Documentation: https://collijk.github.io/rasterra
Source Code: https://github.com/collijk/rasterra
PyPI: https://pypi.org/project/rasterra/
An in-memory object-oriented raster manipulation library.
rasterra
is a library for manipulating raster data in memory. It is designed to be
used in lieu of rasterio
to allow for
easier manipulation of raster data. It is designed to be used in conjunction with
geopandas
when vector data is also being used.
Currently, rasterra
is in a very early stage of development. It's primary limitation
at this point is that it only supports single-band raster data. Multi-band support is
planned for the near future.
pip install rasterra
Reading and writing raster data is done using the load_raster
and to_file
functions.
import rasterra as rt
# Read in a raster
raster = rt.load_raster("path/to/raster.tif")
# Write a raster to disk
raster.to_file("path/to/output.tif")
A raster can also be read and mosaic'd from multiple files using the load_mf_raster
function.
import rasterra as rt
# Read in a multi-file raster
raster = rt.load_mf_raster(["path/to/raster1.tif", "path/to/raster2.tif"])
rasterra
provides a number of methods for manipulating raster data. These methods
are designed to be used in a method-chaining style, similar to pandas
and geopandas
.
import rasterra as rt
import geopandas as gpd
# Read in a raster
raster = rt.load_raster("path/to/raster.tif")
shapes = gpd.read_file("path/to/polygons.shp")
new_raster = (
raster
.to_crs(shapes.crs) # Reproject the raster to the same CRS as the polygons
.clip(shapes) # Clip the raster to the bounding box of the polygons
.mask(shapes, fill_value=0) # Mask the raster to the polygons, filling in areas outside the polygons with 0
.resample(0.5, 'sum') # Downsample the raster half the original resolution,
# computing the area-weighted sum of the contributing pixels
)