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Add EnvShip-Voyage: long-term ship trajectory imputation dataset + full build pipeline + docs
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EnvShip-Voyage — Data Card (voyage_v1)

Task. Long-term vessel trajectory imputation (primary) and prediction (secondary) from AIS. Region. DMA (Danish waters), bbox {'lat_min': 53.5, 'lat_max': 59.0, 'lon_min': 7.5, 'lon_max': 14.0}. Ship classes. ['cargo', 'tanker']. Sampling. native 1 min; flagship view 5 min. Windows. [12, 6] h, stride 6 h. Masks. continuous curriculum + MCAR + real gaps (frozen bank, seed 1220). Splits. vessel-disjoint MMSI-hash [0.7, 0.1, 0.2] + temporal pretrain pool. Provenance. DMA AIS (['2026-01', '2026-02', '2026-03', '2026-04', '2026-05', '2026-06']); reuse of EnvShip stages 01-04; see PLAN + RESEARCH_NOTES.

Summary statistics

{
  "n_samples": 179131,
  "splits": {
    "train": 118292,
    "test": 40903,
    "val": 19936
  },
  "window_len_h": {
    "6": 100278,
    "12": 78853
  },
  "difficulty": {
    "medium": 82255,
    "easy": 63205,
    "hard": 33671
  },
  "ship_class": {
    "cargo": 121340,
    "tanker": 57791
  },
  "n_vessels": 5804
}

Comparison

KDD'24 imputation EnvShip (short-term) EnvShip-Voyage
horizon 12 h 10-60 min 12 h / 6 h
sampling 5 min 20 s 1 min native / 5 min flagship
task imputation prediction imputation + prediction
masks cont 6/8/10 h - cont 1-10 h + MCAR + real gaps
environment none anchor raster streaming basemap + fairway network
region prior none coastline fairway / traffic network (first-class)

Intended use / limits

Research benchmark for maritime trajectory imputation and long-horizon prediction. Not for navigation or vessel re-identification. MMSI is pseudonymised. Derived from public AIS + OSM + ETOPO 2022 bathymetry.