ArticleScientific data2025
Boreal Forest Fire: UAV-collected Wildfire Detection and Smoke Segmentation Dataset.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Detecting Wildfire Smoke Onset from Fixed View Camera Networks.Sensors (Basel, Switzerland) · 2026Article
- BGC-LiteNet: BeiDou grid code embedded lightweight neural architecture for real-time UAV fire detection and localization.Scientific reports · 2026Article
- Boreal Forest Fire: UAV-collected Wildfire Detection and Smoke Segmentation Dataset.Scientific data · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Automated image-based wildfire detection suffers from a lack of open-access data, especially data with annotations. Our dataset targets the gap by providing human and computer vision foundation-model co-annotated images from an uncrewed aerial vehicle (UAV) perspective from Finnish boreal forest environments. The images and videos were collected at multiple prescribed burning events, and the data were used to successfully train wildfire detection models in our previous studies, proving their value for the task. The Boreal Forest Fire dataset contains three sections: images with bounding box annotations, video clips with labels and images with segmentation masks. Alongside the data, we have released code, ensuring that the data is simple to use.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.