Datasets:
File size: 1,627 Bytes
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dataset_info:
features:
- name: rgb
dtype: image
- name: mask
dtype: image
- name: split
dtype: string
splits:
- name: train
num_bytes: 3092369713
num_examples: 213758
download_size: 3096602246
dataset_size: 3092369713
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-segmentation
size_categories:
- 100K<n<1M
---
# Sen2 Lulc
The Sen2_LULC dataset provides real multispectral satellite imagery for semantic segmentation of land use and land cover in the central Indian region. Captured by Sentinel-2 at 10-meter resolution during February-March 2021, the data was collected from a satellite platform over field environments, offering high-quality inputs for agricultural and environmental monitoring applications. The dataset contains 213,758 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original train/test/val split has been preserved in the `split` column.
## Citation
```bibtex
@article{sawant2023sen,
title={Sen-2 LULC: Land use land cover dataset for deep learning approaches},
author={Sawant, Suraj and Garg, Rahul Dev and Meshram, Vishal and Mistry, Shrayank},
journal={Data in Brief},
volume={51},
pages={109724},
year={2023},
publisher={Elsevier}
}
```
Sawant, Suraj; Garg, Rahul Dev; Meshram, Vishal; Mistry, Shrayank (2023), “Sen-2 LULC ”, Mendeley Data, V3, doi: 10.17632/f4ky6ks248.3
*This dataset was reformatted from its original format to match HuggingFace standards.* |