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A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …
environment has become essential for many countries' sustainable development. As various …
Global and regional trends and drivers of fire under climate change
Recent wildfire outbreaks around the world have prompted concern that climate change is
increasing fire incidence, threatening human livelihood and biodiversity, and perpetuating …
increasing fire incidence, threatening human livelihood and biodiversity, and perpetuating …
Combustion machine learning: Principles, progress and prospects
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 …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
A review of practical ai for remote sensing in earth sciences
Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for
revolutionizing data analysis and applications in many domains of Earth sciences. This …
revolutionizing data analysis and applications in many domains of Earth sciences. This …
An improved forest fire detection method based on the detectron2 model and a deep learning approach
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 …
become a major global concern. This can lead to climatic shifts and the greenhouse effect …
Comprehensive survey of artificial intelligence techniques and strategies for climate change mitigation
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 …
(ML) approaches have been prevalently studied in many types of research in this area. ML is …
A review of earth artificial intelligence
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 …
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …
A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management
Wildfires have emerged as one of the most destructive natural disasters worldwide, causing
catastrophic losses. These losses have underscored the urgent need to improve public …
catastrophic losses. These losses have underscored the urgent need to improve public …
Flash-flood susceptibility map** based on XGBoost, random forest and boosted regression trees
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 …
crucial steps for decision makers in disaster management. In this article, classification and …
Machine learning for risk and resilience assessment in structural engineering: Progress and future trends
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …
to increased exposure and vulnerability of structural and infrastructure systems to hazards …