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rio-pansharpen

Project Description

pansharpens Landsat 8 scenes.

What is pansharpening?

Pansharpening is a process of using the spatial information in the high-resolution grayscale band (panchromatic, or pan-band) and color information in the multispectral bands to create a single high-resolution color image.

P pan-pixel cluster + M single multispectral pixel = M pan-sharpened pixel

Find more examples and information in the Mapbox pansharpening blog post.

Install

We highly recommend installing in a virtualenv. Once activated,

pip install -U pip
pip install rio-pansharpen

Or install from source

git checkout https://github.com/mapbox/rio-pansharpen.git
cd rio-pansharpen
pip install -U pip
pip install -r requirements.txt
pip install -e .

Python API

pansharpen.worker

The worker module pansharpens Landsat 8. Visit the USGS Landsat page page for more information on Landsat 8 band designations.

1. worker.pansharpen

The worker.pansharpen function accepts the following as inputs:

  • numpy 3D array with shape == (3, vis_height, vis_width)
  • affine transform defining the georeferencing of the vis array
  • numpy 2D array with shape == (pan_height, pan_width)
  • affine transform defining the georeferencing of the pan array
  • pansharpening method

and outputs:

  • numpy 3D array with shape == (3, pan_height, pan_width)
>>> from pansharpen import worker
>>> from pansharpen.methods import Brovey
...
>>> pansharpened = worker.pansharpen(vis, vis_transform, pan, pan_transform,
                       pan_dtype, r_crs, dst_crs, weight,
                       method="Brovey", src_nodata=0)

2. worker.calculate_landsat_pansharpen

>>> from pansharpen import worker
>>> from pansharpen.utils import _calc_windows
>>> import riomucho
...
>>> worker.calculate_landsat_pansharpen(src_paths, dst_path, dst_dtype,
        weight, verbosity, jobs, half_window,
        customwindow)

CLI

pansharpen

Usage: rio pansharpen [OPTIONS] [SRC_PATHS]... DST_PATH

  Pansharpens a landsat scene. Input is a panchromatic band (B8), plus 3 color
  bands (B4, B3, B2)

     rio pansharpen B8.tif B4.tif B3.tif B2.tif out.tif

  Or with shell expansion

     rio pansharpen LC80410332015283LGN00_B{8,4,3,2}.tif out.tif

Options:
  --dst-dtype [uint16|uint8]
  -w, --weight FLOAT          Weight of blue band [default = 0.2]
  -v, --verbosity
  -j, --jobs INTEGER          Number of processes [default = 1]
  --half-window               Use a half window assuming pan in aligned with
                              rgb bands, default: False
  -c, --customwindow INTEGER  Specify blocksize for custom windows >
                              150[default=src_blockswindows]
  --help                      Show this message and exit.
  --help                 Show this message and exit.

Comparison of Different Pansharpening Methods

We’ve implemented the Weighted Brovey Transform for pansharpening, which is appropriate for data like Landsat where the panchromatic band is relatively similar in resolution to the color bands.

For more information on other pansharpening methods such as IHS, PCA, P+XS, Wavelet, VWP, Wavelet with Canny Edge Detector etc, please read our notes here.

Release History

Release History

This version
History Node

0.2.0

History Node

0.1.1

History Node

0.1.0

Download Files

Download Files

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
rio-pansharpen-0.2.0.tar.gz (6.6 kB) Copy SHA256 Checksum SHA256 Source Sep 8, 2016

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