Rasterio reads and writes geospatial raster datasets
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README.rst

Rasterio

Rasterio reads and writes geospatial raster data.

https://travis-ci.org/mapbox/rasterio.png?branch=master https://coveralls.io/repos/github/mapbox/rasterio/badge.svg?branch=master

Geographic information systems use GeoTIFF and other formats to organize and store gridded, or raster, datasets. Rasterio reads and writes these formats and provides a Python API based on N-D arrays.

Rasterio supports Python 2.7 and 3.3-3.6 on Linux and Mac OS X.

Read the documentation for more details: https://mapbox.github.io/rasterio/.

Example

Here's an example of some basic features that Rasterio provides. Three bands are read from an image and averaged to produce something like a panchromatic band. This new band is then written to a new single band TIFF.

import numpy as np
import rasterio

# Read raster bands directly to Numpy arrays.
#
with rasterio.open('tests/data/RGB.byte.tif') as src:
    r, g, b = src.read()

# Combine arrays in place. Expecting that the sum will
# temporarily exceed the 8-bit integer range, initialize it as
# a 64-bit float (the numpy default) array. Adding other
# arrays to it in-place converts those arrays "up" and
# preserves the type of the total array.
total = np.zeros(r.shape)
for band in r, g, b:
    total += band
total /= 3

# Write the product as a raster band to a new 8-bit file. For
# the new file's profile, we start with the meta attributes of
# the source file, but then change the band count to 1, set the
# dtype to uint8, and specify LZW compression.
profile = src.profile
profile.update(dtype=rasterio.uint8, count=1, compress='lzw')

with rasterio.open('example-total.tif', 'w', **profile) as dst:
    dst.write(total.astype(rasterio.uint8), 1)

The output:

http://farm6.staticflickr.com/5501/11393054644_74f54484d9_z_d.jpg

API Overview

Rasterio gives access to properties of a geospatial raster file.

with rasterio.open('tests/data/RGB.byte.tif') as src:
    print(src.width, src.height)
    print(src.crs)
    print(src.transform)
    print(src.count)
    print(src.indexes)

# Printed:
# (791, 718)
# {u'units': u'm', u'no_defs': True, u'ellps': u'WGS84', u'proj': u'utm', u'zone': 18}
# Affine(300.0379266750948, 0.0, 101985.0,
#        0.0, -300.041782729805, 2826915.0)
# 3
# [1, 2, 3]

A rasterio dataset also provides methods for getting extended array slices given georeferenced coordinates.

with rasterio.open('tests/data/RGB.byte.tif') as src:
    print src.window(**src.window_bounds(((100, 200), (100, 200))))

# Printed:
# ((100, 200), (100, 200))

Rasterio CLI

Rasterio's command line interface, named "rio", is documented at cli.rst. Its rio insp command opens the hood of any raster dataset so you can poke around using Python.

$ rio insp tests/data/RGB.byte.tif
Rasterio 0.10 Interactive Inspector (Python 3.4.1)
Type "src.meta", "src.read(1)", or "help(src)" for more information.
>>> src.name
'tests/data/RGB.byte.tif'
>>> src.closed
False
>>> src.shape
(718, 791)
>>> src.crs
{'init': 'epsg:32618'}
>>> b, g, r = src.read()
>>> b
masked_array(data =
 [[-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]
 ...,
 [-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]],
             mask =
 [[ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]
 ...,
 [ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]],
       fill_value = 0)

>>> np.nanmin(b), np.nanmax(b), np.nanmean(b)
(0, 255, 29.94772668847656)

Rio Plugins

Rio provides the ability to create subcommands using plugins. See cli.rst for more information on building plugins.

See the plugin registry for a list of available plugins.

Installation

Please install Rasterio in a virtual environment so that its requirements don't tamper with your system's Python.

Dependencies

Rasterio has a C library dependency: GDAL >=1.9. GDAL itself depends on some other libraries provided by most major operating systems and also depends on the non standard GEOS and PROJ4 libraries. How to meet these requirement will be explained below.

Rasterio's Python dependencies are listed in its requirements.txt file.

Development also requires (see requirements-dev.txt) Cython and other packages.

Binary Distributions

Use a binary distributions that directly or indirectly provide GDAL if possible.

Linux

Rasterio distributions are available from UbuntuGIS and Anaconda's conda-forge channel.

Manylinux1 distributions may be available in the future.

OS X

Binary distributions with GDAL, GEOS, and PROJ4 libraries included are available for OS X versions 10.7+ starting with Rasterio version 0.17. To install, run pip install rasterio. These binary wheels are preferred by newer versions of pip.

If you don't want these wheels and want to install from a source distribution, run pip install rasterio --no-binary rasterio instead.

The included GDAL library is fairly minimal, providing only the format drivers that ship with GDAL and are enabled by default. To get access to more formats, you must build from a source distribution (see below).

Windows

Binary wheels for rasterio and GDAL are created by Christoph Gohlke and are available from his website.

To install rasterio, simply download both binaries for your system (rasterio and GDAL) and run something like this from the downloads folder:

$ pip install -U pip
$ pip install GDAL-2.0.2-cp27-none-win32.whl
$ pip install rasterio-0.34.0-cp27-cp27m-win32.whl

Source Distributions

Rasterio is a Python C extension and to build you'll need a working compiler (XCode on OS X etc). You'll also need Numpy preinstalled; the Numpy headers are required to run the rasterio setup script. Numpy has to be installed (via the indicated requirements file) before rasterio can be installed. See rasterio's Travis configuration for more guidance.

Linux

The following commands are adapted from Rasterio's Travis-CI configuration.

$ sudo add-apt-repository ppa:ubuntugis/ppa
$ sudo apt-get update
$ sudo apt-get install gdal-bin libgdal-dev
$ pip install -U pip
$ pip install rasterio

Adapt them as necessary for your Linux system.

OS X

For a Homebrew based Python environment, do the following.

$ brew upgrade
$ brew install gdal
$ pip install -U pip
$ pip install --no-use-wheel rasterio

Alternatively, you can install GDAL binaries from kyngchaos. You will then need to add the installed location /Library/Frameworks/GDAL.framework/Programs to your system path.

Windows

You can download a binary distribution of GDAL from here. You will also need to download the compiled libraries and headers (include files).

When building from source on Windows, it is important to know that setup.py cannot rely on gdal-config, which is only present on UNIX systems, to discover the locations of header files and libraries that rasterio needs to compile its C extensions. On Windows, these paths need to be provided by the user. You will need to find the include files and the library files for gdal and use setup.py as follows.

$ python setup.py build_ext -I<path to gdal include files> -lgdal_i -L<path to gdal library>
$ python setup.py install

We have had success compiling code using the same version of Microsoft's Visual Studio used to compile the targeted version of Python (more info on versions used here.).

Note: The GDAL dll (gdal111.dll) and gdal-data directory need to be in your Windows PATH otherwise rasterio will fail to work.

Development and Testing

See CONTRIBUTING.rst.

Documentation

See docs/.

License

See LICENSE.txt.

Authors

See AUTHORS.txt.

Changes

See CHANGES.txt.