha e Mucuri, Carlos Alberto Silva, University of Florida / University of Maryland, Pedro Henrique Santin Brancalion, Universidade de São Paulo (USP/ESALQ), Matthew Fagan, University of Maryland, Paula Meli, Universidade de São Paulo (USP/ESALQ) / Universidad de La Frontera, Robin Chazdon, University of Connecticut / University of the Sunshine Coast.
Rok vydání: 2020
Předmět:
Northeastern Costa Rica
0106 biological sciences
Canopy
Monitoring
010504 meteorology & atmospheric sciences
Forest restoration
Caribbean lowlands
Vehículos aéreos no tripulados
Reconhecimento Florestal
Unmanned aerial vehicles
010603 evolutionary biology
01 natural sciences
Aerial surveys
Diversity index
Floresta Tropical
Teledetección
Sarapiquí
Leaf area index
Restauración de bosques
Restoration ecology
Bosques lluviosos
Ecology
Evolution
Behavior and Systematics
Raio Laser
0105 earth and related environmental sciences
Floresta Secundaria
Lidar
Biomassa aérea
Regeneração florestal
Monitoreo
Biomasa aérea
Aboveground biomass
Species diversity
Forestry
Understory
Remote sensing
TECNOLOGIA LIDAR
Drone
Spatial heterogeneity
Heredia Province
Environmental science
Secondary forest
GatorEye
Rain forests
Secondary forests
Bosques secundarios
Sensoriamento Remoto
Zdroj: Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice)
Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
ISSN: 1744-7429
0006-3606
Popis: 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 aboveground biomass (AGB) stocks and species diversity. In the Caribbean lowlands of northeastern Costa Rica, we analyze nine tropical forests stands (seven secondgrowth and two old-growth). Stands were relatively homogenous in terms of canopy height and spatial heterogeneity, but not in their gap fraction. Neither species density nor tree community Shannon diversity index was significantly correlated with the canopy Shannon index. Canopy height, LAI, and AGB did not show a clear pattern as a function of forest age. However, gap fraction and spatial heterogeneity increased with forest age, whereas understory LAI decreased with forest age. Canopy height was strongly correlated with AGB. The heterogeneous mosaic created by successional forest patches across human-managed tropical landscapes can now be better characterized. Drone-lidar systems offer the opportunity to improve assessment of forest recovery and develop general mechanistic carbon sequestration models that can be rapidly deployed to specific sites, an essential step for monitoring progress within the UN Decade on Ecosystem Restoration. Made available in DSpace on 2020-08-01T11:12:46Z (GMT). No. of bitstreams: 1 27015.pdf: 1386408 bytes, checksum: cce9ebab5fed640e715ad6387e973c5a (MD5) Previous issue date: 2020
Databáze: OpenAIRE
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