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Airborne LIDAR for quantifying changes in biomass stocks and structural dynamics in fire-damaged forests in Central Amazon

Grant number: 16/21043-8
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): March 01, 2017
Status:Discontinued
Field of knowledge:Biological Sciences - Ecology
Principal Investigator:Luiz Eduardo Oliveira e Cruz de Aragão
Grantee:Aline Pontes Lopes
Home Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). São José dos Campos , SP, Brazil
Associated scholarship(s):18/24457-3 - Multi-temporal airborne LIDAR for quantifying aboveground biomass stocks and canopy structure dynamics in fire-affected forests in Central Amazon, BE.EP.DR

Abstract

Forest fires in the Brazilian Amazon may be responsible for over 50% of global emissions due to land use changes. However, the long-term impacts of fires in the Amazon forests are still poorly quantified, especially in the regions far from the arc of deforestation, less known by fire occurrence. The Brazilian government and research funding agencies have prioritized studies that support environmental change mitigation, especially climate change, deforestation and forest degradation. Thus, this project aims to quantify forest fire dynamics in the northern area of Purus-Madeira Interfluve, in Central Amazon, and their impact on the dynamics of forest structure and biomass stocks. To achieve this goal, a multitemporal approach and multiscale data from forest inventories in areas affected by fire will be used in combination with airborne LiDAR data and Landsat satellite images. Biomass stocks and mortality, recruitment and growth processes will be quantified by forest inventories. These data, combined with metrics and models derived from LiDAR, will be used to generate their spatial distribution estimates. The temporal variation of these estimates will allow the study of forest degradation and regeneration dynamics after the fire event and also calculate the carbon emissions associated with such processes. Moreover, the potential of LiDAR data to generate estimates of the observed changes in the forest stocks and structure will be evaluated. Thus, this thesis proposal aims to provide a methodological framework to assist the definition of mitigation strategies for climate change impacts.

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)
DE ALMEIDA, CATHERINE TORRES; GALVAO, LENIO SOARES; DE OLIVEIRA CRUZ E ARAGAO, LUIZ EDUARDO; HENRY BALBAUD OMETTO, JEAN PIERRE; JACON, ALINE DANIELE; DE SOUZA PEREIRA, FRANCISCA ROCHA; SATO, LUCIANE YUMIE; LOPES, ALINE PONTES; LIMA DE ALENCASTRO GRACA, PAULO MAURICIO; SILVA, CAMILA VALERIA DE JESUS; FERREIRA-FERREIRA, JEFFERSON; LONGO, MARCOS. Combining LiDAR and hyperspectral data for aboveground biomass modeling in the Brazilian Amazon using different regression algorithms. REMOTE SENSING OF ENVIRONMENT, v. 232, OCT 2019. Web of Science Citations: 1.
CAMPANHARO, WESLEY A.; LOPES, ALINE P.; ANDERSON, LIANA O.; DA SILVA, THIAGO F. M. R.; ARAGAO, LUIZ E. O. C. Translating Fire Impacts in Southwestern Amazonia into Economic Costs. REMOTE SENSING, v. 11, n. 7 APR 1 2019. Web of Science Citations: 1.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.