Using remote sensing airborne laser scanning technology and multi-spectral high-resolution aerial imagery to estimate carbon stocks in the woody biomass of eucalyptus plantations

• Grant number: 12/03176-0
• Support type: Scholarships in Brazil - Master
• Effective date (Start): June 01, 2012
• Effective date (End): July 31, 2013
• Field of knowledge: Agronomical Sciences - Forestry Resources and Forestry Engineering - Forest Management
• Principal researcher: Luiz Carlos Estraviz Rodriguez
• Grantee: Carlos Alberto Silva
• Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil

Abstract

In the context of global climate change, quantification of carbon stocks in forest stands has received more attention, mainly because forests play a key role in balancing the global carbon stock. Currently, existing methodologies for measuring carbon stocks in forests are constrained by budgetary issues and time, making it difficult to carry out a complete inventory within a short time. The combination of ALS ("Airborne Laser System") technologies and high-resolution multi-spectral aerial imagery has been used as an efficient and flexible alternative to estimate carbon stocks in forest stands, due to its accuracy and efficiency when compared to conventional methods. This study aims to evaluate the use of LIDAR ("Ligth Detection and Ranging") airborne laser technology (ALS) and high-resolution multi-spectral aerial imagery to estimate carbon stocks in the woody biomass of Eucalyptus plantations. The reality of the field will be set through biometric data collected from sample plots to act as independent variables to be estimated in regression models specially developed for fitting data generated by the LiDAR. The LiDAR variables will be obtained after processing the raw data generated by airborne sensors in specific software for this processing, such as FUSION 3.1, ArcGIS 9.3 and TNT Mips 7.2. For the study will be elaborated models correlating the carbon stocks obtained by conventional methods with variables obtained by airborne laser tecnology. The statistical analyzes will be implemented with the support of the software "R Project for Statistical Computing." (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SILVA, CARLOS ALBERTO; KLAUBERG, CARINE; HUDAK, ANDREW T.; VIERLING, LEE A.; LIESENBERG, VERALDO; CARVALHO, SAMUEL P. C. E; RODRIGUEZ, LUIZ C. E.. A principal component approach for predicting the stem volume in Eucalyptus plantations in Brazil using airborne LiDAR data. FORESTRY, v. 89, n. 4, p. 422-433, AUG 2016. (13/05081-9, 12/03176-0)

SILVA, CARLOS ALBERTO; HUDAK, ANDREW THOMAS; KLAUBERG, CARINE; VIERLING, LEE ALEXANDRE; GONZALEZ-BENECKE, CARLOS; CHAVES CARVALHO, SAMUEL DE PADUA; ESTRAVIZ RODRIGUEZ, LUIZ CARLOS; CARDIL, ADRIAN. Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data. Carbon Balance and Management, v. 12, JUN 7 2017. (12/03176-0)

SILVA, CARLOS ALBERTO; KLAUBERG, CARINE; CHAVES E CARVALHO, SAMUEL DE PADUA; HUDAK, ANDREW T.; ESTRAVIZ RODRIGUEZ, LUIZ CARLOS. Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of Sao Paulo, Brazil. SCIENTIA FORESTALIS, v. 42, n. 104, p. 591-604, DEC 2014. (12/03176-0)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

SILVA, Carlos Alberto. Aboveground carbon in Eucalyptus spp. plantations - at tree level by destructive sampling and for whole stands after adjusting LiDAR metrics. 2013. Master's Dissertation - Universidade de São Paulo (USP). Escola Superior de Agricultura Luiz de Queiroz (ESALA/BC) Piracicaba.