Here is the code: %matplotlib inline import geopandas as gpd import matplotlib as mpl # make rcParams available (optional) mpl.rcParams[’figure.dpi’]= 144 # increase dpi (optional) world = gpd.read_file(gpd.datasets.get_path("naturalearth_lowres")) world = world[world.name != ‘Antarctica’] # remove Antarctica (optional) world[’gdp_per_person’] = world.gdp_md_est / world.pop_est g = world.plot(column=’gdp_per_person’, cmap=’OrRd’, scheme=’quantiles’) g.set_facecolor(’#A8C5DD’) # make the ocean blue (optional)%matplotlib […]
Category: Spatial stuff
Assume that you have a file with some locations as text with one location per line. For example, here are some school names in Copenhagen, Denmark, stored in schools.csv: Hyltebjerg Skole Heibergskolen Ellebjerg Skole Katrinedals Skole Peder Lykke Skolen Amager Fælled Skole Tingbjerg Heldagsskole Øster Farimagsgades Skole Sankt Annæ Gymnasiums Grundskole Lykkebo Skole Randersgades Skole […]
While Redshift does not offer native support for spatial data, indexes and functions, there exists a partial workaround. Redshift supports Python UDFs and can also load custom Python libraries. Out of the box, Redshift has numpy, scipy, pandas and many other useful Python libraries. For spatial functionality, one saving grace is the high quality spatial […]
Gratefully making use of what others have provided, i.e. geopy, Google and plpythonu. Type to hold result of geocoding: CREATE TYPE geocoding AS ( place text, latitude DOUBLE PRECISION, longitude DOUBLE PRECISION );CREATE TYPE geocoding AS ( place text, latitude double precision, longitude double precision ); Function that does the actual geocoding (to be extended […]
Being interested in maps in general, and specifically vector data, of course I had to take the new Google Maps for a spin. Vector data aside, what fascinated me most was the option to display photos of the current location in the bottom of the screen. Seeing actual photos is incredibly more useful than being […]
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List of cloud GIS platforms
This is work in progress… http://geocommons.com/ http://www.giscloud.com/ http://cartodb.com/ http://www.google.com/drive/start/apps.html#fusiontables http://tables.googlelabs.com/ Home http://mapbox.com/ http://mapquest.com http://maps.google.com
This post is very Denmark-specific. I was annoyed that downloading environmental data from the ministry of the environment was so cumbersome. Long story made short, here are download URLs for environmental data: Dataset URL Kirkebyggelinjer KIRKEBYGGELINJER_SHAPE.zip Skovbyggelinjer SKOVBYGGELINJER_SHAPE.zip Åbeskyttelseslinjer AA_BES_LINJER_SHAPE.zip Søbeskyttelseslinjer SOE_BES_LINJER_SHAPE.zip EF Fuglebeskyttelsesområder EF_FUGLE_BES_OMR_SHAPE.zip EF Habitatområder EF_HABITAT_OMR_SHAPE.zip RAMSAR-områder RAMSAR_OMR_SHAPE.zip Naturvildtreservat NATUR_VILDT_RESERVAT_SHAPE.zip There are more. […]
Rtree is a ctypes Python wrapper of libspatialindex that provides a number of advanced spatial indexing features for the spatially curious Python user.
A friend of mine, who is the CEO of a company that develops an embedded database, asked me to do a presentation on spatial indexing. This was an opportunity for me to brush up on R-trees and similar datastructures. Download the slides The presentation introduces R-trees and spatial indexing to a technical audience, who are […]
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Having a look at Spacebase
Spacebase is a spatial datastore that began life as military-grade software, which at least sounds kind of cool. It’s an in-memory database, really, so switch off the cluster and the data is gone. Apparently the same thing was (unknown to the SpaceBase people?) invented in the 90’s by some americans also having the military as […]