%0 Conference Proceedings
%@isbn 978-85-17-0076-8
%F 600
%T Análise da relação entre dados de LiDAR e de biomassa florestal no sudoeste da Amazônia
%D 2015
%A Sato, Luciane Yumie,
%A Shimabukuro, Yosio Edemir,
%A Keller, Michael,
%A Santos, Maiza Nara dos,
%A Aragão, Luiz Eduardo Oliveira e Cruz de,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 17 (SBSR)
%C João Pessoa
%8 25-29 abr. 2015
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 3005-3012
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X Understanding the dynamics of tropical forest structure is critical for quantifying impacts of environmental changes on these ecosystems. Biomass is one of the main forest structural attributes and its quantification allows the analysis of changes in carbon stocks. However, a comprehensive assessment of tropical forest dynamics is dependent on the use of remote sensing techniques, because of its large geographical extent. In this context, Light Detection and Ranging (LiDAR) stands out as a recent technology used to obtain direct measurements of vegetation height. This work aims to perform a preliminary analysis of the relationship between LiDAR data and field measurements of forest structure in areas located in the southwestern flank of the Brazilian Amazon. Ultimately, our goal is to analyze changes in above-ground biomass (AGB) and carbon stocks in these areas. We found that height obtained from LiDAR data and biomass are linearly related, resulting in a R2 equal to 0.4425. This result indicate that mean height from LiDAR data may not be the most suitable measurement to estimate AGB if used as a single variable. We suggest that other metrics, such as wood density, 70th, 80th, 90th, 95th, 99th LiDAR height percentiles, can further improve the estimation of AGB from LIDAR data. Moreover, we also envisage that it is required to introduce alternative ways to estimate on-the-ground biomass at the plot level, as the experimental design did not allow direct comparison.
%9 LIDAR: sensores e aplicações
%@language pt
%3 p0600.pdf