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Topic
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Year
Displaying 1 - 3 of 3
Massive wildfires have become more frequent, seriously threatening the Earth’s ecosystems and human societies. Recognizing smoke from forest fires is critical to extinguishing them at an early stage. However, edge devices have low computational accuracy and suboptimal real-time…
Person:
Year: 2024
Type: Document
Source: FRAMES
Topic(s): Emissions and Smoke, Fire Occurrence, Models
Region(s): International
Keywords: China, YOLOv8, lightweight model, smoke detection, SimAmazonia, BiFPN - bidirectional feature pyramid network
Global climate change and extreme weather has a profound impact on wildfire, and it is of great importance to explore wildfire patterns in the context of global climate change for wildfire prevention and management. In this paper, a wildfire spatial prediction model based on…
Person:
Year: 2024
Type: Document
Source: FRAMES
Topic(s): Climate, Emissions and Smoke, Fire Behavior, Fire Occurrence, Fire Prevention, Models, Weather
Region(s): Alaska, California, Eastern, Great Basin, Hawaii, Northern Rockies, Northwest, Rocky Mountain, Southern, Southwest, International, National
Keywords: fire management, GFED - Global Fire Emissions Database, convolutional neural network, area burned
Climate change and human activity have increased fires in India. Fine particulate matter (PM2.5) is released into the atmosphere by stubble burning in Punjab and Haryana and forest fires in the north-eastern and central areas of the country. Accurate short-term PM2.5 estimates…
Person:
Year: 2024
Type: Document
Source: FRAMES
Topic(s): Emissions and Smoke, Fire Occurrence, Models
Region(s): International
Keywords: fire forecasting, deep learning, air pollution, LSTM - long short-term memory, India, PM2.5, fine particulate matter