# MethaneSET-S2 Finetune: Verified Methane Plume Events from Sentinel-2 for Supervised Learning

methaneset-s2-finetune is the verified plume subset of MethaneSET-S2, designed for supervised fine-tuning of methane detection and segmentation models. This subset contains Sentinel-2 imagery with manually verified methane plumes, binary segmentation masks, and methane enhancement maps (ΔXCH₄ in ppb). Unlike MARS-S2L which provides only six common bands, MethaneSET retrieves all 13 Sentinel-2 L1C bands at 10m GSD (200x200 pixel chips), enabling research with coastal aerosol, water vapour, cirrus, and red edge channels. Each sample includes target and reference image pairs, plume segmentation masks, CH4 enhancement images, Cloud Score+ masks, wind vectors (ERA5-Land onshore, GEOS-FP offshore), solar/viewing geometry, emission rates with uncertainties, elevation (Copernicus DEM GLO-30), and 64-dim AlphaEarth Foundation embeddings.
## Dataset Information

**Version**: 1.0.0

**License**: CC-BY-4.0

**Keywords**: methane, finetune, supervised, segmentation, plume-detection, remote-sensing, Sentinel-2, MSI, earth-observation, deep-learning

**Tasks**: segmentation, classification, detection

## Dataset Overview

**Partitions**: 21 files
**Spatial coverage**: [-103.98, -36.37, 116.52, 49.97] (WGS84)
**Temporal coverage**: 2018-01-05 to 2024-12-30

## Dataset Structure (Root-Sibling Uniform Tree)

**Root**: FOLDER (3,612 samples)

**Hierarchy**:

- Level 1: FILE → FILE → FILE → FILE → FILE (18,060 samples)

## Metadata Fields

### LEVEL0

| Field | Type | Description |
|-------|------|-------------|
| `id` | `string` | Unique sample identifier within parent scope. Must be unique among siblings. |
| `type` | `string` | Sample type discriminator (FILE or FOLDER). |
| `stac:crs` | `string` | Coordinate reference system (WKT2, EPSG, or PROJ) |
| `stac:tensor_shape` | `list<item: int64>` | Raster dimensions [bands, height, width] |
| `stac:geotransform` | `list<item: double>` | GDAL affine transform |
| `stac:time_start` | `timestamp[us]` | Start timestamp (μs since Unix epoch, UTC) |
| `stac:centroid` | `binary` | Center point in EPSG:4326 (WKB) |
| `stac:time_end` | `timestamp[us]` | End timestamp (μs since Unix epoch, UTC) |
| `stac:time_middle` | `timestamp[us]` | Middle timestamp (μs since Unix epoch, UTC) |
| `detection:isplume` | `bool` | Whether a methane plume is present |
| `detection:ch4_fluxrate` | `float` | Methane flux rate (kg/h) |
| `detection:ch4_fluxrate_std` | `float` | Standard deviation of flux rate |
| `detection:sector` | `string` | Emission sector (Oil and Gas, Coal, Waste, etc.) |
| `detection:offshore` | `bool` | Whether location is offshore |
| `detection:wind_source` | `string` | Wind data source (e.g. ERA5-Land, GEOS-FP) |
| `detection:case_study` | `string` | Case study area name (e.g. Permian Basin) |
| `satellite:platform` | `string` | Satellite platform (S2A, S2B, LC08, LC09) |
| `satellite:tile` | `string` | Product identifier |
| `satellite:vza` | `float` | Viewing zenith angle (degrees) |
| `satellite:sza` | `float` | Solar zenith angle (degrees) |
| `satellite:background_tile` | `string` | Reference image product identifier |
| `quality:percentage_clear` | `float` | Percentage of clear pixels (0-100) |
| `quality:observability` | `string` | Image quality classification |
| `quality:notified` | `bool` | Whether observation has been notified |
| `quality:last_update` | `string` | Last registry modification timestamp (ISO format) |
| `plume:geometry` | `binary` | Plume extent as WKB geometry |
| `site:country` | `string` | Country of the emission source |
| `site:location_name` | `string` | Site location identifier |
| `meteo:wind_u` | `float` | U-component of wind at 10m (m/s) |
| `meteo:wind_v` | `float` | V-component of wind at 10m (m/s) |
| `split` | `string` | Dataset partition identifier (train, test, or validation) |
| `majortom:code` | `string` | MajorTOM spherical grid cell identifier (e.g., 0100km_0003U_0005R) with ~dist_km spacing |
| `geoenrich:elevation` | `float` | Mean elevation in meters (GLO-30 DEM) |
| `geoenrich:temperature` | `float` | Mean annual temperature in °C estimated from MODIS LST data |
| `geoenrich:population` | `float` | Population density from HRSL. Facebook High Resolution Settlement Layer |
| `geoenrich:admin_countries` | `string` | Country name at centroid location |
| `geoenrich:admin_states` | `string` | State/province name at centroid location |
| `geoenrich:admin_districts` | `string` | District/county name at centroid location |
| `internal:current_id` | `int64` | Current sample position at this level (0-indexed). Enables O(1) random access and relational JOINs (ZIP, FOLDER, TACOCAT). |
| `internal:parent_id` | `int64` | Foreign key referencing parent sample position in previous level (ZIP, FOLDER, TACOCAT). |

### LEVEL1

| Field | Type | Description |
|-------|------|-------------|
| `id` | `string` | Unique sample identifier within parent scope. Must be unique among siblings. |
| `type` | `string` | Sample type discriminator (FILE or FOLDER). |
| `geotiff:stats` | `list<item: list<item: float>>` | Per-band statistics (List[List[Float32]]): categorical mode returns class probabilities, continuous mode returns [min, max, mean, std, valid%, p25, p50, p75, p95] |
| `taco:header` | `binary` | Binary TACOTIFF header (35 bytes + tile counts) for fast reading without IFD parsing |
| `internal:current_id` | `int64` | Current sample position at this level (0-indexed). Enables O(1) random access and relational JOINs (ZIP, FOLDER, TACOCAT). |
| `internal:parent_id` | `int64` | Foreign key referencing parent sample position in previous level (ZIP, FOLDER, TACOCAT). |
| `internal:relative_path` | `string` | Relative path from DATA/ directory. Format: {parent_path}/{id} or {id} for level0 (ZIP, FOLDER, TACOCAT). |


## Usage

### Python

```python
# pip install tacoreader
import tacoreader

ds = tacoreader.load("methaneset-s2-finetune.tacozip")
print(f"ID: {ds.id}")
print(f"Version: {ds.version}")
print(f"Samples: {len(ds.data)}")
```

### R

```r
# Coming soon: R support is planned but not yet available
# install.packages("tacoreader")
library(tacoreader)

ds <- load_taco("methaneset-s2-finetune.tacozip")
cat(sprintf("ID: %s\n", ds$id))
cat(sprintf("Version: %s\n", ds$version))
cat(sprintf("Samples: %d\n", nrow(ds$data)))
```

### Julia

```julia
# Coming soon: Julia support is planned but not yet available
# using Pkg; Pkg.add("TacoReader")
using TacoReader

ds = load_taco("methaneset-s2-finetune.tacozip")
println("ID: ", ds.id)
println("Version: ", ds.version)
println("Samples: ", size(ds.data, 1))
```

## Data Providers

**UNEP IMEO** — *producer*

**Source Cooperative** — *host*


## Dataset Curators

| Name | Organization | Email |
|------|--------------|-------|
| Cesar Aybar | Universitat de València, Image and Signal Processing (ISP) Group | cesar.aybar@uv.es |

## Publications & Citations

If you use this dataset in your research, please cite:


**DOI**: 10.48550/arXiv.2411.15452

Vaughan, A.*, Mateo-Garcia, G.*, Irakulis-Loitxate, I., Watine, M., Fernandez-Poblaciones, P., Turner, R. E., Requeima, J., Gorroño, J., Randles, C., Caltagirone, M., &amp; Cifarelli, C.* (2024). AI for operational methane emitter monitoring from space. arXiv preprint arXiv:2411.15452.

*Operational MARS-S2L system for global methane monitoring from Sentinel-2 and Landsat 8/9.*

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**DOI**: 10.48550/arXiv.2511.21777

Vaughan, A.*, Mateo-Garcia, G.*, Irakulis-Loitxate, I., Watine, M., Fernandez-Poblaciones, P., Turner, R. E., Requeima, J., Gorroño, J., Randles, C., Caltagirone, M., &amp; Cifarelli, C.* (2024). Artificial intelligence for methane detection: from continuous monitoring to verified mitigation. arXiv preprint arXiv:2511.21777.

*Extended operational deployment demonstrating 1,015 stakeholder notifications across 20 countries and verified permanent mitigation of six persistent emitters.*

---

**DOI**: 10.5194/essd-13-4349-2021

Muñoz-Sabater, J., et al. (2021). ERA5-Land: a state-of-the-art global reanalysis. Earth System Science Data, 13, 4349-4383.

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**DOI**: 10.1029/2014JD022685

Lucchesi, R. (2013). GEOS-5 FP (Forward Processing) File Specification. NASA GMAO Technical Report.

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### BibTeX

```bibtex
@dataset{methaneset-s2-finetune1,
  title = {MethaneSET-S2 Finetune: Verified Methane Plume Events from Sentinel-2 for Supervised Learning},
  author = {Cesar Aybar},
  year = {2018},
  version = {1.0.0},
  publisher = {Universitat de València, Image and Signal Processing (ISP) Group}
}
```

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