AIMC Topic: Wildfires

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Forest fire susceptibility mapping using multi-criteria decision making and machine learning models in the Western Ghats of India.

Journal of environmental management Mar 9, 2025
Forest fires have significantly increased over the last decade due to shifts in rainfall patterns, warmer summers, and long spells of dry weather events in the coastal regions. Assessment of susceptibility to forest fires has become an important mana...
Machine Learning Geographic Information Systems India Fires Forests Wildfires Decision Making Remote Sensing Technology
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Capsule neural network and adapted golden search optimizer based forest fire and smoke detection.

Scientific reports Feb 4, 2025
Forest fires represent a major risk to both ecosystems and human health that rising frequency of it exacerbates global warming. This study introduces an innovative methodology for detecting forest fires and smoke using an enhanced capsule neural netw...
Neural Networks, Computer Algorithms Deep Learning Humans Wildfires Smoke Fires Forests
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Spatial prediction of forest fires in India: a machine learning approach for improved risk assessment and early warning systems.

Environmental science and pollution research international Feb 1, 2025
Forest fires pose a significant ecological and environmental threat globally, and India has seen a marked increase in both the frequency and severity of these events in recent years. This has led to extensive damage to natural resources, including fo...
Machine Learning Wildfires Risk Assessment Climate Change Fires Forests India
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U3UNet: An accurate and reliable segmentation model for forest fire monitoring based on UAV vision.

Neural networks : the official journal of the International Neural Network Society Jan 30, 2025
Forest fires pose a serious threat to the global ecological environment, and the critical steps in reducing the impact of fires are fire warning and real-time monitoring. Traditional monitoring methods, like ground observation and satellite sensing, ...
Forests Wildfires Remote Sensing Technology Fires Unmanned Aerial Devices Algorithms Environmental Monitoring Neural Networks, Computer
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Evaluating Chemical Transport and Machine Learning Models for Wildfire Smoke PM: Implications for Assessment of Health Impacts.

Environmental science & technology Dec 18, 2024
Growing wildfire smoke represents a substantial threat to air quality and human health. However, the impact of wildfire smoke on human health remains imprecisely understood due to uncertainties in both the measurement of exposure of population to wil...
Machine Learning United States Smoke Humans Environmental Monitoring Particulate Matter Air Pollutants Wildfires
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Emulating Wildfire Plume Injection Using Machine Learning Trained by Large Eddy Simulation (LES).

Environmental science & technology Dec 3, 2024
Wildfires have a major influence on the Earth system, with costly impacts on society. Despite decades of research, wildfires are still challenging to represent in air quality and chemistry-climate models. Wildfire plume rise (injection) is one of tho...
Machine Learning Air Pollution Models, Theoretical Wildfires
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Machine learning estimates on the impacts of detection times on wildfire suppression costs.

PloS one Nov 20, 2024
As climate warming exacerbates wildfire risks, prompt wildfire detection is an essential step in designing an efficient suppression strategy, monitoring wildfire behavior and, when necessary, issuing evacuation orders. In this context, there is incre...
Climate Change Canada Wildfires Machine Learning Time Factors
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Predicting burn probability: Dimensionality reduction strategies enable accurate and computationally efficient metamodeling.

Journal of environmental management Oct 30, 2024
Predicting the probability that a given location will be burnt by a wildfire is an important part of understanding the risk that wildfires pose and how our management actions (e.g., prescribed burning) can reduce this risk. Existing methods to quanti...
Wildfires Probability Models, Theoretical Fires Neural Networks, Computer Machine Learning
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Deep learning models map rapid plant species changes from citizen science and remote sensing data.

Proceedings of the National Academy of Sciences of the United States of America Sep 5, 2024
Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learni...
California Citizen Science Climate Change Humans Conservation of Natural Resources Remote Sensing Technology Forests Ecosystem Plants Wildfires Deep Learning Biodiversity
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Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine.

Journal of environmental management Apr 26, 2024
Forest fires threaten global ecosystems, socio-economic structures, and public safety. Accurately assessing forest fire susceptibility is critical for effective environmental management. Supervised learning methods dominate this assessment, relying o...
Wildfires Ecosystem Fires Support Vector Machine Forests China Supervised Machine Learning
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