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Dam Segmentation Dataset
Multispectral UAV Remote Sensing Data for Embankment Dam Segmentation
Dataset Summary
This dataset contains a series of multispectral image slices captured at the embankment dams and dikes of the Belo Monte Hydroelectric Complex, located in the state of Pará, northern Brazil. Each image is paired with its respective NDRE vegetation index values, binary segmentation mask and multiclass segmentation mask.
The multispectral images were captured by the Micasense RedEdge-P multispectral sensor embedded in a DJI M210 V2 UAV. Radiometric calibration was performed for all images based on the known reflectance values of a calibration panel. All images were used to process a Digital Ortophoto Map, which was then sliced into the 256x256x6 image patches that are contained in this dataset.
Each image file is composed of six channels:
- Red band reflectance
- Green band reflectance
- Blue band reflectance
- Red Edge band reflectance
- Near-infrared band reflectance
- Binary cutline
The vegetation index (NDRE) values were calculated based on the spectral bands and the segmentation masks were manually annotated using the CVAT software.
Dataset Structure
The dataset files are organized as following:
📁 dam-segmentation
├── 📁 images # Multispectral images
├── 📁 index_ndre # NDRE index values
├── 📁 labels_binary # Binary Segmentation Masks
├── 📁 labels_multiclass # Multiclass Segmentation Masks
└── 📝 README.md
Segmentation Classes
The image annotations are formatted for both binary and multi-class segmentation.
Binary Segmentation Classes:
- Slope
- Not-Slope
Multi-class Segmentation Classes:
- Slope
- Drainage Channels
- Stairways
- Background
License Information
This dataset is licensed under the Creative Commons Attribution Non Commercial Share Alike 4.0 International license terms.
Citation Information
If you use this dataset in your work, please cite:
@misc{teixeira2024damseg,
author = {Carlos André de Mattos Teixeira},
title = {Multispectral UAV Remote Sensing Data for Embankment Dam Segmentation},
year = {2024},
publisher = {Hugging Face},
journal = {Dataset Repository},
url = {https://huggingface.co/datasets/andrematte/dam-segmentation}
doi = { 10.57967/hf/3089 },
}
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