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OLIVEIRA, M. V. N. d'; BROADBENT, E. N.; OLIVEIRA, L. C. de; ALMEIDA, D. R. A.; PAPA, D. de A.; FERREIRA, M. E.; ZAMBRANO, A. M. A.; SILVA, C. A.; AVINO, F. S.; PRATA, G. A.; MELLO, R. A.; FIGUEIREDO, E. O.; JORGE, L. A. de C.; JUNIOR, L.; ALBUQUERQUE, R. W.; BRANCALION, P. H. S.; WILKINSON, B.; COSTA, M. O. da. |
Tropical forests are often located in dicult-to-access areas, which make high-quality forest structure information dicult and expensive to obtain by traditional field-based approaches. LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-ecient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon.... |
Tipo: Artigo de periódico |
Palavras-chave: Bosques tropicales; Inventario forestal; Monitoreo; Biomassa aérea; Teledetección; Vehículos aéreos no tripulados; Drone; GatorEye; Seringal Filipinas (AC); RESEX Chico Mendes; Acre; Amazônia Ocidental; Western Amazon; Amazonia Occidental; Floresta Tropical; Inventário Florestal; Reconhecimento Florestal; Estimativa; Sensoriamento Remoto; Raio Laser; Tropical forests; Forest inventory; Monitoring; Aboveground biomass; Remote sensing; Unmanned aerial vehicles; Lidar. |
Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1122818 |
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ALMEIDA, D. R. A. de; ZAMBRANO, A. M. A.; BROADBENT, E. N.; WENDT, A. L.; FOSTER, P.; WILKINSON, B. E.; SALK, C.; PAPA, D. de A.; STARK, S. C.; VALBUENA, R.; GORGENS, E. B.; SILVA, C. A.; BRANCALION, P. H. S.; FAGAN, M.; MELI, P.; CHAZDON, R.. |
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... |
Tipo: Artigo de periódico |
Palavras-chave: Drone; GatorEye; Aerial surveys; Regeneração florestal; Biomassa aérea; Bosques lluviosos; Monitoreo; Restauración de bosques; Bosques secundarios; Biomasa aérea; Teledetección; Vehículos aéreos no tripulados; Sarapiquí; Heredia Province; Caribbean lowlands; Northeastern Costa Rica; Floresta Tropical; Reconhecimento Florestal; Floresta Secundaria; Sensoriamento Remoto; Raio Laser; Rain forests; Monitoring; Forest restoration; Secondary forests; Aboveground biomass; Remote sensing; Unmanned aerial vehicles; Lidar. |
Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1124130 |
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