%0 Conference Proceedings
%4 sid.inpe.br/mtc-m21d/2022/12.13.18.25
%2 sid.inpe.br/mtc-m21d/2022/12.13.18.25.39
%T Forest degradation rates and carbon changes in the Brazilian Arc of Deforestation using repeated airborne lidar
%D 2022
%A Keller, Michael Maier,
%A Csillik, Ovidiu,
%A Ferraz, Antonio,
%A Pinagé, Ekena Rangel,
%A Longo, Marcos,
%A Duffy, Paul,
%A Saatchi, Sassan S.,
%A Ometto, Jean Pierre Henry Balbaud,
%@affiliation US Forest Service San Juan
%@affiliation NASA Jet Propulsion Laboratory
%@affiliation NASA Jet Propulsion Laboratory
%@affiliation Oregon State University
%@affiliation Lawrence Berkeley National Laboratory
%@affiliation Neptune and Company
%@affiliation JPL
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress jean.ometto@inpe.br
%B AGU Fall Meeting
%C Chicago, IL
%8 12-16 Dec. 2022
%I AGU
%X The Brazilian Amazon is a hotspot of deforestation and forest degradation caused by logging, fire, and deforestation-associated fragmentation and edge effects. While the extent of deforestation and associated carbon losses are relatively well known, the quantification of the carbon losses caused by degradation and the carbon gained by recovery of degraded forest ranges widely. We present a detailed analysis of forest changes and associated carbon gains and losses by using repeated randomized airborne lidar surveys for 2016 and 2017 over 102 different transects covering more than 50,000 ha throughout the Brazilian Arc of Deforestation . We directly measured changes in canopy height and used previously calibrated allometric equations to estimate aboveground carbon changes. After gridding the surveyed area to 50 m x 50 m, we found that 21.6% of the area analyzed suffered losses in canopy height that exceeded 0.5 m, while only 16.3% of the area had canopy height recovery higher than 0.5 m. This translates to an annual carbon loss of 102.8 GgC, while carbon gained through forest regrowth was 33.4 GgC. Canopy height losses that exceeded 5 m accounted for 6.1% of the loss area identified but were responsible for 28.3% of the total aboveground carbon loss. When separated according to legally protected status, carbon changes on loss areas averaged -7.1 ± 7.6 (standard deviation) MgC/ha-y inside indigenous territories, -9.8 ± 13.0 MgC/ha-y within conservation units and -10.1 ± 12.1 MgC/ha-y outside the two protected categories. Carbon changes in gain areas averaged 4.0 ± 1.8 MgC/ha-y with no discernible differences among the three categories. To attribute carbon losses to different degradation drivers, we trained a machine learning model based on lidar point cloud metrics and visual interpretation of high resolution satellite imagery to differentiate between multiple types of deforestation and forest degradation (e.g. logging, fire). Extrapolating the results to the extent of the Arc of Deforestation represented by our randomized airborne campaigns, we find that forest degradation would account for a substantial portion of Brazilian carbon emissions were it considered in national budgets. Our study presents one of the first large-scale quantifications of carbon losses due to forest degradation from logging and fire.