Mathematical and computer sciences (general)
### FAIRification - Satellite imagery converted to DGGS using [xhealpixify](https://github.com/IAOCEA/xhealpixify) - Machine-actionable: `schema:ViewAction` links the dataset to the [FAIR2Adapt dashboard](https://fair2adapt.github.io/riomar-dashboard/) for interactive visualization at any zoom level - Metadata enriched with [I-ADOPT](https://i-adopt.github.io/) variable decomposition
### Dataset - **Variable**: Band 02 (Blue, 490nm) top-of-atmosphere reflectance - **Spatial coverage**: Normandy, France (~48.5°N–49.5°N, 0.5°E–1.5°E) - **Grid**: HEALPix multiscale pyramid (11 levels) - Finest: level 20 (nside=1,048,576, ~10m resolution, 208M cells) - Coarsest: level 10 (nside=1,024, ~10km resolution) - Resampling: mean aggregation between levels - **Format**: Cloud-optimized Zarr with nested HEALPix indexing on WGS84 ellipsoid
Science and technology/Technology and engineering/Micro science/Nanotechnology
FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid) Sentinel-2 Level-1C satellite observation converted to a HEALPix Discrete Global Grid System (DGGS) multiscale pyramid, covering a region in **Normandy, France** (Seine Valley, between Rouen and Paris)
Climate change impacts, risks and adaptation
Science and technology/Technology and engineering/IT-computer sciences
Sentinel-2 Level-1C satellite observation converted to a HEALPix Discrete Global Grid System (DGGS) multiscale pyramid, covering a region in **Normandy, France** (Seine Valley, between Rouen and Paris). ### Dataset - **Variable**: Band 02 (Blue, 490nm) top-of-atmosphere reflectance - **Spatial coverage**: Normandy, France (~48.5°N–49.5°N, 0.5°E–1.5°E) - **Grid**: HEALPix multiscale pyramid (11 levels) - Finest: level 20 (nside=1,048,576, ~10m resolution, 208M cells) - Coarsest: level 10 (nside=1,024, ~10km resolution) - Resampling: mean aggregation between levels - **Format**: Cloud-optimized Zarr with nested HEALPix indexing on WGS84 ellipsoid ### FAIRification - Satellite imagery converted to DGGS using [xhealpixify](https://github.com/IAOCEA/xhealpixify) - Machine-actionable: `schema:ViewAction` links the dataset to the [FAIR2Adapt dashboard](https://fair2adapt.github.io/riomar-dashboard/) for interactive visualization at any zoom level - Metadata enriched with [I-ADOPT](https://i-adopt.github.io/) variable decomposition ### Context Part of the [FAIR2Adapt](https://fair2adapt.eu) project, demonstrating that the HEALPix DGGS approach works for both ocean model outputs and Earth observation data. The multiscale pyramid enables efficient visualization from global overview to full 10m resolution.
FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid)
Fouilloux, Anne. "FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid)." ROHub. Feb 20 ,2026. https://w3id.org/ro-id/fdc1c071-76d7-44df-a565-8217ebcc59fe.
View Sentinel-2 data in FAIR2Adapt Dashboard
The Sentinel-2 Level-1C satellite observation can be converted to a HEALPix DGGS multiscale pyramid, enabling efficient visualization from global overview to 10m resolution.
The HEALPix DGGS multiscale pyramid allows for efficient visualization of Sentinel-2 Level-1C satellite data from global overview to 10m resolution.
The Sentinel-2 Level-1C satellite observation is converted to a HEALPix DGGS multiscale pyramid, covering a region in Normandy, France, with a spatial coverage of ~48.5°N–49.5°N, 0.5°E–1.5°E.
The HEALPix multiscale pyramid has 11 levels, with the finest level having a resolution of approximately 10 meters and the coarsest level having a resolution of approximately 10 kilometers.
Mean aggregation between levels is used for resampling in the HEALPix multiscale pyramid.
The dataset is stored in a Cloud-optimized Zarr format with nested HEALPix indexing on the WGS84 ellipsoid, enabling efficient data retrieval and visualization.
The Sentinel-2 Level-1C satellite observation was successfully converted to a HEALPix Discrete Global Grid System (DGGS) multiscale pyramid using the xhealpixify tool.
The dataset is machine-actionable, allowing for interactive visualization at any zoom level through the FAIR2Adapt dashboard.
I-ADOPT variable decomposition is applied to the metadata of the Sentinel-2 Level-1C satellite observation dataset.
The HEALPix Discrete Global Grid System (DGGS) can be applied to both ocean model outputs and Earth observation data, such as Sentinel-2 Level-1C satellite observations, for efficient visualization and analysis.
AIDA Claim 4: The dataset is machine-actionable, allowing for interactive visualization at any...
AIDA Claim 3: The dataset is stored in a Cloud-optimized Zarr format with nested HEALPix index...
AIDA Claim 8: The Sentinel-2 Level-1C satellite observation was successfully converted to a HE...
AIDA Claim 5: The HEALPix Discrete Global Grid System (DGGS) can be applied to both ocean mode...
AIDA Claim 7: Mean aggregation between levels is used for resampling in the HEALPix multiscale...
AIDA Claim 10: The Sentinel-2 Level-1C satellite observation can be converted to a HEALPix DGGS...
AIDA Claim 2: The HEALPix multiscale pyramid has 11 levels, with the finest level having a res...
AIDA Claim 9: I-ADOPT variable decomposition is applied to the metadata of the Sentinel-2 Leve...
AIDA Claim 1: The HEALPix DGGS multiscale pyramid allows for efficient visualization of Sentin...
AIDA Claim 6: The Sentinel-2 Level-1C satellite observation is converted to a HEALPix DGGS mul...