youngsun05/SDSU_MidWest_Flood_2019

SDSU Midwest Flood Dataset 2019

This dataset provides a benchmark for flood detection in satellite imagery. It contains true-color satellite images from the 2019 Midwest USA flooding event, with each image paired with a binary mask indicating flooded areas.

Paper

If you use this dataset in your research or project, please cite the following paper:

A Novel Dataset for Flood Detection Robust to Seasonal Changes in Satellite Imagery Youngsun Jang, Dongyoun Kim, Chulwoo Pack, and Kwanghee Won Presented at the ACM RACS 2024 conference (Pompei, Italy, November 5–8, 2024)

• arXiv version

Note: This paper was presented at ACM RACS 2024, but the session was not published in the official ACM proceedings. This Hugging Face repository and the arXiv version serve as the official references.

Dataset Contents

• Images: True-color satellite imagery
• Masks: Binary masks for flood areas
• States covered: Iowa, Kansas, Montana, Nebraska, South Dakota
• Images per location: 10

Usage

You can load this dataset directly using Hugging Face Datasets:

from datasets import load_dataset

dataset = load_dataset("youngsun05/SDSU_MidWest_Flood_2019")

Citation

If you use this dataset, please cite:

@misc{jang2024midwestflood,
  title={A Novel Dataset for Flood Detection Robust to Seasonal Changes in Satellite Imagery},
  author={Youngsun Jang and Dongyoun Kim and Chulwoo Pack and Kwanghee Won},
  year={2024},
  note={Presented at ACM RACS 2024. Available at \url{https://huggingface.co/datasets/youngsun05/SDSU_MidWest_Flood_2019} and \url{https://arxiv.org/abs/2507.23193}},
}

License

This dataset is distributed under the CC-BY-4.0 License, allowing sharing and adaptation with appropriate credit.

Links

• Dataset GitHub Repository
• arXiv Paper