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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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MEYER, V.; SAATCHI, S.; CLARCK, D. B.; KELLER, M.; VICENT, G.; FERRAZ, A.; ESPÍRITO-SANTO, F.; OLIVEIRA, M. V. N. d'; KAKI, D.; CHAVE, J.. |
Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the Properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth... |
Tipo: Artigo de periódico |
Palavras-chave: Floresta neotropical; Neotropical forests; Bosques neotropicales; Teledetección; Inventario forestal; Dossel; Cubierta forestal; Biomassa aérea; Reservorios de carbono; Old-grow lowland; Planícies antigas; Planicies antiguas; Sensoriamento Remoto; Inventário Florestal; Raio Laser; Carbono; Estoque; Remote sensing; Lasers; Lidar; Forest inventory; Forest canopy; Aboveground biomass; Carbon sinks. |
Ano: 2018 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1092386 |
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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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PAPA, D. de A.; ALMEIDA, D. R. A. de; SILVA, C. A.; FIGUEIREDO, E. O.; STARK, S. C.; VALBUENA, R.; RODRIGUEZ, L. C. E.; OLIVEIRA, M. V. N. d'. |
In high biodiversity areas, such as the Amazon, forest inventory is a challenge due to large variations in vegetation structure and inaccessibility. Capturing the full gradient of variability requires the acquisition of a large number of sample plots. Pre-stratified inventory is an efficient strategy that reduces sampling effort and cost. Low-cost remote sensing techniques may significantly expand pre-stratification capacity; however, the simplest option, satellite optical imagery, cannot detect small variations in primary forests. Alternatively, three-dimensional information obtained from airborne laser scanning (ALS, a.k.a. airborne lidar) has been successfully used to estimate structural parameters in tropical forests. Our objective was to assess to... |
Tipo: Artigo de periódico |
Palavras-chave: Manejo florestal; Field forest inventory; Filed sampling; Amostragem de campo; Características de plantas; Cubierta forestal; Espacios vacíos en el dosel; Índice de área foliar; Análisis de conglomerados; Análisis estadístico; Embrapa Acre; Rio Branco (AC); Acre; Amazônia Ocidental; Western Amazon; Amazonia Occidental; Administração Florestal; Floresta Tropical; Inventário Florestal; Amostragem; População de Planta; Sensoriamento Remoto; Raio Laser; Estrutura Vegetal; Campo Experimental; Análise Estatística; Tropical forests; Forest management; Plant characteristics; Remote sensing; Lidar; Forest canopy; Canopy gaps; Leaf area index; Cluster analysis; Statistical analysis. |
Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1115167 |
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