This package makes it easy to load, query and save geographic raster datasets in the Python programming language. The package uses Geospatial Data Abstraction Library (GDAL, http://www.gdal.org/) bindings, and so in a single command can import any geo-referenced dataset that is understood by GDAL (http://www.gdal.org/formats_list.html), complete with all geo-referencing information and various helper functions.
GeoRaster is compatible with Python 2.4-3.x. It requires GDAL and its Python bindings to be installed in your environment.
There are two basic types of raster: either a single-band dataset, which you load into a SingleBandRaster
object, or a dataset containing multiple bands to be loaded, which you load into a MultiBandRaster
object.
There is also an 'advanced' option where you can load a raster dataset, manually specifying your geo-referencing information. See example below.
conda install -c conda-forge georaster
http://georaster.readthedocs.io
Before doing anything you must import the package.
import georaster
The examples below also require matplotlib:
import matplotlib.pyplot as plt
Load the image with a single command:
my_image = georaster.SingleBandRaster('myfile.tif')
The single data band is loaded into the r
attribute of my_image
. Use the extent
attribute of the my_image
object to set the coordinates of the plotted image:
plt.imshow(my_image.r,extent=my_image.extent)
In lat/lon (WGS84) - note that this will also set the class georeferencing information to match (i.e. self.nx, .yx, .extent, .xoffset, .yoffset):
my_image = georaster.SingleBandRaster('myfile.tif',load_data=(lonll,lonur,latll,latur),latlon=True)
Or in projection system of the image:
my_image = georaster.SingleBandRaster('myfile.tif',load_data=
(xstart,xend,ystart,yend),
latlon=False)
Each class works as a wrapper to the GDAL API. A raster dataset can be loaded without needing to load the actual data as well, which is useful for querying geo-referencing information without memory overheads. Simply set the load_data
flag to False
:
my_image = georaster.SingleBandRaster('myfile.tif',load_data=False)
print(my_image.srs.GetProjParm('central_meridian'))
(See the 'Accessing geo-referencing information' section below for informtation on srs
)
For example, load GDAL band 2:
my_image = georaster.MultiBandRaster('myfile.tif',band=2)
my_image = georaster.MultiBandRaster('myfile.tif')
plt.imshow(my_image.r)
my_image = georaster.MultiBandRaster('myfile.tif',bands=[1,3])
plt.imshow(my_image.r[:,:,my_image.gdal_band(3)])
from osgeo import osr
spatial_ref = osr.SpatialReference()
# This georef example is from http://nsidc.org/data/docs/daac/nsidc0092_greenland_ice_thickness.gd.html
spatial_ref.ImportFromProj4('+proj=stere +lat_0=90 +lat_ts=71 +lon_0=-39 +k=1 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs')
my_image = georaster.SingleBandRaster('myfile.tif',
geo_transform=(-800000,5000,0,-600000,0,-5000),
spatial_ref=ref)
Once an image is loaded, the object provides the following attributes:
-
Raster.ds : the
GDAL
handle to the dataset, which provides access to all GDAL functions - see http://www.gdal.org/classGDALDataset.html -
Raster.srs : an
OGR Spatial Reference
object representation of the dataset - see http://www.gdal.org/classOGRSpatialReference.html -
Raster.proj : a
pyproj
coordinate conversion function between the dataset coordinate system and WGS84 (latitude/longitude) -
Raster.extent : a
tuple
of the corners of the dataset in its native coordinate system as (left, right, bottom, top). -
Raster.nx, ny : x and y sizes of the loaded raster area.
-
Raster.xres, yres : x and y pixel resolution of loaded raster area.
-
Raster.x0, y0 : the pixel offsets in x and y of the loaded area. These will be zero unless a subset area has been loaded (using
load_data=(tuple)
). -
Raster.get_extent_latlon() : returns WGS84 (lat/lon) extent of raster as tuple.
-
Raster.get_extent_projected(pyproj_obj) : returns raster extent in the coordinate system specified by the pyproj object (e.g. provide a Basemap instance).
-
Raster.coord_to_px(x,y,latlon=True/False) : convert x,y coodinates into raster pixel coordinates.
-
Raster.coordinates() : return projected or geographic coordinates of the whole image (or, with optional arguments, a subset of the image)
Official documentation will shortly be hosted on ReadTheDocs.
- Report bugs, suggest features or view the code on GitHub.
GeoRaster was initially developed by Andrew Tedstone in 2013 whilst at the University of Edinburgh. Andrew Tedstone and Amaury Dehecq continue to develop and maintain the package. GeoRaster was made publicly available in January 2016.
GeoRaster is licenced under GNU Lesser General Public License (LGPLv3).