Carbon dioxide spatial variability and dynamics for contrasting land uses in central Brazil agricultural frontier from remote sensing data

Greenhouse gas (GHG) sources and sinks are an important global concern. Monitoring the spatiotemporal variations of GHG concentrations, particularly carbon dioxide (CO2), is crucial for identifying potential sources and sinks and moving toward a sustainable future. Therefore, via a time-series of remote data and multispectral images, this study evaluates the CO2 spatiotemporal dynamics and related factors during 2015-2018 in one of the world's main agricultural frontier areas, the state of Mato Grosso (SMT), Brazil, which is both experiencing continued deforestation and attempting to achieve sustainable food production. In this study, data was obtained from the measurement of column-averaged carbon dioxide (CO2) dry air mole fraction in the atmosphere, set as XCO2 from Orbiting Carbon Observatory-2 satellite from January 2015 to December 2018. The enhanced vegetation index data were obtained from the Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor, and rainfall data were obtained from the Climate Hazards Group InfraRed Precipitation with Station dataset. From a series of Landsat-8 satellite images, it was possible to distinguish land use and land cover classes and estimate the CO2 flux in the SMT. The results showed that the temporal variability of CO2 flux is correlated positively with rainfall, while XCO2 is negatively correlated with rainfall. Regarding spatial variability, we observed that forest areas that were converted to other land uses resulted in higher values that characterize with sources, and that the highest and lowest average concentrations of CO2 occurred in the dry and rainy months, respectively, for XCO2, which might be the result of differences in the vertical resolution of the CO2 column and scale. In contrast, areas with large continuous forest areas tended to have lower values and contribute positively to the carbon balance as sinks, thereby mitigating climate change impacts. Therefore, not only XCO2 but also CO2 flux are directly related to changes in land use and land cover (LULC) in complex systems that are affected by climatic variables and processes, such as photosynthesis and soil respiration.

Automated summary

This study evaluates the spatiotemporal dynamics of CO2 and related factors in the state of Mato Grosso, Brazil from 2015 to 2018. The results show that CO2 flux is positively correlated with rainfall, while XCO2 is negatively correlated with rainfall. Forest areas converted to other land uses have higher CO2 concentrations, while continuous forest areas contribute positively to the carbon balance.