rio-l8qa

Landsat 8 QA band CLI tool and python module

Install

$ pip install rio-l8qa

Python Usage

The l8qa module provides both qa (for Landsat Collection 1 data) and qa_pre (for pre-Collection landsat data). Both provide a number of functions to extract integer data from the respective QA band formats.

• cirrus_confidence

• cloud

• cloud_confidence

• cloud_shadow_confidence

• fill_qa

• lookup

• radiometric_qa

• snow_ice_confidence

• terrain_qa

  And some additional utilty functions to calculate stats or write cloud masks.

• summary_stats

• write_cloud_mask

Example

from l8qa.qa import cloud_confidence
import rasterio

qatif = "LC08_L1TP_005004_20170410_20170414_01_T1_BQA.TIF"

with rasterio.open(qatif) as src:
    yesclouds = cloud_confidence(src.read(1)) == 3  # high confidence

Command Line Usage

The command line interface currently works only with new Landsat collections format. See docs/collections.md for details.

Summary statistics for each of the QA metrics

$ rio l8qa LC08_L1TP_005004_20170410_20170414_01_T1_BQA.TIF \
    --stats
{
  "cloudConf": {
    "maybe": 0.000119,
    "yes": 5e-06,
    "no": 0.486637,
    "notDetermined": 0.513239
  },
  ...
}

To generate output tifs for each QA metric to a directory

$ rio l8qa LC08_L1TP_005004_20170410_20170414_01_T1_BQA.TIF \
    --outdir /tmp
$ ls /tmp
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_cirrusConf.TIF
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_cloud.TIF
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_cloudConf.TIF
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_cloudShadowConf.TIF
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_fill.TIF
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_radiometricSaturation.TIF
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_snowIceConf.TIF
/tmp/LC08_L1TP_005004_20170410_20170414_01_T1_terrain.TIF

If you need a uint8 0-255 cloud mask, suitable for use as an alpha band in an RGBA geotif, there is a shortcut

$ rio l8qa LC08_L1TP_005004_20170410_20170414_01_T1_BQA.TIF \
    --cloudmask /tmp/justclouds.tif