dep_tools.s2_utils module

This module contains useful functions for working with Sentinel-2 data.

dep_tools.s2_utils.mask_clouds(xr, filters=None, keep_ints=False, return_mask=False)[source]

Mask Sentinel-2 data using the “SCL” band, with optional filters.

The following classes are masked:

  • “SATURATED_OR_DEFECTIVE” (SCL = 1)

  • “CLOUD_SHADOWS” (SCL = 3)

  • “CLOUD_MEDIUM_PROBABILITY” (SCL = 8)

  • “CLOUD_HIGH_PROBABILITY” (SCL = 9)

  • “THIN_CIRRUS” (SCL = 10)

Parameters:

  • xr (DataArray) – Input Sentinel-2 data including, at least, a variable called “scl”, which contains the scene classification band.

  • filters (Optional[Iterable[Tuple[str, int]]]) – Filters to apply, passed to odc.algo.mask_cleanup().

  • keep_ints (bool) – If True, data is kept as input (typically integer) data type, and masking is performed using odc.algo.erase_bad().

  • return_mask (bool) – Whether to return the mask itself along with the data.

Return type:

DataArray

Returns:

If return_mask is False, the input data is returned, with the specified masking applied, If True, then a tuple of (<data>, <mask>).

dep_tools.s2_utils.harmonize_to_old(data)[source]

Harmonize new Sentinel-2 data to the old baseline.

Inspired by https://planetarycomputer.microsoft.com/dataset/sentinel-2-l2a#Baseline-Change

Parameters:

data (xarray.DataArray) – A DataArray with four dimensions: time, band, y, x

Returns:

harmonized – A DataArray with all values harmonized to the old processing baseline.

Return type:

xarray.DataArray