cuibinge/Multimodal-Sea-Land

Mulitmodal Sea-Land Segmentation Dataset

Dataset Overview

This dataset contains optical and SAR images from Sentinel-2 and Sentinel-1.

Optical image

The Optical images were acquired from the Sentinel-2 satellite.

SAR image

The SAR images were acquired from the Sentinel-1 satellite. Specifically, the Interferometric Wide Swath (IW) mode was used, incorporating both Vertical-Vertical (VV) and Vertical-Horizontal (VH) polarizations.The Sentinel-1 data underwent preprocessing in SNAP software, including orbit correction, thermal noise removal, radiometric calibration, and terrain correction. Finally, the data were resampled to a resolution of 10 m × 10 m to align with the selected Sentinel-2 spectral bands.

Dataset Specifications

<table> <tr> <th>Property</th> <th>Optical image</th> <th>SAR image</th> </tr> <tr> <th>Source</th> <td >Sentinel-2 satellite</td> <td>Sentinel-1 Satellite</td> </tr> <tr> <th>Spectral Bands</th> <td >Red, Green, Blue, and Near-Infrared</td> <td>VV, VH</td> </tr> <tr> <td>Spatial Resolution</td> <td colspan=2>10 meters</td> </tr> <tr> <td>Image Patch Size</td> <td colspan=2>224 × 224 pixels</td> </tr> <tr> <td>Total Image Pairs</td> <td colspan=2>1286</td> </table>

Dataset Structure and File Organization

The dataset is organized into paired folders for image patches and corresponding labels:

-LandSea/
├── opts/ (optical image)
│ ├── 1_1.tif
│ ├── 1_2.tif
│ └── ...
├── sars/ (SAR image)
│ ├── 1_1_0.tif
│ ├── 1_1_1.tif
│ ├── 1_2_0.tif
│ ├── 1_2_1.tif
│ └── ...
├── labels/
│ ├── 1_1.tif
│ ├── 1_2.tif
│ └── ...
└── README.md

• —Each sample consists of three images: one optical image and two SAR images. For example, the optical image is stored as ‘opts/11.tif’, and the corresponding SAR images are ‘sars/110.tif’ and ‘sars/11_1.tif’, representing the VV and VH polarization channels, respectively.
• —The corresponding sea-land segmentation map is stored in the lbls directory.

Labels

The label files are binary masks:

• —Pixel value 0: land
• —Pixel value 1: sea

<!-- ## Potential Applications

• —Glacier dynamics monitoring
• —Polar environmental change detection
• —Multispectral image analysis
• —Time-series remote sensing research
• —Climate-related environmental studies

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<!-- ## Dataset Access

The complete dataset is publicly available on GitHub: 👉 https://github.com/cuibinge/Glacier-Dataset

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<!-- ## Citation

If you use this dataset in your research, please cite:

VPGCD-Net: A Visual Prompt Driven Network for Glacier Change Detection in Remote Sensing Imagery. Zhishen Shi, Bing'e Cui, et al. IEEE Geoscience and Remote Sensing Letters, 2025.

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Contact

For dataset-related inquiries, please contact: 📧 cuibinge@sdust.edu.cn