Application of remote sensing in evaluating the PM 10 concentration in Ho Chi Minh city

Abstract

Nowadays, air pollution is a serious problem for the entire world, but especially in developing countries like Vietnam. For monitoring and managing air quality, scientists have successfully used different technologies such as predictive models, interpolation, and monitoring, however; these methods require a large amount of input data to simulate. Further, the results from spatial simulations are not detailed and have deviations from reality due to factors such as terrain changes, wind direction, and rainfall. Based on the physical index extracted from remote sensing images like radiation and reflection values, the aerosol optical depth (AOD) can be extracted. In this work, a regression equation is constructed and the correlation between the extracted AOD and measured PM₁₀ concentration is found. The results show that PM₁₀ and AOD are best correlated with a non-linear regression equation. This work also shows that the concentration of PM₁₀ in Ho Chi Minh city is distributed mainly along the outskirts of the city, which has many highways, industrial parks, factories, and enterprises.