WARNING: Starting from version 2.0.0, rectifiedgrid grid has been refactored basing basing on xarray and rioxarray packages. Several API have been changed.

RectifiedGrid is a Python package which, combining into a single class several python packages (e.g. xarray, rioxarray, SciPy, shapely, fiona, geopandas, owslib, Cartopy), simplifies geospatial grid-based analyses. Numpy is a notable package for scientific computing with a support for large, multi-dimensional arrays and matrices: starting from version 2.0.0, RectifiedGrid extends xarray introducing an "rg" accessor for adding additional functionalities (e.g. rasterization, 3D manipulation). RectifiedGrid employs rasterio and fiona under the hood for raster and vector I/O and owslib to access data through OGC interoperable services.

RectifiedGrid has been initially developed to support Integrated Coastal Management and Maritime Spatial Planning analyses.

When using RectifiedGrid, you need to make sure that Geopandas is installed with rtree support. Refer to following link for more informations:

• http://geopandas.org/install.html#installing-with-pip
• http://toblerity.org/rtree/install.html

If you want to install Shapely dependency from source for compatibility with cartopy or if you want to use a different version of GEOS than the one included in the project wheels you should first install the GEOS library, Cython, and Numpy on your system (using apt, yum, brew, or other means) and then direct pip to ignore the binary wheels.

$ pip install shapely --no-binary shapely

import rectifiedgrid as rg
grid = rg.read_raster('test/data/adriatic_ionian.tiff', masked=True)
grid.plotmap()

RectifiedGrid wraps Matplotlib Basemap Toolkit functions.

grid.plotmap(rivers=True, countries=True,
             grid=True, coast=True)

import rectifiedgrid as rg

b4 = rg.read_raster('test/data/b04.tiff', masked=True)
b8 = rg.read_raster('test/data/b08.tiff', masked=True)

ndvi = (b8 - b4)/(b8 + b4)
ndvi.plotmap(cmap=cmap_ndvi, legend=True, vmin=-1, vmax=1)

RectifiedGrid implements a function wrapper (wrap_func) to apply array-wise functions.

In this example we use the distance_transform_bf (from scipy.ndimage,morphology) to calculate the distance from the coast for the Adriatic-Inonian region.

from scipy.ndimage.morphology import distance_transform_bf
distances = grid.wrap_func(distance_transform_bf)

# plotting
plt.figure(figsize=[10, 8])
distances.plotmap(rivers=True, countries=True,
             grid=True, coast=True, legend=True)

Please, when you use rectifiedgrid cite as:

Menegon S, Sarretta A, Barbanti A, Gissi E, Venier C. (2016) Open source tools to support Integrated Coastal Management and Maritime Spatial Planning. PeerJ Preprints 4:e2245v2. doi: [10.5334/jors.106] (https://doi.org/10.7287/peerj.preprints.2245v2)