.. _sphx_glr_gallery_hurricane_katrina.py:


Hurricane Katrina
-----------------

This example uses the power of Shapely to illustrate states that are likely to
have been significantly impacted by Hurricane Katrina.





.. image:: /gallery/images/sphx_glr_hurricane_katrina_001.png
    :align: center





.. code-block:: python


    import matplotlib.patches as mpatches
    import matplotlib.pyplot as plt
    import shapely.geometry as sgeom

    import cartopy.crs as ccrs
    import cartopy.io.shapereader as shpreader


    def sample_data():
        """
        Return a list of latitudes and a list of longitudes (lons, lats)
        for Hurricane Katrina (2005).

        The data was originally sourced from the HURDAT2 dataset from AOML/NOAA:
        http://www.aoml.noaa.gov/hrd/hurdat/newhurdat-all.html on 14th Dec 2012.

        """
        lons = [-75.1, -75.7, -76.2, -76.5, -76.9, -77.7, -78.4, -79.0,
                -79.6, -80.1, -80.3, -81.3, -82.0, -82.6, -83.3, -84.0,
                -84.7, -85.3, -85.9, -86.7, -87.7, -88.6, -89.2, -89.6,
                -89.6, -89.6, -89.6, -89.6, -89.1, -88.6, -88.0, -87.0,
                -85.3, -82.9]

        lats = [23.1, 23.4, 23.8, 24.5, 25.4, 26.0, 26.1, 26.2, 26.2, 26.0,
                25.9, 25.4, 25.1, 24.9, 24.6, 24.4, 24.4, 24.5, 24.8, 25.2,
                25.7, 26.3, 27.2, 28.2, 29.3, 29.5, 30.2, 31.1, 32.6, 34.1,
                35.6, 37.0, 38.6, 40.1]

        return lons, lats


    def main():
        fig = plt.figure()
        ax = fig.add_axes([0, 0, 1, 1], projection=ccrs.LambertConformal())

        ax.set_extent([-125, -66.5, 20, 50], ccrs.Geodetic())

        shapename = 'admin_1_states_provinces_lakes_shp'
        states_shp = shpreader.natural_earth(resolution='110m',
                                             category='cultural', name=shapename)

        lons, lats = sample_data()

        # to get the effect of having just the states without a map "background"
        # turn off the outline and background patches
        ax.background_patch.set_visible(False)
        ax.outline_patch.set_visible(False)

        ax.set_title('US States which intersect the track of '
                     'Hurricane Katrina (2005)')

        # turn the lons and lats into a shapely LineString
        track = sgeom.LineString(zip(lons, lats))

        # buffer the linestring by two degrees (note: this is a non-physical
        # distance)
        track_buffer = track.buffer(2)

        for state in shpreader.Reader(states_shp).geometries():
            # pick a default color for the land with a black outline,
            # this will change if the storm intersects with our track
            facecolor = [0.9375, 0.9375, 0.859375]
            edgecolor = 'black'

            if state.intersects(track):
                facecolor = 'red'
            elif state.intersects(track_buffer):
                facecolor = '#FF7E00'

            ax.add_geometries([state], ccrs.PlateCarree(),
                              facecolor=facecolor, edgecolor=edgecolor)

        ax.add_geometries([track_buffer], ccrs.PlateCarree(),
                          facecolor='#C8A2C8', alpha=0.5)
        ax.add_geometries([track], ccrs.PlateCarree(),
                          facecolor='none', edgecolor='k')

        # make two proxy artists to add to a legend
        direct_hit = mpatches.Rectangle((0, 0), 1, 1, facecolor="red")
        within_2_deg = mpatches.Rectangle((0, 0), 1, 1, facecolor="#FF7E00")
        labels = ['State directly intersects\nwith track',
                  'State is within \n2 degrees of track']
        ax.legend([direct_hit, within_2_deg], labels,
                  loc='lower left', bbox_to_anchor=(0.025, -0.1), fancybox=True)

        plt.show()


    if __name__ == '__main__':
        main()

**Total running time of the script:** ( 0 minutes  0.348 seconds)



.. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: hurricane_katrina.py <hurricane_katrina.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: hurricane_katrina.ipynb <hurricane_katrina.ipynb>`

.. rst-class:: sphx-glr-signature

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