The Alaska Reference Database originated as the standalone Alaska Fire Effects Reference Database, a ProCite reference database maintained by former BLM-Alaska Fire Service Fire Ecologist Randi Jandt. It was expanded under a Joint Fire Science Program grant for the FIREHouse project (The Northwest and Alaska Fire Research Clearinghouse). It is now maintained by the Alaska Fire Science Consortium and FRAMES, and is hosted through the FRAMES Resource Catalog. The database provides a listing of fire research publications relevant to Alaska and a venue for sharing unpublished agency reports and works in progress that are not normally found in the published literature.
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Topic
Year
Displaying 1 - 5 of 5
El-Madafri, Peña, Olmedo-Torre
This study introduces a novel hierarchical domain-adaptive learning framework designed to enhance wildfire detection capabilities, addressing the limitations inherent in traditional convolutional neural networks across varied forest environments. The framework innovatively…
Year: 2024
Type: Document
Source: FRAMES
Badhan, Shamsaei, Ebrahimian, Bebis, Lareau, Rowell
The rising severity and frequency of wildfires in recent years in the United States have raised numerous concerns regarding the improvement in wildfire emergency response management and decision-making systems, which require operational high temporal and spatial resolution…
Year: 2024
Type: Document
Source: FRAMES
Fillmore, McCaffrey, Bean, Evans, Iniguez, Thode, Smith, Thompson
Background: The decision making process undertaken during wildfire responses is complex and prone to uncertainty. In the US, decisions federal land managers make are influenced by numerous and often competing factors.
Aims: To assess and validate the presence of decision factors…
Year: 2024
Type: Document
Source: FRAMES
Erni, Wang, Swystun, Taylor, Parisien, Robinne, Eddy, Oliver, Armitage, Flannigan
Large and intense wildfires are an integral part of many Canadian landscapes, playing a critical role in ecosystem dynamics. However, the recent catastrophic fire seasons have highlighted the threat that wildfires can pose to human communities. Identifying areas at higher fire…
Year: 2024
Type: Document
Source: FRAMES
Qayyum, Jamil, Alsboui, Hijjawi
Background: Understanding the intricacies of wildfire impact across diverse geographical landscapes necessitates a nuanced comprehension of fire dynamics and areas of vulnerability, particularly in regions prone to high wildfire risks. Machine learning (ML) stands as a…
Year: 2024
Type: Document
Source: FRAMES