Mapping total aboveground biomass change in the Brazilian cerrado using Uav-Lidar (2023)
- Authors:
- Schlickmann, Monique Bohora
- Nogueira, Luiz Guilherme
- Leite, Rodrigo - Universidade Federal de Viçosa (UFV)
- Kleydson Diego Rocha
- Xia, Jinyi
- Souza, Danilo
- Broadbent, Eben North
- Saatchi, Sassan
- Klauberg, Carine
- Hudak, Andrew T
- Karasinski, Mauro Alessandro - Universidade Federal do Paraná (UFPR)
- Ferreira, Matheus Pinheiro
- Almeida, Danilo Roberti Alves de
- Silva, Carlos Alberto
- Autor USP: ALMEIDA, DANILO ROBERTI ALVES DE - ESALQ
- Unidade: ESALQ
- DOI: 10.1109/IGARSS52108.2023.10282158
- Subjects: AERONAVES NÃO TRIPULADAS; BIOMASSA; CERRADO; DOSSEL (BOTÂNICA); SENSORIAMENTO REMOTO; TECNOLOGIA LIDAR
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway, NJ
- Date published: 2023
- Source:
- Título do periódico: IEEE International Geoscience and Remote Sensing Symposium - IGARSS
- Conference titles: IEEE International Geoscience and Remote Sensing Symposium - IGARSS
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SCHLICKMANN, Monique Bohora et al. Mapping total aboveground biomass change in the Brazilian cerrado using Uav-Lidar. 2023, Anais.. Piscataway, NJ: Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, 2023. Disponível em: https://doi.org/10.1109/IGARSS52108.2023.10282833. Acesso em: 27 set. 2024. -
APA
Schlickmann, M. B., Nogueira, L. G., Leite, R., Kleydson Diego Rocha,, Xia, J., Souza, D., et al. (2023). Mapping total aboveground biomass change in the Brazilian cerrado using Uav-Lidar. In IEEE International Geoscience and Remote Sensing Symposium - IGARSS. Piscataway, NJ: Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo. doi:10.1109/IGARSS52108.2023.10282158 -
NLM
Schlickmann MB, Nogueira LG, Leite R, Kleydson Diego Rocha, Xia J, Souza D, Broadbent EN, Saatchi S, Klauberg C, Hudak AT, Karasinski MA, Ferreira MP, Almeida DRA de, Silva CA. Mapping total aboveground biomass change in the Brazilian cerrado using Uav-Lidar [Internet]. IEEE International Geoscience and Remote Sensing Symposium - IGARSS. 2023 ;[citado 2024 set. 27 ] Available from: https://doi.org/10.1109/IGARSS52108.2023.10282833 -
Vancouver
Schlickmann MB, Nogueira LG, Leite R, Kleydson Diego Rocha, Xia J, Souza D, Broadbent EN, Saatchi S, Klauberg C, Hudak AT, Karasinski MA, Ferreira MP, Almeida DRA de, Silva CA. Mapping total aboveground biomass change in the Brazilian cerrado using Uav-Lidar [Internet]. IEEE International Geoscience and Remote Sensing Symposium - IGARSS. 2023 ;[citado 2024 set. 27 ] Available from: https://doi.org/10.1109/IGARSS52108.2023.10282833 - Impacts of selective logging on Amazon forest canopy structure and biomass with a LiDAR and photogrammetric survey sequence
- Postfire tree structure from high-resolution LiDAR and RBR sentinel 2A fire severity metrics in a Pinus halepensis-dominated burned stand
- High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD)
- Assessing tropical forest degradation and restoration through lidar remote sensing
- Beyond trees: mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data
- Measuring Individual Tree Diameter and Height Using GatorEye High-Density UAV-Lidar in an Integrated Crop-Livestock-Forest System
- Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data
- Reframing tropical savannization: linking changes in canopy structure to energy balance alterations that impact climate
- Plant‐mediated effects of fire and fragmentation drive plant–pollinator interaction β‐diversity in fire‐dependent pine savannas
- Forest inventory with high-density UAV-Lidar: Machine learning approaches for predicting individual tree attributes
Informações sobre o DOI: 10.1109/IGARSS52108.2023.10282158 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas