Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data
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Abstract (arXiv)
Identifying regions that have high likelihood for wildfires is a key component of land and forestry management and disaster preparedness. We create a data set by aggregating nearly a decade of remote-sensing data and historical fire records to predict wildfires. This prediction problem is framed as three machine learning tasks. Results are compared and analyzed for four different deep learning models to estimate wildfire likelihood. The results demonstrate that deep learning models can successfully identify areas of high fire likelihood using aggregated data about vegetation, weather, and topography with an AUC of 83%.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Oct 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 3; 2024: 4; 2025: 2; 2026: 2.
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- 2021Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Datacited by 41
- 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterraneancited by 18
- 2022Deep Learning for Global Wildfire Forecastingcited by 11
- 2024SegNet: A Segmented Deep Learning based Convolutional Neural Network Approach for Drones Wildfire Detectioncited by 4
- 2025Uncertainty-Aware Deep Learning for Wildfire Danger Forecastingcited by 4
- 2022Multi-time Predictions of Wildfire Grid Map using Remote Sensing Local Datacited by 2
- 2023Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Managementcited by 2
- 2023Rapid Deforestation and Burned Area Detection using Deep Multimodal Learning on Satellite Imagerycited by 1
- 2024Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scalecited by 1
- 2024Next day fire prediction via semantic segmentationcited by 0
- 2024Enhancing Tree Type Detection in Forest Fire Risk Assessment: Multi-Stage Approach and Color Encoding with Forest Fire Risk Evaluation Framework for UAV Imagerycited by 0
- 2025Comparing Next-Day Wildfire Predictability of MODIS and VIIRS Satellite Datacited by 0
2 more
- 2026Physics-guided spatiotemporal neural models for fuel density prediction8 Jul 2026
- 2026N-Tree Diffusion for Long-Horizon Wildfire Risk Forecasting7 Mar 2026
- 2025Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting29 Sep 2025
- 2025Comparing Next-Day Wildfire Predictability of MODIS and VIIRS Satellite Data11 Mar 2025
- 2024Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale30 Aug 2024
- 2024Enhancing Tree Type Detection in Forest Fire Risk Assessment: Multi-Stage Approach and Color Encoding with Forest Fire Risk Evaluation Framework for UAV Imagery27 Jul 2024
- 2024Next day fire prediction via semantic segmentation20 Mar 2024
- 2024SegNet: A Segmented Deep Learning based Convolutional Neural Network Approach for Drones Wildfire Detection29 Feb 2024
- 2023Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management2 Oct 2023
- 2023Rapid Deforestation and Burned Area Detection using Deep Multimodal Learning on Satellite Imagery10 Jul 2023
- 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean8 Jun 2023
- 2022Deep Learning for Global Wildfire Forecasting1 Nov 2022
- 2021Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Datacited by 41
- 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterraneancited by 18
- 2022Deep Learning for Global Wildfire Forecastingcited by 11
- 2024SegNet: A Segmented Deep Learning based Convolutional Neural Network Approach for Drones Wildfire Detectioncited by 4
- 2025Uncertainty-Aware Deep Learning for Wildfire Danger Forecastingcited by 4
- 2022Multi-time Predictions of Wildfire Grid Map using Remote Sensing Local Datacited by 2
- 2023Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Managementcited by 2
- 2023Rapid Deforestation and Burned Area Detection using Deep Multimodal Learning on Satellite Imagerycited by 1
- 2024Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scalecited by 1
- 2024Next day fire prediction via semantic segmentationcited by 0
- 2024Enhancing Tree Type Detection in Forest Fire Risk Assessment: Multi-Stage Approach and Color Encoding with Forest Fire Risk Evaluation Framework for UAV Imagerycited by 0
- 2025Comparing Next-Day Wildfire Predictability of MODIS and VIIRS Satellite Datacited by 0
12 most cited of 13 All 13 (JSON)
- 2026Physics-guided spatiotemporal neural models for fuel density prediction8 Jul 2026
- 2025Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting29 Sep 2025
- 2025Comparing Next-Day Wildfire Predictability of MODIS and VIIRS Satellite Data11 Mar 2025
- 2024Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale30 Aug 2024
- 2024Enhancing Tree Type Detection in Forest Fire Risk Assessment: Multi-Stage Approach and Color Encoding with Forest Fire Risk Evaluation Framework for UAV Imagery27 Jul 2024
- 2024Next day fire prediction via semantic segmentation20 Mar 2024
- 2024SegNet: A Segmented Deep Learning based Convolutional Neural Network Approach for Drones Wildfire Detection29 Feb 2024
- 2023Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management2 Oct 2023
- 2023Rapid Deforestation and Burned Area Detection using Deep Multimodal Learning on Satellite Imagery10 Jul 2023
- 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean8 Jun 2023
- 2022Deep Learning for Global Wildfire Forecasting1 Nov 2022
- 2022Multi-time Predictions of Wildfire Grid Map using Remote Sensing Local Data15 Sep 2022
12 newest of 13 All 13 (JSON)