Data fusion based monitoring of the air pollution evolution in Southeast Asia using satellite observations

Abstract

This study addresses the escalating issue of air pollution in Southeast Asia, which significantly affects human health, agricultural productivity, and broader ecological systems. Utilizing advanced satellite observations to obtain a comprehensive understanding of air pollution dynamics, the research emphasizes the integration of data from various satellite sources, including the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). This integrated approach allows for a broader and more accurate assessment of air quality over time and space compared to individual satellite data sets. The primary focus of the research is to refine data fusion methodologies, enhancing the accuracy and reliability of air pollution monitoring. The results are vital for aiding policymakers and stakeholders in making informed decisions to effectively mitigate air pollution in the region. Improved data accuracy is crucial for assessing the effectiveness of air quality regulations and policies and for developing targeted strategies for emission reduction from various pollution sources such as vehicles, industries, and agricultural activities. The project not only contributes to the scientific understanding of air pollution dynamics using cutting-edge satellite technology but also provides actionable insights that can drive policy and community actions towards healthier and more sustainable environments in Southeast Asia.