AIMC Topic: Wildfires

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Evaluating Chemical Transport and Machine Learning Models for Wildfire Smoke PM: Implications for Assessment of Health Impacts.

Environmental science & technology
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...

Emulating Wildfire Plume Injection Using Machine Learning Trained by Large Eddy Simulation (LES).

Environmental science & technology
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 estimates on the impacts of detection times on wildfire suppression costs.

PloS one
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...

Predicting burn probability: Dimensionality reduction strategies enable accurate and computationally efficient metamodeling.

Journal of environmental management
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...

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
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...

Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine.

Journal of environmental management
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...

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

PloS one
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...

Estimation of potential wildfire behavior characteristics to assess wildfire danger in southwest China using deep learning schemes.

Journal of environmental management
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...

Deep learning-based burned forest areas mapping via Sentinel-2 imagery: a comparative study.

Environmental science and pollution research international
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...

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
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...