Add comprehensive dataset README

README.md

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+---
+license: mit
+task_categories:
+- image-classification
+tags:
+- satellite
+- remote-sensing
+- land-cover
+- eurosat
+size_categories:
+- 1K<n<10K
+---
+
+# EuroSAT Image Classification Dataset
+
+This dataset contains the EuroSAT satellite image classification data in parquet format for easy loading and processing.
+
+## Dataset Information
+
+- **Task**: Image Classification
+- **Source**: [EuroSAT Dataset](https://github.com/phelber/EuroSAT)
+- **Classes**: 10 land use/land cover classes
+- **Image Size**: 64x64 pixels (RGB)
+- **Format**: Parquet with embedded images
+- **Splits**: train, test
+
+## Classes
+
+The dataset contains 10 land use and land cover classes:
+
+| ID | Class Name | Description |
+|----|------------|-------------|
+| 0 | AnnualCrop | Annual crop fields |
+| 1 | Forest | Forest areas |
+| 2 | HerbaceousVegetation | Herbaceous vegetation |
+| 3 | Highway | Highway and roads |
+| 4 | Industrial | Industrial buildings |
+| 5 | Pasture | Pasture land |
+| 6 | PermanentCrop | Permanent crop fields |
+| 7 | Residential | Residential areas |
+| 8 | River | Rivers and water bodies |
+| 9 | SeaLake | Seas and lakes |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+ds = load_dataset("resaro/eurosat")
+
+# Access splits
+print(ds["train"][0])  # First training example
+print(ds["test"][0])   # First test example
+
+# Iterate over the dataset
+for example in ds["train"]:
+    image = example["image"]  # PIL Image
+    label = example["label"]  # Integer 0-9
+    # Your processing here
+```
+
+## Dataset Structure
+
+Each example contains:
+- `image`: PIL Image object (64x64 RGB)
+- `label`: Integer label (0-9) corresponding to the class
+
+### Data Splits
+
+| Split | Samples |
+|-------|---------|
+| train | 990 |
+| test | 1,000 |
+| **Total** | **1,990** |
+
+### Class Distribution (Training Set)
+
+All classes are balanced with approximately 99 samples per class in the training set.
+
+## Citation
+
+If you use this dataset, please cite the original EuroSAT paper:
+
+```bibtex
+@article{helber2019eurosat,
+  title={Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification},
+  author={Helber, Patrick and Bischke, Benjamin and Dengel, Andreas and Borth, Damian},
+  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
+  volume={12},
+  number={7},
+  pages={2217--2226},
+  year={2019},
+  publisher={IEEE}
+}
+```
+
+## License
+
+MIT License - Please refer to the original EuroSAT dataset for detailed license information.