AIDERv2 Dataset

Overview

AIDERv2 (Aerial Image Dataset for Emergency Response Applications) is an aerial image classification dataset for disaster recognition. It contains 16,723 UAV and aerial images across four classes:

• Earthquake
• Flood
• Fire
• Normal

Statistics

Class	Train	Validation	Test	Total
Earthquake	1,927	239	239	2,405
Flood	4,063	505	502	5,070
Fire	3,509	439	436	4,384
Normal	3,900	487	477	4,864
Total	13,399	1,670	1,654	16,723

Image Format

• RGB Images
• Resolution: 224 × 224 pixels
• Dataset split into Train, Validation, and Test sets

Applications

• Disaster Recognition
• Aerial Image Classification
• UAV-Based Emergency Response
• Deep Learning and Computer Vision Research

Source

Original dataset:

https://zenodo.org/records/10891054

Citation

@inproceedings{shianios2023aider,
  title={A Benchmark and Investigation of Deep-Learning-Based Techniques for Detecting Natural Disasters in Aerial Images},
  author={Shianios, Demetris and Kyrkou, Christos and Kolios, Panayiotis S.},
  booktitle={Computer Analysis of Images and Patterns (CAIP)},
  year={2023},
  publisher={Springer}
}