Data

Modelling Bushfire Severity and Predicting Future Trends in Australia

Central Queensland University
Shouthiri Partheepan (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25946/31449037.v1&rft.title=Modelling Bushfire Severity and Predicting Future Trends in Australia&rft.identifier=10.25946/31449037.v1&rft.publisher=Central Queensland University&rft.description=The Modelling Bushfire Severity and Predicting Future Trends in Australia dataset is a multi-source geospatial dataset developed to analyse bushfire severity across Australia from 2012 to 2023. It integrates Landsat 5, 7, and 8 satellite imagery with NASA FIRMS fire data, along with derived spectral indices such as NDVI, NBR, and dNBR. The dataset also incorporates topographical features (elevation, slope, TPI) and climatic variables (temperature, precipitation, soil moisture) to support predictive modelling. The final GeoTIFF dataset enables large-scale fire severity mapping and machine learning-based bushfire trend prediction across diverse Australian ecosystems.&rft.creator=Shouthiri Partheepan&rft.date=2026&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_subject=Deep learning&rft_subject=Modelling and simulation&rft_subject=Reinforcement learning&rft_subject=Planning and decision making&rft_subject=Autonomous agents and multiagent systems&rft_subject=Bushfire severity&rft_subject=Future Trends&rft_subject=Satellite Imagery&rft_subject=Machine Learning&rft.type=dataset&rft.language=English Access the data
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The Modelling Bushfire Severity and Predicting Future Trends in Australia dataset is a multi-source geospatial dataset developed to analyse bushfire severity across Australia from 2012 to 2023. It integrates Landsat 5, 7, and 8 satellite imagery with NASA FIRMS fire data, along with derived spectral indices such as NDVI, NBR, and dNBR. The dataset also incorporates topographical features (elevation, slope, TPI) and climatic variables (temperature, precipitation, soil moisture) to support predictive modelling. The final GeoTIFF dataset enables large-scale fire severity mapping and machine learning-based bushfire trend prediction across diverse Australian ecosystems.

Data time period: 2012-02-01 to 2023-12-31

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Subjects
Autonomous agents and multiagent systems | Bushfire severity | Deep learning | Future Trends | Machine Learning | Modelling and simulation | Planning and decision making | Reinforcement learning | Satellite Imagery |

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