Update README.md

README.md

@@ -2,21 +2,61 @@
 task_categories:
 - image-segmentation
 ---
+# NLCD-L 
+This dataset incorporates both SSL4EO-L Benchmark dataset and the NLCD-L dataset which is derived from the original SSL4EO-L Benchmark dataset by combining optical data from Landsat-7 and Landsat 8-9 with NLCD ground-truth labels, originally proposed in SSL4EO-L. The dataset contains 20 MSI bands, deliberately exceeding Sentinel-2’s channel count. It comprises 17,500 training samples, 3,750 validation samples, and 3,750 test samples.
 
-# SSL4EO-L Benchmark Dataset
+Please refer to the original SSL4EO-L paper for more detailed information about the original SSL4EO-L Benchmark dataset:
+- Paper: https://arxiv.org/abs/2306.09424
 
-The **SSL4EO-L Benchmark**, a benchmark dataset for image segmentation, consisting data from [Landsat](https://landsat.gsfc.nasa.gov/) program.
+## How to Use This Dataset
+```python
+from datasets import load_dataset
 
-Please see our [GFM-Bench](https://github.com/uiuctml/GFM-Bench) for more information about how to use the dataset! 🙂
+# To access NLCD-L, set name to etm_oli_toa_nlcd in load_dataset function
+dataset = load_dataset("GFM-Bench/SSL4EO-L-Benchmark", name="etm_oli_toa_nlcd")
+```
+
+Also, please see our [GFM-Bench](https://github.com/uiuctml/GFM-Bench) repository for more information about how to use the dataset! 🤗
+
+## Dataset Metadata
+
+The following metadata provides details about the Landsat imagery used in the dataset:
+| Configuration Name       | Number of Bands | Number of Label Classes | Spatial Resolution |
+|:---------------:|:------------:|:------------:|:------------:|
+| etm_sr_cdl | 6 | 134 | 30 |
+| etm_sr_nlcd | 6 | 21 | 30 |
+| etm_toa_cdl | 9 | 134 | 30 |
+| etm_toa_nlcd | 9 | 21 | 30 |
+| oli_sr_nlcd | 7 | 134 | 30 |
+| oli_sr_nlcd | 7 | 21 | 30 |
+| oli_tirs_toa_cdl | 11 | 134 | 30 |
+| oli_tirs_toa_nlcd | 11 | 21 | 30 |
+| **etm_oli_toa_cdl** | 20 | 134 | 30 |
+| **etm_oli_toa_nlcd** | 20 | 21 | 30 |
+
+## Dataset Splits
+The **NLCD-L** and SSL4EO-L Benchmark dataset consist following splits:
+- **train**: 17,500 samples
+- **val**: 3,750 samples
+- **test**: 3,750 samples
 
+## Dataset Features:
+The **NLCD-L** and SSL4EO-L dataset consist of following features:
+<!--- **radar**: the Sentinel-1 image.-->
+- **optical**: the Landsat image.
+- **label**: the segmentation labels.
+<!--- **radar_channel_wv**: the central wavelength of each Sentinel-1 bands.-->
+- **optical_channel_wv**: the central wavelength of each Landsat bands.
+- **spatial_resolution**: the spatial resolution of images.
 ## Citation
-If you use the SSL4EO-L Benchmark dataset in your work, please cite the original paper:
+If you use either the NLCD-L dataset or the original SSL4EO-L Benchmark dataset in your work, please cite the original paper:
 ```
-@article{stewart2024ssl4eo,
+@article{stewart2023ssl4eo,
   title={Ssl4eo-l: Datasets and foundation models for landsat imagery},
   author={Stewart, Adam and Lehmann, Nils and Corley, Isaac and Wang, Yi and Chang, Yi-Chia and Ait Ali Braham, Nassim Ait and Sehgal, Shradha and Robinson, Caleb and Banerjee, Arindam},
   journal={Advances in Neural Information Processing Systems},
   volume={36},
-  year={2024}
+  pages={59787--59807},
+  year={2023}
 }
 ```