---
datasets:
  - nesteo-prototype
language: 
  - en
size_categories:
  - 10M<n<100M
multilinguality: monolingual
tags:
  - ai4eo
  - earth-observation
  - remote-sensing
  - multimodal
  - grids
license: cc-by-4.0
task_categories:
  - image-segmentation
  - image-classification
pretty_name: NestEO Prototype

# dataset_info:
#   - config_name: default
#     features:
#     - name: view:sun_elevation
#       dtype: float64
#     - name: json_path
#       dtype: object
#     - name: satl:altitude
#       dtype: float64
#     - name: datetime
#       dtype: object
#     - name: satl:product_name
#       dtype: object
#     - name: platform
#       dtype: object
#     - name: proj:epsg
#       dtype: object
#     - name: view:azimuth
#       dtype: float64
#     - name: grid:code
#       dtype: object
#     - name: providers
#       dtype: object
#     - name: proj:shape
#       dtype: object
#     - name: license
#       dtype: object
#     - name: scene_id
#       dtype: object
#     - name: proj:transform
#       dtype: object
#     - name: view:sun_azimuth
#       dtype: float64
#     - name: satl:altitude_units
#       dtype: object
#     - name: view:off_nadir
#       dtype: float64
#     - name: gsd
#       dtype: float64
      
# configs:
#   - config_name: default
#     data_files: metadata_current/scene_parameters/newsat*.parquet



configs:
  - config_name: grids_selected_1200m          # appears in the drop-down
    default: true                              # <- this is what the viewer shows first
    data_files:
      - split: train
        path: "grids/grids_selected/selected_1200m_grid.parquet"
  # <!-- - config_name: legacy_full_grid              # keep the old file available
  #   data_files:
  #     - split: train
  #       path: "old_folder/old_grid.parquet"    # adjust to real path -->

---


# NestEO: Modular and Hierarchical EO Dataset Framework

NestEO is a hierarchical, resolution-aligned, UTM-based nested grid dataset framework supporting general-purpose, multi-scale multimodal Earth Observation workflows. Built from diverse EO sources and enriched with metadata for landcover, climate zones, and population, it enables scalable, representative and progressive sampling for AI4EO.

**Grid Levels**: 120000m, 12000m, 2400m, 1200m, 600m, 300m, 150m  
**Grid Metadata**: ESA WorldCover proportions, GHSL, Köppen Climate  
**Current Sample Datasets**: Wyvren Hyperspectral, Satellogic Newsat, Sentinel-2, Sentinel-1, Sentinel-3
**Zones**: UTM 1N–60N, 1S–60S and Polar North/South
**Formats**: Parquet, GeoParquet, Zarr (planned)
**License**: CC-BY-4.0  
**More Info**: See [paper](link), [GitHub](https://github.com/mbzuai-oryx/NestEO).  


## Directory Structure Scaffold

```text
NestEO/
├── grids/                  # UTM-aligned hierarchical grid Parquet files
├── metadata_current/       # Precomputed proportions: landcover, planned (climate, region, biomes, ghsl)
├── datasets_EO/            # Clipped EO imagery tiles (Newsat, Sentinels, planned(Landsat, HLS, MODIS, etc.))
├── datasets_AUX/           # Auxiliary datasets planned(DEM, landcover, OSM)
├── embeddings/             # Precomputed model embeddings planned (e.g., DINOv2, SigLIP, SAM, SAM2)
├── index_structure/        # tile-to-super-tile, Source-to-tile and tile-ID index maps
└── versions/               # Information about snapshots for version control
```

## Dataset Structure
- Each tile includes a unique `tile_id`, and spatial geometry.
- Grouped by zone directories: `grid_2400m/grid_37N_2400.parquet`

## Code
Github code provides the grid creation logic, ESA Worldcover proportion calculations, notebooks for processing sample datasets, and fetching/merging grids with datasets


**How to Use**  

* Install from Github and create your own Nested grid structure 
* Load a grid from grids/ (e.g., grid_1200m.parquet).  
* Join with metadata (e.g., metadata_lc.parquet) on tile_id.  
* Apply spatial or semantic filtering (e.g., only urban, with specific dates).  
* Select and load paired EO imagery and sources from folders.  


**Current Status**  

This is a prototype release of the NestEO dataset framework, showcasing the core design principles, including hierarchical UTM-aligned grids, modular directory layout, structured GeoParquet-based metadata, and compatibility with scalable Earth Observation (EO) data ingestion. This release includes a limited set of EO source tiles and metadata layers meant to demonstrate framework usability, alignment strategies, and pipeline extensibility. Metadata-driven filtering, source-pairing, and tile-to-super-tile indexing are fully implemented.

**Limitations**
- This version provides a demonstration of the framework vision. Only few selected EO modalities (e.g., Sentinel-2, Sentinel-3, Satellogic, Wyvren) are currently included at sample scale.
- Further EO content layers (imagery, land cover, auxillary layers etc.) to be added in later updates for NestEOv1.
- Cross-modal pairings, auxiliary layers (e.g., DEM, OSM), and full-resolution coverage across grid levels are under active development.
- Not all grid levels are currently populated with imagery; some grid layers are provided primarily to support alignment, pairing and demonstration purposes. 

### Roadmap and Ongoing Work

A comprehensive **v1 release** is under development. This upcoming version will include:

- **12+ EO modalities** (optical, SAR, hyperspectral, atmospheric, thermal)  
- **Over 250,000 geospatially distributed tiles** across multiple grid levels  
- **Paired imagery samples** at selected locations, across grid levels, supporting multimodal learning  
- **Expanded metadata layers** including ESA WorldCover, Copernicus DEM, Köppen-Geiger zones, and GHSL-derived population classes  
- **Precomputed model embeddings** (e.g., DINOv2, SigLIP, SAM2) at tile-level granularity  
- **Full compatibility** with cloud-based filtering, lazy loading, and Hugging Face Datasets  

All v1 expansions will preserve the **NestEO prototype structure** and align with **FAIR dataset development practices**. The prototype release remains stable as a referential snapshot of the NestEO design framework, while v1 will extend data completeness, modeling readiness and potential foundation model development.



**Contributing**  

We welcome contributions on:

* Region-specific or resolution-specific imagery  
* Auxiliary or annotation layers  
* Grid-level metadata enrichment  
* Benchmarks and model evaluations


## Citation
TBD – upon official release.