Changes in Carbon Dioxide Balance Associated with Land Use and Land Cover in Brazilian Legal Amazon Based on Remotely Sensed Imagery

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The Amazon region comprises the largest tropical forest on the planet and is responsible for absorbing huge amounts of CO2 from the atmosphere. However, changes in land use and cover have contributed to an increase in greenhouse gas emissions, especially CO2, and in endangered indigenous lands and protected areas in the region. The objective of this study was to detect changes in CO2 emissions and removals associated with land use and land cover changes in the Brazilian Legal Amazon (BLA) through the analysis of multispectral satellite images from 2009 to 2019. The Gross Primary Production (GPP) and CO2Flux variables were estimated by the MODIS sensor onboard Terra and Aqua satellite, representing carbon absorption by vegetation during the photosynthesis process. Atmospheric CO2 concentration was estimated from the GOSAT satellite. The variables GPP and CO2Flux showed the effective flux of carbon in the BLA to atmosphere, which were weakly correlated with precipitation (r = 0.191 and 0.133). The forest absorbed 211.05 TgC annually but, due to its partial conversion to other land uses, the loss of 135,922.34 km2 of forest area resulted in 5.82 TgC less carbon being absorbed. Pasture and agriculture, which comprise the main land conversions, increased by 100,340.39 km2 and absorbed 1.32 and 3.19 TgC less, and emitted close to twice more, than forest in these areas. Atmospheric CO2 concentrations increased from 2.2 to 2.8 ppm annually in BLA, with hotspots observed in the southeast Amazonia, and CO2 capture by GPP showed an increase over the years, mainly after 2013, in the north and west of the BLA. This study brings to light the carbon dynamics, by GPP and CO2Flux models, as related to the land use and land cover in one of the biggest world carbon reservoirs, the Amazon, which is also important to fulfillment of international agreements signed by Brazil to reduce greenhouse gas emissions and for biodiversity conservation and other ecosystem services in the region.




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Remote Sensing, v. 15, n. 11, 2023.

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