Datasets:
Modalities:
Geospatial
Size:
1B<n<10B
Tags:
remote-sensing
water-quality
chlorophyll-a
harmful-algal-blooms
spatial-reconstruction
benchmark
License:
File size: 2,794 Bytes
88c61ef 341902f 88c61ef 341902f 88c61ef fbd46e6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | ---
license: cc-by-4.0
pretty_name: BloomField
tags:
- remote-sensing
- water-quality
- chlorophyll-a
- harmful-algal-blooms
- spatial-reconstruction
- benchmark
size_categories:
- 1B<n<10B
---
# BloomField
Whole-lake chlorophyll-*a* (Chl-*a*) **field-reconstruction** benchmark for the
**trusted-sparse × biased-dense** regime: a handful of accurate in-situ stations paired with two
independent, value-biased ocean-colour satellites (GOCI-II geostationary + Sentinel-3 OLCI), over
three eutrophic lakes in eastern China (Tai, Chao, Hongze), 2021–2024.
## Structure
Per-lake folder (`tai/`, `chao/`, `hongze/`):
- `goci_cache.npy`, `olci_cache.npy` — gridded per-scene Chl-*a* rasters on a common ~300 m lake grid.
- `goci_scenes.json`, `olci_dates.json` — scene → cache-row indices.
- `goci/`, `sentinel/` — raw per-scene rasters and lake-grid metadata (`lake_meta*`).
- `situ/` — in-situ station time series (chlorophyll-*a*, turbidity, and station coordinates only).
- `split_index.csv`, `alignment_index.csv` — (scene, station) match-ups with temporal `split`.
- `goci_station_features.csv`, `olci_station_features.csv` — station-pixel satellite values.
- `station_meta.csv`, `shp/` — station and lake geometry.
Splits are strictly temporal (train ≤2023, val 2024-H1, test 2024-H2).
## Usage
The benchmark code consumes a lake via two environment variables:
```bash
export SCENE_DATA_ROOT=/path/to/bloomfield/tai
export SCENE_META=/path/to/bloomfield/tai/goci/full/lake_meta_taihu.npz
```
Download:
```python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="ALH84001/bloomfield", repo_type="dataset", local_dir="bloomfield")
```
## Companion resources
The benchmark **code** and the small **station × satellite match-up tables** are released separately;
their links are provided upon publication (anonymized during double-blind review).
## License & sources
Released under **CC-BY-4.0**. Underlying Level-2 products (GOCI-II, Sentinel-3 OLCI) are public and
re-downloadable; in-situ readings come from an automatic-analyser station network. See the paper's
Dataset Datasheet appendix for full provenance, collection, and ethics.
## Citation
> BloomField: a benchmark for whole-lake chlorophyll-*a* field reconstruction. *Under review.*
## Raw per-scene rasters (tarballs)
The `*_cache.npy` files already stack every scene for direct use by the code, so most users need only
the caches. For provenance / custom re-gridding we also ship the individual per-scene `.npz` rasters as
per-lake tarballs (Lake Tai GOCI scenes are cache-only):
- `<lake>/scenes_sentinel.tar`, `<lake>/scenes_goci.tar`
Extract inside the lake folder to restore `sentinel/scene_npz/` and `goci/full/scene_npz/`:
```bash
cd tai && tar -xf scenes_sentinel.tar
```
|