unpackqa

A python package for QA/QC bit unpacking and labeling in earth science data products

• Works with single QA values, 1D arrays (eg. time series), or 2D arrays (eg. full scenes).
• Get a QA mask in a single line of code: unpackqa.unpack_to_array(qa,'LANDSAT_8_C2_L2_QAPixel','Cloud')
• The same methods are used for all sensors, with specific product flags specified via arguments.
• Common data products are included. Specifying bit flag information manually is also supported.
• No file reading or writing, everything is handled as pre-loaded arrays.
• Requires python 3.6+, with numpy and pyyaml as the only dependencies.

Installation

Install via pip:

pip install unpackqa

Documentation

https://sdtaylor.github.io/unpackqa

Quickstart

import numpy as np
from unpackqa import unpack_to_array

# Specify the Landsat 8 Collection 2 Level 2 QA Pixel
# see all identifiers in unpackqa.list_products()
l8_identifer = 'LANDSAT_8_C2_L2_QAPixel'

qa_array = np.array([[21284,0],[21284,0]])

unpack_to_array(qa_array, product = l8_identifer)
array([[[0, 0, 1, 0, 0, 1, 0, 0, 3, 0, 1, 1],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],

       [[0, 0, 1, 0, 0, 1, 0, 0, 3, 0, 1, 1],
        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]], dtype=uint8)

# The original shape is retained, with a new axis for the 
# 12 Landsat 8 QA flags. 
qa_array.shape
(2,2)
unpack_to_array(qa_array, product = l8_identifer).shape
(2,2,12)

# Masks for individual flags can also be obtained from a dictionary object
from unpackqa import unpack_to_dict

# See flags for each product with unpackqa.list_qa_flags()
flags = ['Cloud','Cloud Shadow']

flag_masks = unpack_to_dict(qa_array, product = l8_identifer, flags=flags)
flag_masks['Cloud'].shape
(2,2)
flag_masks['Cloud Shadow'].shape
(2,2)