# edh-docs > Earth Data Hub (EDH) is a Destination Earth (DestinE) service, operated by B-Open, that provides petabytes of analysis-ready, cloud-optimised (ARCO) Earth data, including ERA5, ERA5-Land, CMIP6, the Climate Adaptation Digital Twin (Climate DT), Copernicus DEM and Sentinel-1 ARD. EDH is built entirely on open standards: datasets are Zarr v3 stores streamed over HTTPS and discovered through a STAC catalogue, so any Zarr-capable tool works without a bespoke SDK. Python with Xarray (zarr-python 3 or later) is recommended. > > Main features and endpoints: > > - STAC catalogue: https://earthdatahub.destine.eu/api/stac/v1 (public, no API key). Each dataset is a STAC item whose `data` asset holds the dataset URL and the arguments to open it with Xarray. Interactive API reference: https://earthdatahub.destine.eu/api/stac/v1/api.html > - Zarr over HTTPS: datasets are served from https://data.earthdatahub.destine.eu as `/-v.zarr`, where a higher version number is newer. Take dataset URLs from STAC or the EDH website rather than guessing them. > - Authentication: a free API key from a DestinE Platform account (https://earthdatahub.destine.eu/quota-api-keys), sent as HTTP basic auth (user `edh`), a bearer token, or through a .netrc file. A public test dataset needs no key. https://api.earthdatahub.destine.eu is an alternative data host. > - Upgraded access: restricted datasets, such as the Climate DT collection, also require DestinE upgraded access. > - Quotas: 500,000 HTTP requests per user per month, where each Zarr chunk read counts as one request. Local caching with fsspec reduces repeated requests. > - Chunking: datasets are map-optimised or time series-optimised, and some are published in both layouts. > - Notebooks: Jupyter notebooks with examples, use cases and best practices, some of which run in the browser in Insula Code Lab. > > The Data Access page covers setup, authentication, quotas, caching and the full STAC and Zarr API reference. Troubleshooting covers common errors (401, 403, 426, 429 and Zarr v3 incompatibilities). Every page is available as Markdown, and llms-full.txt contains the complete documentation in one file. 2026, European Union ## Pages in this subsection - [Getting started with the Earth Data Hub](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/00-getting-started.md): This notebook explains the very first steps to get started with accessing data from the Earth Data Hub (EDH). - [Use case: ERA5-Land monthly averages over Europe](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/05-era5-land-europe.md): Earth Data Hub offers an innovative and super-efficient way to access data. - [Use case: ERA5 on a small area](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/10-use-case-era5-small-area.md): This notebook provides an example of how to compute various climatological averages of one ERA5 variable over a long period of time, e.g. the surface temperature over 30 years. - [Use case: CMIP6 temperature timeseries extraction](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/20-use-case-cmip6-rome.md): This notebook provides an example of how to compare and visualise near-surface air temperature simulated by six different CMIP6 models. - [Use case: Copernicus DEM on a small area](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/30-use-case-copernicus-dem-small-area.md): This notebook provides an example of how to access the Copernicus DEM on a small area, e.g. the surroundings of Rome, with Python and Xarray, and with the GDAL command line tools to crop and reproject it to GeoTIFF files. - [Use case: Sentinel-1 ARD on a small area](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/50-use-case-sentinel-1-small-area.md): This notebook provides an example of how to compute various statistics of Sentinel-1 radiometrically corrected images over a period of time, e.g. over 1 year or 31 acquisition dates, using the Sentinel-1 ARD datasets over Rome, Italy. - [Best practice: transparently cache files on the local filesystem](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/60-best-practice-local-cache-era5-small-area.md): This notebook demonstrates how to use transparent caching of the data chunks on the local file system by leveraging the simplecache directive of fsspec. This is especially useful on slow connections or to save on your EDH request quota. ## Optional - [Top-level llms.txt](https://earthdatahub.destine.eu/docs/llms.txt): Complete documentation index.