Skip to content

mapbox/rio-cloudmask

Repository files navigation

Build Status Coverage Status

rio-cloudmask

Rasterio plugin for identifying clouds in multi-spectral satellite imagery.

This project is based laregely on the research by Zhu and Woodcock

as well as the subsequent fmask and cfmask software implementations.

Why build our own? The CFmask software produces excellent results but is designed to be part of a larger USGS processing framework, thus bringing with it some implementation overhead and assumptions that prevent easy integration with other systems. In short, we need a pip installable, numpy-based tool that works with GDAL raster formats and integrates well with Rasterio data processing pipelines.

Example

Given this input data from Landsat 8 (LC80130312015295LGN00)

rgb

Assuming we've already derived Top of Atmosphere (TOA) reflectance and brightness temperatures using rio-toa, we can use those to create a uint8 mask suitable for use as an alpha band in an RGBA image:

rio cloudmask LC8*_B[2-7]_toa.tif LC8*_B9_toa.tif LC8*_B10_toa.tif -o test.tif

mask

Status

The first iteration of the cloudmask algorithm implements the potential cloud layer

Still to do...

  • cloud shadow and snow detection (section 3.1 in Zhu, Woodcock 2012 with subsequent changes from 2015 paper) for Landsat 8.

  • Landsat 4-7 (TM/ETM+) sensors lack the cirrus band which is a critical component to high-quality cloud masks. However, the algorithm could be adjusted in the future by optionally ommiting the cirrus tests.

  • Sentinel 2 does not include a thermal band which is heavily used by this implementation. In the future, we may adjust the algorithm (per Zhu, Woodcock 2015, section 2.2.2) to account for this and allow for use with Sentinel 2 data.

  • The object-based cloud and show matching may be implemented at a later time if needed. (per Zhu, Woodcock 2012, section 3.2)

See also

Another Python implementation: Python Fmask

About

Rasterio plugin for identifying clouds in multi-spectral satellite imagery

Topics

Resources

License

Code of conduct

Security policy

Stars

Watchers

Forks

Packages

No packages published

Languages