Estimation of Carbon Fluxes from a City at 1 km × 1 km Grid Using Remotely Sensed Data

In today’s world, environmental pollution is worsening and having detrimental effects on the environment. The current focus of human endeavors is aimed at reducing this pollution to ensure a sustainable future for our planet. In this pursuit, we are striving to create a framework that can estimate the carbon fluxes within a city. The accurate estimation of carbon fluxes from cities is crucial for understanding and mitigating their impact on global greenhouse gas emissions. This paper presents a novel approach for estimating carbon fluxes at a spatial resolution of 1 km x 1 km grids using remotely sensed data. Our research relies on indicators such as population and impervious surface area as proxies for estimating carbon dioxide (CO
2
) levels with a linear regression model. To test the generality of the method and models, we have validated our grid-model coefficients on point data and vice versa.