eoio.readers.sentinel3_olci.data_io module

eoio.readers.sentinel3_olci.data_io module#

Sentinel-3 OLCI image reading utilities.

This module contains helpers to read radiance bands, uncertainty bands, latitude/longitude coordinates into an xarray Dataset.

Functions follow Sphinx/reST docstring conventions (:param:, :type:, :returns:, :rtype:).

eoio.readers.sentinel3_olci.data_io.read_bands_into_dataset(*, ds: Dataset, layout: S3OLCILayout, meas: List[str], subset: ResolvedROISubset | None, mtd: S3OLCIMetadataExtractor, chunks: Dict[str, int] | None = None, use_chunks: bool = False) → Dataset[source]#

Read radiance bands into an xarray Dataset.

Parameters:

  • ds – Base dataset to which band variables will be added. The dataset is mutated and returned.

  • layout – Layout helper used to locate band files on disk.

  • meas – Sequence of band tokens to read (e.g. ['Oa01']).

  • subset – Optional resolved ROI subset object; when present and containing a clip_box attribute the band arrays will be clipped to that box.

  • mtd – Metadata extractor used to retrieve band-specific metadata.

  • chunks – Optional chunking specification passed to the raster reader.

  • use_chunks – Whether to compute and apply chunking heuristics.

Returns:

The dataset with the requested bands attached.

eoio.readers.sentinel3_olci.data_io.read_lat_lon_coordinates(*, ds: Dataset, layout: S3OLCILayout, subset: ResolvedROISubset | None = None, config: ReaderConfig, chunks: Dict[str, int] | None = None, use_chunks: bool = False) → Tuple[Dataset, Dict[str, Any] | None][source]#

Read latitude/longitude coordinate arrays and attach to ds.

Reads the product’s geo_coordinates.nc file via rioxarray and normalises the stored integer coordinates to degrees. Optionally applies ROI clipping based on a resolved subset and returns a clip-box suitable for later use by image readers.

Parameters:

  • ds – Base dataset to which longitude_300m and latitude_300m will be assigned and set as coordinates.

  • layout – Layout helper used to locate the geo_coordinates.nc file.

  • subset – Optional resolved ROI subset; when provided the function will compute and return an (x_min, y_min, x_max, y_max) clip box.

  • chunks – Optional chunking specification for raster reads.

  • use_chunks – Whether to compute and apply chunking heuristics.

Returns:

Tuple with the updated dataset and an optional clip-box when a subset was supplied.

eoio.readers.sentinel3_olci.data_io.read_tie_geo_coordinates(*, ds: Dataset, layout: S3OLCILayout, subset: ResolvedROISubset | None = None, config: ReaderConfig, chunks: Dict[str, int] | None = None, use_chunks: bool = False) → Tuple[Dataset, Any | None][source]#

Read tie-point grid coordinates and add them to ds.

Reads the tie_geo_coordinates.nc file via rioxarray and extracts tie-point longitude and latitude arrays, applying any requested ROI clipping. The coordinates are scaled using the stored scale_factor attributes and are renamed to x_tie/y_tie coordinate names before being merged into ds.

Parameters:

  • ds – Dataset to which tie-point longitude and latitude will be added.

  • layout – Layout helper for locating the tie_geo_coordinates.nc file.

  • subset – Optional resolved ROI subset for clipping; may be None.

  • config – Reader configuration containing variable selection and read parameters.

  • chunks – Optional chunking specification for raster reads.

  • use_chunks – Whether to compute and apply chunking heuristics.

Returns:

Tuple of (updated dataset, tie-point clip box) where the clip box is returned when subset was provided, otherwise None.

eoio.readers.sentinel3_olci.data_io.read_uncertainty_into_dataset(*, ds: Dataset, layout: S3OLCILayout, meas: List[str], subset: ResolvedROISubset | None, chunks: Dict[str, int] | None = None, use_chunks: bool = False) → Dataset[source]#

Read uncertainty (error) bands and attach them to ds.unc.

Parameters:

  • ds – Dataset to which uncertainty arrays will be attached.

  • layout – Layout helper for locating uncertainty files.

  • meas – Bands for which uncertainties should be read.

  • subset – Optional ROI subset used for clipping.

  • chunks – Chunking specification for raster reads.

  • use_chunks – Whether to compute and apply chunking heuristics.

Returns:

Dataset containing attached uncertainty variables.