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This paper presents a comprehensive Investigation of Satellite data for Monitoring Air quality through Remote sensing Technology tool (ISMART tool). Specifically, it utilizes data from the Sentinel-5 precursor (Sentinel-5p) Tropospheric Monitoring Instrument (TROPOMI) datasets to monitor the columnar surface of co gas across India, with a focus on high-pollution regions. After rigorous data processing, essential attributes were extracted to monitor the columnar CO level. Haversine formula is employed for specific area monitoring, Basemap is used to visualize the pollution levels and machine learning models (ARIMA, LSTM) for precise monitoring and forecasting. This research culminated in a user-friendly website, built with the Django framework, where users can easily identify pollution hotspots by inputting specific parameters. Ultimately, this paper underscores the cost-effectiveness and vast coverage advantages of remote sensing over traditional ground-level instruments, urging governments to harness this technology for timely interventions against pollution.

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Investigation of Satellite Data for Monitoring Air Quality Over Remote Sensing Technology

  • 会议论文

  • 发表日期：

    2025年

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  • Panimalar Kathiroli,
  • V. Vijayalakshmi,
  • Piyush Gopal,
  • Sivananda Panda

摘要

This paper presents a comprehensive Investigation of Satellite data for Monitoring Air quality through Remote sensing Technology tool (ISMART tool). Specifically, it utilizes data from the Sentinel-5 precursor (Sentinel-5p) Tropospheric Monitoring Instrument (TROPOMI) datasets to monitor the columnar surface of co gas across India, with a focus on high-pollution regions. After rigorous data processing, essential attributes were extracted to monitor the columnar CO level. Haversine formula is employed for specific area monitoring, Basemap is used to visualize the pollution levels and machine learning models (ARIMA, LSTM) for precise monitoring and forecasting. This research culminated in a user-friendly website, built with the Django framework, where users can easily identify pollution hotspots by inputting specific parameters. Ultimately, this paper underscores the cost-effectiveness and vast coverage advantages of remote sensing over traditional ground-level instruments, urging governments to harness this technology for timely interventions against pollution.