Add HF metadata and clean links

README.MD

@@ -1,159 +0,0 @@
-# MethaneS2CM – Plume Masks Only (Derived Dataset)
-
-This dataset is a **plume-mask-only** derivative of  
-[H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW). :contentReference[oaicite:0]{index=0}  
-
-It contains the methane plume segmentation masks (`plume.tif`) without redistributing the Sentinel-2 imagery (`s2.tif`, `s2_pre.tif`, `s2_pre_pre.tif`).  
-The goal is to provide a compact (~2 GB) resource focused on plume labels for users who already have access to Sentinel-2 data or who want to combine these masks with their own imagery.
-
----
-
-## 1. Origin and Relationship to MethaneS2CM
-
-The original **MethaneS2CM** dataset is a large-scale benchmark for methane emission detection from Sentinel-2 multispectral imagery, built from real plume annotations from CarbonMapper and co-located Sentinel-2 observations. :contentReference[oaicite:1]{index=1}  
-
-Each sample in MethaneS2CM includes:
-- Sentinel-2 imagery at three time points: leak day (T), T-90, and T-365, and  
-- a corresponding plume mask and plume label.
-
-This derived dataset:
-
-- Keeps only the **plume masks** (`plume.tif`),  
-- Preserves the original indexing / IDs where applicable (so that users can cross-reference with the full MethaneS2CM dataset),  
-- Does **not** include any Sentinel-2 pixel data.
-
-For full details on the construction and intended use of the original dataset, please refer to:
-
-- Original dataset: [H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW) :contentReference[oaicite:2]{index=2}  
-- Paper: “MethaneS2CM: A Dataset for Multispectral Deep Methane Emission Detection” (KDD 2025). :contentReference[oaicite:3]{index=3}  
-
----
-
-## 2. Data Contents
-
-### 2.1 File structure
-
-The repository contains only plume masks, stored as GeoTIFFs (`plume.tif`).  
-A typical directory layout is:
-
-```text
-.
-├── README.md
-└── plumes/
-    ├── ang20160915t180022-B_0/plume.tif
-    ├── GAO20210731t175256p0000-B_1/plume.tif
-    ├── emi20220827t060753p04013-C_0/plume.tif
-    └── ...
-```
-
-Each `plume.tif` is a raster mask with:
-
-- Single channel (binary):  
-  - `1` (or 255) = plume pixels  
-  - `0` = non-plume pixels  
-- Spatial reference / georeferencing inherited from the original Sentinel-2 product used in MethaneS2CM (e.g. UTM/WGS84).
-
-> Note: The exact folder structure and naming convention may differ; check this README and the repository tree for the final, authoritative layout.
-
-### 2.2 Coordinate system and resolution
-
-Plume masks are aligned with the original MethaneS2CM Sentinel-2 patches:
-
-- Pixel size: 20 m (Sentinel-2 SWIR resolution),  
-- Projection: the same as in MethaneS2CM (UTM zone corresponding to the plume location, WGS84 ellipsoid).  
-
-This ensures that users can:
-
-- Directly overlay these plume masks on Sentinel-2 imagery downloaded from Copernicus / Google Earth Engine, or  
-- Combine them with the original MethaneS2CM dataset.
-
----
-
-## 3. Intended Use
-
-This plume-only dataset is suitable for:
-
-- Training and evaluating **segmentation** models for methane plume detection when you supply your own input imagery,  
-- Using the masks as labels while:
-  - Redownloading Sentinel-2 data from the official sources, or  
-  - Using Sentinel-2 data from the original MethaneS2CM dataset (if you also have a local copy),  
-- Performing analyses that focus on:
-  - Plume shape and morphology,  
-  - Spatial statistics,  
-  - Label quality and uncertainty, independently of a specific input feature set.
-
-If you require:
-
-- Full Sentinel-2 inputs (T, T-90, T-365) and  
-- The predefined dataset splits and Parquet metadata,  
-
-please use the original dataset: [H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW).  
-
----
-
-
-## 4. Citation
-
-If you use this dataset in your work, **please cite the original MethaneS2CM paper**, as this dataset is entirely derived from it:
-
-```bibtex
-@inproceedings{liu2025methanes2cm,
-  title        = {MethaneS2CM: A Dataset for Multispectral Deep Methane Emission Detection},
-  author       = {Liu, Hongxuan and Leung, Juliana Y and Niu, Di},
-  booktitle    = {Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 2},
-  pages        = {5640--5651},
-  year         = {2025}
-}
-```
-
-Additionally, you may optionally reference this derived dataset as:
-
-```bibtex
-@misc{methanes2cm_plume_only,
-  title        = {MethaneS2CM – Plume Masks Only (Derived Dataset)},
-  author       = {<Your Name>},
-  howpublished = {\url{https://huggingface.co/datasets/Lucab95/MethaneS2CM_plume_only}},
-  year         = {2025},
-  note         = {Derived from H1deaki/S2CM_RAW under CC-BY-NC 4.0}
-}
-```
-
-Please replace `<Your Name>` and `<yourname>` with your actual information.
-
----
-
-## 5. License
-
-The original **MethaneS2CM** dataset is released under the **CC-BY-NC 4.0** license.
-
-This derived plume-only dataset is therefore also distributed under:
-
-> **License:** CC-BY-NC 4.0 (Attribution–NonCommercial)
-
-Key points (informal, not legal advice):
-
-- **Attribution (BY):**  
-  You must credit:
-  - the MethaneS2CM authors (Liu, Leung, Niu) and  
-  - this derived dataset (if used explicitly),
-  and retain references to the original dataset and this repository where appropriate.
-
-- **NonCommercial (NC):**  
-  You may not use this dataset or derivatives of it for **commercial purposes** without obtaining separate permission from the rights holders.
-
-For the full legal text, see the [CC-BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/).
-
----
-
-## 6. Acknowledgments
-
-This dataset is a derivative work of:
-
-- MethaneS2CM: [H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW).  
-
-We acknowledge:
-
-- The **European Space Agency (ESA)** for providing Sentinel-2 data, and  
-- The **CarbonMapper** initiative for plume annotations and their open data efforts,  
-
-following the acknowledgments of the original MethaneS2CM dataset.

README.md

@@ -1,7 +1,15 @@
+---
+tags:
+  - methane
+  - sentinel-2
+  - image-segmentation
+license: cc-by-nc-4.0
+---
+
 # MethaneS2CM – Plume Masks Only (Derived Dataset)
 
 This dataset is a **plume-mask-only** derivative of  
-[H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW). :contentReference[oaicite:0]{index=0}  
+[H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW).  
 
 It contains the methane plume segmentation masks (`plume.tif`) without redistributing the Sentinel-2 imagery (`s2.tif`, `s2_pre.tif`, `s2_pre_pre.tif`).  
 The goal is to provide a compact (~2 GB) resource focused on plume labels for users who already have access to Sentinel-2 data or who want to combine these masks with their own imagery.
@@ -10,7 +18,7 @@ The goal is to provide a compact (~2 GB) resource focused on plume labels for us
 
 ## 1. Origin and Relationship to MethaneS2CM
 
-The original **MethaneS2CM** dataset is a large-scale benchmark for methane emission detection from Sentinel-2 multispectral imagery, built from real plume annotations from CarbonMapper and co-located Sentinel-2 observations. :contentReference[oaicite:1]{index=1}  
+The original **MethaneS2CM** dataset is a large-scale benchmark for methane emission detection from Sentinel-2 multispectral imagery, built from real plume annotations from CarbonMapper and co-located Sentinel-2 observations.  
 
 Each sample in MethaneS2CM includes:
 - Sentinel-2 imagery at three time points: leak day (T), T-90, and T-365, and  
@@ -24,8 +32,8 @@ This derived dataset:
 
 For full details on the construction and intended use of the original dataset, please refer to:
 
-- Original dataset: [H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW) :contentReference[oaicite:2]{index=2}  
-- Paper: “MethaneS2CM: A Dataset for Multispectral Deep Methane Emission Detection” (KDD 2025). :contentReference[oaicite:3]{index=3}  
+- Original dataset: [H1deaki/S2CM_RAW](https://huggingface.co/datasets/H1deaki/S2CM_RAW)  
+- Paper: “MethaneS2CM: A Dataset for Multispectral Deep Methane Emission Detection” (KDD 2025).  
 
 ---