QGIS - Revision history

Admin at 05:44, 10 February 2015

2015-02-10T05:44:18Z

← Older revision		Revision as of 05:44, 10 February 2015
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	[[Image:QGIS_DerivedQuantityMap.png\|500px]]		[[Image:QGIS_DerivedQuantityMap.png\|500px]]

			[[Category:GIS]]

2015-02-10T02:44:32Z

Making Quantitative Maps

← Older revision		Revision as of 02:44, 10 February 2015
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	[[Image:QGIS_Military2.png\|500px]]		[[Image:QGIS_Military2.png\|500px]]

	=~~Making~~ Quantitative Maps=		=Visualizing Quantitative Maps=

			This covers how I made and visualized a quantitative map.

			==Creating a Quantitative Map with Python==

	To test out the capabilities of QGIS for creating quantitative maps, I started with each county in California. I obtained GeoJSON for each of the 58 counties using the Census Reporter API. The API call looks like this:		To test out the capabilities of QGIS for creating quantitative maps, I started with each county in California. I obtained GeoJSON for each of the 58 counties using the Census Reporter API. The API call looks like this:
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	</source>		</source>

	Now I use the field "derived_quantity" to control the map color:		==Using Properties to Control Map Style==

			I can start by adding an OpenLayers tile layer to show me the United States in context. Next, I add a vector layer, and add the JSON file I created with the script above, <code>ca_derived_quantity.geojson</code>.

			Now I right click on the vector layer that is created, and pick Properties. I can use the field "derived_quantity" to control the map color:

	[[Image:QGIS_DeriviedQuantityColor.png\|500px]]		[[Image:QGIS_DeriviedQuantityColor.png\|500px]]

2015-02-10T02:40:22Z

Making Quantitative Maps

← Older revision		Revision as of 02:40, 10 February 2015
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	import urllib2		import urllib2

	url = "http://api.censusreporter.org/1.0/geo/show/tiger2013?geo_ids=050\|04000US06"		url = "http://api.censusreporter.org/1.0/geo/show/tiger2013?geo_ids=050\|04000US06"

			county_names = json.load(urllib2.urlopen(url))

	county_names ~~= json.load(urllib2.urlopen(url)~~)		for ii,conty_names in enumerate(county_names):

	~~for ii,conty_names in enumerate~~(~~county_names~~):		derived_quantity = np.random.rand()*10

	derived_quantity = ~~np.random.rand()*10~~		counties['features'][ii]['properties']['derived_quantity'] = derived_quantity

	~~counties['features'][ii]['properties']['derived_quantity'] = derived_quantity~~


			with open('ca_derived_quantity.geojson','w') as f:
			f.write( json.dumps(counties) )

	~~with open('ca_derived_quantity.geojson','w') as f:~~		print "bing! all done!"
	~~f.write( json.dumps(counties) )~~

	print "bing! all done!"
	</source>		</source>

2015-02-10T02:39:47Z

Making Quantitative Maps

@@ Line 86: / Line 86: @@
 </pre>
 <source lang="python">
@@ Line 108: / Line 112: @@
      print "bing! all done!"
 </source>

2015-02-10T02:38:07Z

Making Quantitative Maps

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 <pre>
+{
+    "geometry": {
 </pre>

2015-02-10T02:37:14Z

Basics

← Older revision		Revision as of 02:37, 10 February 2015
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	[[Image:QGIS_Military2.png\|500px]]		[[Image:QGIS_Military2.png\|500px]]

			=Making Quantitative Maps=

			To test out the capabilities of QGIS for creating quantitative maps, I started with each county in California. I obtained GeoJSON for each of the 58 counties using the Census Reporter API. The API call looks like this:

			<pre>
			$ curl "http://api.censusreporter.org/1.0/geo/show/tiger2013?geo_ids=050\|04000US06"
			</pre>

			This means every county (050 is county level) in the state (040 is state level) in state number 06 (California).

			This returns a dictionary with the following structure:

			<pre>




			</pre>

			<source lang="python">
			import json
			import urllib2

			url = "http://api.censusreporter.org/1.0/geo/show/tiger2013?geo_ids=050\|04000US06"

			county_names = json.load(urllib2.urlopen(url))

			for ii,conty_names in enumerate(county_names):

			derived_quantity = np.random.rand()*10

			counties['features'][ii]['properties']['derived_quantity'] = derived_quantity



			with open('ca_derived_quantity.geojson','w') as f:
			f.write( json.dumps(counties) )

			print "bing! all done!"
			</source>

2015-02-07T02:41:17Z

Adding Tiles

← Older revision		Revision as of 02:41, 7 February 2015
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	[[Image:QGIS_Military.png\|500px]]		[[Image:QGIS_Military.png\|500px]]

			By right-clicking on the layer and selecting properties, you can make the polygons transparent and change their colors:

			[[Image:QGIS_Military2.png\|500px]]

2015-02-07T01:17:26Z

Adding Tiles

← Older revision		Revision as of 01:17, 7 February 2015
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	==Adding Tiles==		==Adding Tiles==

			Figured most of this out thanks to the QGIS wiki, [http://wiki.openstreetmap.org/wiki/QGIS]

	The shapefile on its own probably isn't very interesting. You can add the OpenLayers plugin, which allows you to bring in map layers from Google Maps, OpenStreetMap, Bing Maps, etc.		The shapefile on its own probably isn't very interesting. You can add the OpenLayers plugin, which allows you to bring in map layers from Google Maps, OpenStreetMap, Bing Maps, etc.

2015-02-07T01:15:32Z

Adding Tiles

← Older revision		Revision as of 01:15, 7 February 2015
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	[[Image:QGIS_Plugins.png\|500px]]		[[Image:QGIS_Plugins.png\|500px]]

			If we now go to Web > OpenLayers plugin, we can pick from a list of different map layers provided by different services!

			Now I see a much more interesting map of military installations:

			[[Image:QGIS_Military.png\|500px]]

2015-02-07T01:10:54Z

Opening Shapefiles

← Older revision		Revision as of 01:10, 7 February 2015
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	[[Image:QGIS_Shapefile.png\|500px]]		[[Image:QGIS_Shapefile.png\|500px]]

			==Adding Tiles==

			The shapefile on its own probably isn't very interesting. You can add the OpenLayers plugin, which allows you to bring in map layers from Google Maps, OpenStreetMap, Bing Maps, etc.

			[[Image:QGIS_Plugins.png\|500px]]