Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
|
| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.17366635 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- <p>This dataset provides the georeferenced delineation of sandy beach extents along the Indian coastline, derived from IRS ResourceSat-2/2A LISS-IV multispectral imagery using a U-Net deep learning model. The dataset captures fine-scale sandy shoreline features and serves as a foundational resource for coastal geomorphology, shoreline monitoring, and sustainable coastal zone management.</p> <p>The sandy beach polygons were extracted through a deep learning workflow implemented in PyTorch, employing a U-Net segmentation model trained on manually annotated coastal sites representing diverse geomorphic and sedimentary settings. The input imagery comprises 5.8 m spatial resolution LISS-IV data with green, red, and near-infrared bands, supplemented by derived indices such as NDVI, Green–NIR ratio, and composite intensity to improve feature separability.</p> <p>The shapefile provides polygon representations of mapped sandy beaches across the Indian coastline and is projected in WGS 84 geographic coordinates (EPSG:4326). Users can integrate this dataset within GIS environments for visualization, spatial analysis, and model validation.</p> <p>Temporal coverage of the imagery used for mapping spans 2021–2024. Users should note that very small or seasonally transient sandy patches may not be captured due to the 5.8 m spatial resolution of the source data. </p> <p>This dataset supports applications in coastal mapping, blue economy planning, sediment dynamics research, and shoreline change assessment.</p>