Published September 9, 2024 | Version 1.0.0-beta.2
Dataset Open

FireMan-UAV-RGBT

Description

The FireMan-UAV-RGBT dataset is a collection of UAV-captured RGB and thermal videos aimed at improving wildfire detection methods in boreal forests. Captured during four controlled burns in Finland from 2022 to 2023, the dataset includes 34 RGB videos and 20 RGB-Thermal paired videos. These high-resolution images have been annotated using both manual and semi-automatic methods to ensure accuracy.

Using advanced drone technology, including the DJI Matrice 30T and Matrice 300 with Zenmuse H20T and H20N cameras, the dataset provides essential visual and thermal data for early fire detection and management. The annotations, formatted in YOLO, support machine learning applications in wildfire detection.

To validate the dataset, state-of-the-art deep learning models were trained, showing the reliability and applicability of the FireMan-UAV-RGBT dataset in real-world scenarios. This dataset is publicly available to support researchers in developing new methods for wildfire management.




Files

Binary.zip

Files (39.4 GB)

Name Size Download all
md5:37cbb82037c272bad38565cdae8dd002
6.4 GB Preview Download
md5:6936a68f2695f8b763ffa6a419455f6b
1.4 kB Preview Download
md5:7877d8059cd3559e469d3af7ee1410c9
510.1 kB Preview Download
md5:b354528d53914a1b2dafe974bd75cb1f
526.8 kB Preview Download
md5:ddc790b901bfc51e196976145f49ea5d
33.0 GB Preview Download
md5:c2f66e39c24a7d291c8299d591e5302e
4.8 kB Preview Download

Additional details

Funding

Research Council of Finland
6G Flagship 346208
Research Council of Finland
Unmanned aerial systems based solutions for real-time management of wildfires 348008

Dates

Updated
2024-09-09

Software

Programming language
Python
Development Status
Active