Fire’s Latent Activity Monitoring and Evaluation through Thermography (FLAME-T)

Description

This repository presents FLAME-T, an annotated dataset of a prescribed burn conducted in Gran Canaria. This dataset is structured to aid in thermal imaging analysis for fire monitoring and evaluation. Dataset Composition: The FLAME-T dataset consists of approximately 2,640 thermal images, each captured with high precision using a terrestrial thermal camera system. The dataset was annotated using the You Only Look Once (YOLO) format, allowing for easy integration with object detection algorithms and machine learning models focused on fire behavior analysis and other related applications. Technical Specifications: File Format: JPEG, TXT Resolution: Ranges from 160x120 to 336x256 Cameras Used: FLIR Tau 2, FLIR A35, and FLIR Lepton Image Capture Protocol: The thermal images were captured from multiple geographic locations and varying perspectives of the same fire, providing a comprehensive view of the fire’s progression and intensity across different vantage points. Images are grouped in batches of 20 frames, each captured at 1-second intervals from a single perspective, enabling fine-grained temporal analysis of the fire’s latent activity. Geographical Information: Fire location: 27.990619, -15.518103, 737 m Point A: 27.997256, -15.514588, 768 m Point B: 27.997955, -15.510110, 789 m Point C: 27.995225, -15.505335, 769 m Point D: 27.992816, -15.521879, 861 m Point E: 28.000828, -15.517579, 971 m Point F: 27.999762, -15.515277, 951 m These coordinates allow users to accurately understand the location and elevation context of each image batch, facilitating spatial analysis of fire activity across different terrains. Attached to this repository is the dataset created and used during the work. If you wish to use the code sample to replicate our work, please use the link found in the 'Related links' section, which leads directly to the official GitHub of the paper.

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