Produção Nacional
Revisado por pares
Carbon dioxide spatial variability and dynamics for contrasting land uses in central Brazil agricultural frontier from remote sensing data
2022; Elsevier BV; Volume: 116; Linguagem: Inglês
10.1016/j.jsames.2022.103809
ISSN1873-0647
AutoresFernando Saragosa Rossi, Gustavo André de Araújo Santos, Luciano de Souza Maria, Thaís Lourençoni, Tatiane Deoti Pelissari, João Lucas Della-Silva, José Wagner Oliveira Júnior, Adriana de Avila e Silva, Mendelson Lima, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro, José Francisco de Oliveira‐Júnior, Newton La Scala, Carlos Antônio da Silva,
Tópico(s)Fire effects on ecosystems
ResumoGreenhouse gas (GHG) sources and sinks are an important global concern. Monitoring the spatiotemporal variations of GHG concentrations, particularly carbon dioxide (CO 2 ), 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 CO 2 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 (CO 2 ) dry air mole fraction in the atmosphere, set as X CO2 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 CO 2 flux in the SMT. The results showed that the temporal variability of CO 2 flux is correlated positively with rainfall, while X CO2 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 CO 2 occurred in the dry and rainy months, respectively, for X CO2 , which might be the result of differences in the vertical resolution of the CO 2 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 X CO2 but also CO 2 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 . • X CO2 is inversely related to rainfall, with highest concentration in drier periods. • Human actions in land use and land cover change increase atmospherical CO 2 . • Remote sensing to locate and understand the sources and sinks of carbon dioxide.
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