Global and regional trends and drivers of fire under climate change

MW Jones, JT Abatzoglou, S Veraverbeke… - Reviews of …, 2022 - Wiley Online Library
Recent wildfire outbreaks around the world have prompted concern that climate change is
increasing fire incidence, threatening human livelihood and biodiversity, and perpetuating …

Combustion machine learning: Principles, progress and prospects

M Ihme, WT Chung, AA Mishra - Progress in Energy and Combustion …, 2022 - Elsevier
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …

A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities

W Han, X Zhang, Y Wang, L Wang, X Huang… - ISPRS Journal of …, 2023 - Elsevier
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …

Comprehensive survey of artificial intelligence techniques and strategies for climate change mitigation

Z Amiri, A Heidari, NJ Navimipour - Energy, 2024 - Elsevier
With the gallo** progress of the changing climates all around the world, Machine Learning
(ML) approaches have been prevalently studied in many types of research in this area. ML is …

A review of earth artificial intelligence

Z Sun, L Sandoval, R Crystal-Ornelas… - Computers & …, 2022 - Elsevier
In recent years, Earth system sciences are urgently calling for innovation on improving
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …

Flash-flood susceptibility map** based on XGBoost, random forest and boosted regression trees

R Abedi, R Costache… - Geocarto …, 2022 - Taylor & Francis
Historical exploration of flash flood events and producing flash-flood susceptibility maps are
crucial steps for decision makers in disaster management. In this article, classification and …

An improved forest fire detection method based on the detectron2 model and a deep learning approach

AB Abdusalomov, BMDS Islam, R Nasimov… - Sensors, 2023 - mdpi.com
With an increase in both global warming and the human population, forest fires have
become a major global concern. This can lead to climatic shifts and the greenhouse effect …

Machine learning for risk and resilience assessment in structural engineering: Progress and future trends

X Wang, RK Mazumder, B Salarieh… - Journal of Structural …, 2022 - ascelibrary.org
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

A brief review of machine learning algorithms in forest fires science

R Alkhatib, W Sahwan, A Alkhatieb, B Schütt - Applied Sciences, 2023 - mdpi.com
Due to the harm forest fires cause to the environment and the economy as they occur more
frequently around the world, early fire prediction and detection are necessary. To anticipate …

Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting

S Cheng, IC Prentice, Y Huang, Y **, YK Guo… - Journal of …, 2022 - Elsevier
The large and catastrophic wildfires have been increasing across the globe in the recent
decade, highlighting the importance of simulating and forecasting fire dynamics in near real …