Multi-temporal airborne LIDAR for quantifying aboveground biomass stocks and canop...
| 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. | |