What’s New in cartopy 0.14

Date:24th March 2016


  • Zachary Tessler and Raj Kesavan added the cartopy.crs.Sinusoidal projection, allowing MODIS data to be visualised in its native projection. Additionally, a prepared cartopy.crs.Sinusoidal.MODIS projection has been made available for convenience.

  • Joseph Hogg and Daniel Atton Beckmann added the cartopy.geodesic.Geodesic class which wraps the proj.4 geodesic library. This allows users to solve the direct and inverse geodesic problems (calculating distances between points etc). It also contains a convenience function that returns geodetic circles. This is used by cartopy.mpl.geoaxes.GeoAxes.tissot() which draws Tissot’s indicatrices on the axes.


  • The SRTM3 data source has been changed to the LP DAAC Data Pool. The Data Pool is more consistent, fixing several missing tiles, and the data is void-filled. Consequently, the cartopy.srtm.fill_gaps() function has been deprecated as it has no purpose within the STRM context. The SRTM example has also been updated to skip the void-filling step. Additionally, this data source provides SRTM at a higher resolution of 1 arc-second, which may be accessed via cartopy.io.srtm.SRTM1Source.

  • All downloaders will use secure connections where available. Not every service supports this method, and so those will use non-secured HTTP connections instead. (See PR #736 for full details.)

  • Cartopy now supports, and is tested against, matplotlib 1.3 and 1.5 as well as numpy 1.7, 1.8 and 1.10.

  • Daniel Eriksson added a new example to the gallery:


Incompatible changes


  • cartopy.crs.GOOGLE_MERCATOR has been moved to cartopy.crs.Mercator.GOOGLE.

What’s new in cartopy 0.13

Date:30th June 2015


What’s new in cartopy 0.12

Date:14th April 2015


  • We are very pleased to announce that Elliott Sales de Andrade was added to the cartopy core development team. Elliott has added several new projections in this release, as well as setting up cartopy’s Python 3 testing on TravisCI and generally improving the cartopy codebase.

  • Installing cartopy became much easier for conda users. A scitools channel has been added which makes getting cartopy and all of its dependencies on Linux, OSX and Windows possible with:

    conda install -c scitools cartopy
  • Support for Python 3, specifically 3.3 and 3.4, has been added. Some features that depend on OWSLib will not be available as it does not support Python 3.

  • Two new projections, AzimuthalEquidistant and AlbersEqualArea have been added. See the Cartopy projection list for the full list of projections now available in cartopy.

  • The Web Map Service (WMS) interface has been extended to support on-the-fly reprojection of imagery if the service does not support the projection of the map being drawn. The following example demonstrates the process by adding WMS imagery to an Interrupted Goode Homolosine map - unsurprisingly this WMS service does not provide IGH imagery, so cartopy has had to reproject them from a projection the WMS does support:

  • Peter Killick added an interface for accessing MapBox tiles using the MapBox Developer API. A MapBox client can be created with, MapboxTiles and as with the other imagery from a simple URL based imagery service, it can be added to a GeoAxes with the add_image() method. The following example demonstrates the interface for another source of imagery:

  • Some improvements were made to the geometry transformation algorithm to improve the stability of geometry winding. Several cases of geometries being incorrectly inverted when transformed have now been resolved. (PR #545)

  • Mark Hedley added the central_rotated_longitude keyword to cartopy.crs.RotatedPole, which is particularly useful for limited area rotated pole models in areas such as New Zealand:

  • A new method has been added to the GeoAxes to allow control of the neatline of a map drawn with the matplotlib interface. The method, set_boundary(), takes a matplotlib Path object, which means that arbitrary shaped edges can be achieved:

  • A new SRTM3 RasterSource has been implemented allowing interactive pan/zoom of 3 arc-second elevation data from the Shuttle Radar Topography Mission. The SRTM example has also been updated to use the new interface.

  • New additions to the gallery:

    • image_un_flag
    • image_always_circular_stereo
    • image_tube_stations
    • image_wms
    • image_image_tiles


  • The SRTM module has been re-factored for simplicity and to take advantage of the new raster source interface. Some methods have therefore been deprecated and will be removed in future releases. The function cartopy.io.srtm.srtm() has been replaced with the cartopy.io.srtm.SRTM3Source.single_tile() method. Similarly, cartopy.io.srtm.srtm_composite() and cartopy.io.srtm.SRTM3_retrieve() have been replaced with the cartopy.io.srtm.SRTM3Source.combined() and cartopy.io.srtm.SRTM3Source.srtm_fname() methods respectively.
  • The cartopy.io.RasterSource.fetch_raster interface has been changed such that a sequence of cartopy.io.LocatedImage must be returned, rather than a single image and its associated extent.
  • The secant_latitudes keyword in cartopy.crs.LambertConformal has been deprecated in favour of standard_parallels.

What’s new in cartopy 0.11

Date:19 June 2014
  • Richard Hattersley added epsg() support for generating a Cartopy projection at run-time based on the EPSG code of a projected coordinate system. This mechanism utilises https://epsg.io/ as a coordinate system resource and employs EPSG request caching using pyepsg
  • Phil Elson added WMSRasterSource which provides interactive pan and zoom OGC web services support for a Web Map Service (WMS) aware axes. This capability may be added to an axes via the add_wms() method. Generic interactive slippy map panning and zooming capability is managed through the new SlippyImageArtist and use of the add_raster() method.
  • WMTSRasterSource was added by Richard Hattersley to provide interactive pan and zoom OGC web services support for a Web Map Tile Service (WMTS) aware axes, which is available through the add_wmts() method. This includes support for the Google Mercator projection and efficient WTMS tile caching. This new capability determines how to match up the available tiles projections with the target projection and chooses the zoom level to best match the pixel density in the rendered image.

(Source code)

  • Thomas Lecocq added functionality to cartopy.io.srtm allowing intelligent filling of missing elevation data, as well as a function to compute elevation shading for relief style mapping. An example has been added which uses both of these functions to produce a grayscale shaded relief map:

(Source code)

  • Lion Krischer extended the capability of GoogleTiles to allow support for street, satellite, terrain and street_only style Google Map tiles.
  • Nat Wilson’s contribution brought us a major step closer to Python 3 compatibility.
  • Support for the UTM projection was added by Mark Hedley.
  • Andrew Dawson has added a new convenience utility function add_cyclic_point() to add a cyclic point to an array and optionally to a corresponding 1D coordinate.
  • Andrew Dawson added formatters for producing longitude/latitude tick labels for rectangular projections. The formatters are customizable and can be used to produce nice tick labels in a variety of styles:

(Source code)


What’s new in cartopy 0.10

Date:17 January 2014

We are very pleased to announce that Andrew Dawson was added to the cartopy core development team. In this release Andrew has single-handedly implemented comprehensive vector transformation and visualisation capabilities, including:

  • The ability to transform vector fields between different coordinate reference systems via the transform_vectors() CRS method.
  • GeoAxes.quiver and GeoAxes.barbs for arrow and barb plotting. More information is available at Vector plotting.
  • A regridding function for “regularising” a vector field in the target coordinate system. See also cartopy.vector_transform.vector_scalar_to_grid(). Both quiver() and barbs() accept the regrid_shape keyword to trigger this behaviour automatically.
  • GeoAxes.streamplot adds the ability to draw streamlines in any projection from a vector field in any other projection.

(Source code)


What’s new in cartopy 0.9

Date:12 September 2013
  • We are very pleased to announce that Bill Little was added to the cartopy core development team. Bill has made some excellent contributions to cartopy, and his presentation at EuroScipy‘13 on “Iris & Cartopy” was voted best talk of the conference.

  • Other talks and tutorials during this release cycle include Phil Elson’s talk at SciPy‘13 (with video), Thomas Lecocq’s tutorial at EuroSciPy and a forthcoming talk at FOSS4G.

  • Christoph Gohlke updated cartopy to support Windows 7.

  • The Plate Carree projection was updated to fully handle arbitrary globe definitions.

  • Peter Killick updated the Mercator class’ default globe to WGS84. His refactor paved the way for some follow on work to fully implement the Google Spherical Mercator (EPSG:3857) projection.


  • The TransverseMercator class saw a tidy up to include several common arguments (pull request)

  • Bill Little added the Geostationary projection to allow geolocation of satellite imagery.


  • Byron Blay added the Lambert conformal conic projection.

What’s new in cartopy 0.8

Date:3 June 2013
  • Bill Little added support for the OSNI projection and enhanced the image nest capability. (PR #263)
  • cartopy.io.img_nest.Img has been extended to include a cartopy.io.img_nest.Img.from_world_file() static method for easier loading of georeferenced images.
  • Phil Elson added a major performance improvement when plotting data from PlateCarree onto a PlateCarree map. (PR #260)
  • Byron Blay and Richard Hattersley added a cartopy.crs.Globe class to encapsulate ellipsoid and optionally datum information for CRSs. Globe handling in many projections, including Stereographic, has been added.

What’s new in cartopy 0.7

Date:21 Mar 2013

This is a quick release which targets two very specific requirements. The goals outlined in the development plan at v0.6 still remain the primary target for v0.8 and beyond.

What’s new in cartopy 0.6

Date:19 Feb 2013
  • Patrick Peglar added the ability to draw ticks for some limited projections when using the gridlines() method on an Axes.
  • Phil Elson and Carwyn Pelley extended the cartopy documentation to include new tutorials such as Using the cartopy shapereader.
  • Ian Edwards added a new example to create a favicon for cartopy.
  • Phil Elson added a new example to show polygon analysis and visualisation with Shapely and cartopy.
  • Edward Campbell added a new cartopy.crs.EuroPP projection for UTM zone 32.
  • Andrew Dawson added a central_longitude keyword for the Stereographic family of projections.
  • Phil Elson added a Downloader class which allows automatic downloading of shapefiles (currently from Natural Earth and GSHHS). The extension requires no user action and can be configured via the cartopy.config dictionary.

Development plans for cartopy 0.7 and beyond

  • Improve the projection definitions to support better control over datum definitions and consider adding WKT support (ticket).
  • Begin work on vector field support (barbs, quiver, streamlines etc.).
  • Continue identifying and implementing performance enhancements (particularly in contour drawing).
  • Extend the number of projections for which it is possible to draw tick marks.

What’s new in cartopy 0.5

Date:7 Dec 2012

This document explains the new/changed features of cartopy in version 0.5.

Release 0.5 of cartopy continues the work to expand the feature-set of cartopy to encompass common operations, and provide performance improvements.

Cartopy 0.5 features

A summary of the main features added with version 0.5:

  • An improved feature API to support future expansion and sophistication, and a wider range of pre-defined Natural Earth datasets.

Incompatible changes



  • The method Axes.natural_earth_shp() has been replaced by the method Axes.add_feature() and the cartopy.feature module.

Feature API

A new features api is now available, see Using the cartopy shapereader.

import cartopy
import matplotlib.pyplot as plt

def main():

    ax = plt.axes(projection=cartopy.crs.PlateCarree())

    ax.add_feature(cartopy.feature.BORDERS, linestyle=':')
    ax.add_feature(cartopy.feature.LAKES, alpha=0.5)

    ax.set_extent([-20, 60, -40, 40])


if __name__ == '__main__':

(Source code)