# rio-l8qa

**Repository Path**: mirrors_mapbox/rio-l8qa

## Basic Information

- **Project Name**: rio-l8qa
- **Description**: Landsat 8 QA band CLI tool and python lib
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-09
- **Last Updated**: 2026-03-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# rio-l8qa

[![Build Status](https://travis-ci.org/mapbox/rio-l8qa.svg?branch=master)](https://travis-ci.org/mapbox/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
```