TEMA AIIA_wildfire Dataset

General description of the dataset The TEMA AIIA_wildfire dataset is a collection of 2,236 natural disaster images designed for semantic segmentation, focusing on burnt areas, smoke, and fire. It aggregates and standardizes images from three distinct sources: the BLAZE classification dataset (https://aiia.csd.auth.gr/blaze-fire-classification-segmentation-dataset/), Finland’s wildfire dataset and Sardegna’s wildfire dataset. If one uses any part of these datasets in his/her work, he/she is kindly asked to cite the following paper: M. Siavrakas, C. Papaioannidis and I.Pitas, "BLAZE: A dataset for wildfire and burnt area UAV image classification and segmentation", IEEE International Conference on Image Processing (ICIP), Anchorage, Alaska, USA, 13-17 September, 2025. https://link.springer.com/article/10.1007/s00521-022-07467-z https://link.springer.com/article/10.1007/s00521-023-08260-2 https://www.sciencedirect.com/science/article/pii/S0924271623001831 https://zenodo.org/records/7944963 Dataset Structure The dataset is organized by source, each with standard train/validation splits containing .jpg images and corresponding .png label masks. The corresponding folder for each source are BLAZE (BLAZE1), Finland’s (KAHY) and Sardegna’s (RAS). Labels follow a four-class hierarchy (0: background, 1: burnt, 2: smoke, 3: fire). The final composition is 984 images from BLAZE ( 584 from KAHY, and 668 from RAS, split into 1,527 training and 655 validation images almost a 70 – 30% split. Details on acquiring the dataset can be found here.