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dhidb

PyPI version CI and release

dhidb provides read-only Python access to a global 300 m, 12-year (2014-2025) Dynamic Habitat Indices time series stored as a dense TileDB array on public S3-compatible object storage. It supports point, bounding-box, and polygon queries without first downloading the complete database.

DHIs are widely used in spatial ecology as interpretable predictors of habitat quality and vegetation dynamics, including covariates in species distribution models (SDMs) and biodiversity assessments.

Installation

pip install dhidb

For development:

python -m pip install -e ".[test]"

Requirements and optional dependencies

DHIDB requires Python 3.10 or newer. The runtime dependencies and the compatibility ranges published by the package are:

Dependency Supported version range
affine >=2.4
numpy >=1.26,<3
pandas >=2.1
pyproj >=3.6
rasterio >=1.3
shapely >=2.0
tiledb >=0.35,<0.38
xarray >=2024.1

Optional features are installed with package extras. There is no generic dhidb[dependency] extra; use the feature-specific extra you need:

Extra Install command Adds
netcdf pip install "dhidb[netcdf]" scipy>=1.11 for NetCDF export
zarr pip install "dhidb[zarr]" zarr>=2.18 for Zarr export
test pip install "dhidb[test]" build, pytest, coverage, Ruff, and SciPy tooling

For local development and testing:

python -m pip install -e ".[test,netcdf,zarr]"

The documentation website has its own Node.js dependencies in website/package.json; they are not part of the Python package extras.

Quick start

from dhidb import DHIProvider

with DHIProvider() as db:
    print(db.years)
    print(db.variables)

    for batch in db.iter_bbox(
        bounds=(12.25, 51.25, 12.50, 51.40),  # Leipzig, Germany
        years=range(2014, 2026),
        variables=["dhi_cum", "dhi_min", "dhi_var", "valid_count"],
        batch_shape={"y": 256, "x": 256},
    ):
        print(batch.sizes)

Documentation

The Docusaurus website source is in website/. Build it locally with:

npm --prefix website install
npm --prefix website run start

Data variables

Variable Meaning Unit
dhi_cum Cumulative productivity from LSP TPROD PPI integral (m2 m-2 day)
dhi_min Minimum seasonal productivity baseline from LSP MINV PPI (m2 m-2)
dhi_var Inter-period GPP coefficient of variation dimensionless
dhi_combined Normalized combined DHI, where available dimensionless
observed_count Number of available 10-day observations scenes
valid_count Number of accepted 10-day observations scenes
qflag_any_count Observations carrying any source quality flag scenes
qflag_rejected_count Observations rejected by quality filtering scenes

License

MIT

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