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Google Earth Engine (GEE) Forest Fire Detection and Pollutant Flow Analysis

Remote Sensing of the Forest Fire Pollutant Flow of the 2019 Australian Bushfires

Overview

This project analyzes the spread of forest fire pollutants (FFP) from the 2019 Australian bushfires using remote sensing data. The study focuses on tracking carbon monoxide (CO), nitrogen dioxide (NO₂), and particulate matter (PM) to understand how pollutants disperse through the atmosphere and impact Earth system processes.

Objective

To demonstrate the capability of remote sensing and Google Earth Engine (GEE) in detecting, mapping, and tracking forest fire pollutants over time and space.

Study Area

Eastern Australia, one of the most fire-prone regions globally, dominated by eucalyptus forests prone to recurrent bushfires.

Methodology

  • Collected satellite-based data of CO, NO₂, and PM from the 2019 bushfire events.
  • Processed and visualized the data using Google Earth Engine (GEE).
  • Analyzed pollutant flow patterns.
  • Evaluated interconnections between fire intensity, and pollutant load.

Tools and Datasets

  • Google Earth Engine (GEE)
  • Sentinel-5P (TROPOMI) for CO and NO₂
  • MODIS for fire detection and aerosol data
  • Python / Jupyter Notebook (optional for supporting analysis)

Key Findings

  • Forest fire pollutants exhibited long-range atmospheric transport influenced by global wind patterns.
  • Elevated CO, NO₂, and PM concentrations persisted even after active fire events ended.
  • Remote sensing enables effective pollutant tracking and environmental impact assessment during large-scale fires.

Publication

Published in: 2023 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)
Date of Conference: 10–13 December 2023
Date Added to IEEE Xplore: 09 April 2024
DOI: 10.1109/InGARSS59135.2023.10490389
Publisher: IEEE

Citation

Rohit P., Shivani S., Alka Singh.
Remote Sensing of the Forest Fire Pollutant Flow of the 2019 Australian Bushfires
Center for Wireless Networks & Applications,
Amrita Vishwa Vidyapeetham, Amritapuri, India.

Keywords

Forest fire pollutant, remote sensing, Google Earth Engine, Australian bushfires, carbon monoxide, nitrogen dioxide, particulate matter.

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GEE Wildfire Detection and Pollutant Flow Analysis

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