AIMC Topic: Wildfires

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Development of a deep learning-based surveillance system for forest fire detection and monitoring using UAV.

PloS one Mar 12, 2024
This study presents a surveillance system developed for early detection of forest fires. Deep learning is utilized for aerial detection of fires using images obtained from a camera mounted on a designed four-rotor Unmanned Aerial Vehicle (UAV). The o...
Artificial Intelligence Algorithms Deep Learning Wildfires Unmanned Aerial Devices
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Estimation of potential wildfire behavior characteristics to assess wildfire danger in southwest China using deep learning schemes.

Journal of environmental management Jan 5, 2024
Accurate estimation of potential wildfire behavior characteristics (PWBC) can improve wildfire danger assessment. However, wildfire behavior has been estimated by most fire spread models with immeasurable uncertainties and difficulties in large-scale...
Artificial Intelligence Deep Learning Fires Wildfires Conservation of Natural Resources China Reactive Oxygen Species
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Deep learning-based burned forest areas mapping via Sentinel-2 imagery: a comparative study.

Environmental science and pollution research international Dec 19, 2023
In order to evaluate the effects of forest fires on the dynamics of the function and structure of ecosystems, it is necessary to determine burned forest areas with high accuracy, effectively, economically, and practically using satellite images. Extr...
Wildfires Deep Learning Bayes Theorem Algorithms Ecosystem
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Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.

Journal of exposure science & environmental epidemiology Oct 17, 2023
BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophag...
Air Pollution Particulate Matter Particle Size Air Pollutants Soot Smoke Environmental Exposure Wildfires Male Middle Aged Lung Carbon Female Adult Algorithms Macrophages Humans Artificial Intelligence
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Use of machine learning as a tool for determining fire management units in the brazilian atlantic forest.

Anais da Academia Brasileira de Ciencias Apr 28, 2023
Geoprocessing techniques are generally applied in natural disaster risk management due to their ability to integrate and visualize different sets of geographic data. The objective of this study was to evaluate the capacity of classification and regre...
Brazil Wildfires Machine Learning Algorithms
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Deep Learning and Transformer Approaches for UAV-Based Wildfire Detection and Segmentation.

Sensors (Basel, Switzerland) Mar 3, 2022
Wildfires are a worldwide natural disaster causing important economic damages and loss of lives. Experts predict that wildfires will increase in the coming years mainly due to climate change. Early detection and prediction of fire spread can help red...
Deep Learning Fires Wildfires Climate Change
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Forest fire detection system using wireless sensor networks and machine learning.

Scientific reports Jan 7, 2022
Forest fires have become a major threat around the world, causing many negative impacts on human habitats and forest ecosystems. Climatic changes and the greenhouse effect are some of the consequences of such destruction. Interestingly, a higher perc...
Disaster Planning Wireless Technology Forests Wildfires Regression Analysis Machine Learning Remote Sensing Technology
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A Decentralized Fuzzy Rule-Based Approach for Computing Topological Relations between Spatial Dynamic Continuous Phenomena with Vague Boundaries Using Sensor Data.

Sensors (Basel, Switzerland) Oct 14, 2021
Sensor networks (SN) are increasingly used for the observation and monitoring of spatiotemporal phenomena and their dynamics such as pollution, noise and forest fires. In multisensory systems, a sensor node may be equipped with different sensing unit...
Wildfires Fuzzy Logic
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Extreme fire weather is the major driver of severe bushfires in southeast Australia.

Science bulletin Oct 5, 2021
In Australia, the proportion of forest area that burns in a typical fire season is less than for other vegetation types. However, the 2019-2020 austral spring-summer was an exception, with over four times the previous maximum area burnt in southeast ...
Forests Wildfires Humans Fires Australia Weather
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Emulation of wildland fire spread simulation using deep learning.

Neural networks : the official journal of the International Neural Network Society Apr 20, 2021
Numerical simulation of wildland fire spread is useful to predict the locations that are likely to burn and to support decision in an operational context, notably for crisis situations and long-term planning. For short-term, the computational time of...
Wildfires Forecasting France Computer Simulation Geographic Mapping Deep Learning Time Factors
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