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BlessemFlood21

The BlessemFlood21 dataset was created by the Fraunhofer Institute for Image Processing and other institutions, focusing on high‑resolution RGB images of non‑coastal flood scenes. It contains 4,623 images, each 512×512 pixels, captured by a drone after the 2021 Erftstadt‑Blessem flood event. Detailed water masks were generated using semi‑supervised human‑in‑the‑loop techniques, primarily for training and testing deep‑learning models to support flood detection and emergency response.

Updated 7/6/2024
arXiv

Description

Dataset Overview

Dataset Title

BlessemFlood21: Advancing Flood Analysis with a High‑Resolution Georeferenced Dataset for Humanitarian Aid Support

Dataset Description

The BlessemFlood21 dataset aims to promote research on flood detection tools. It comprises high‑resolution, georeferenced RGB‑NIR images captured during the 2021 Erftstadt‑Blessem flood event, supplemented with detailed water masks obtained via semi‑supervised human‑in‑the‑loop techniques. The dataset is used to evaluate deep‑learning models for semantic segmentation, providing high‑resolution RGB data and a benchmark for RGB‑based flood detection algorithms.

Dataset Type

Image

Release Date

January 2024

Identifier

Contributors

  • Polushko, Vladyslav
  • Weinmann, Andreas
  • März, Thomas
  • Rauhut, Markus
  • Jenal, Alexander
  • Weber, Immanuel
  • Rösch, Ronald
  • Hatic, Damjan
  • Bongartz, Jens

Keywords

  • Remote Sensing
  • Humanitarian Aid Support
  • Deep Learning
  • Water Detection Dataset

Files

  • Filename: ortho_blessem_20210718_mask_v.01.24.tif
    • Size: 21.55 MB
    • Format: TIFF
  • Filename: ortho_blessem_20210718_rgb_v.01.24.tif
    • Size: 3.12 GB
    • Format: TIFF

License

The dataset is available under the Creative Commons Attribution‑NonCommercial‑ShareAlike 4.0 International License.

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Topics

Flood Detection
Deep Learning

Source

Organization: arXiv

Created: 7/6/2024

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