Thanks to Yalemakes and Yale Data Science for inviting me by to discuss one of my favorite topics, GIS. I hope everyone enjoyed the talk and came away with enough to start playing around with QGIS on your own.
In addition to the materials from the discussion, I’ve added a few other helpful resources below.
For reference, the image below shows how GIS data breaks down:
- Two principal types of GIS files: vectors and rasters
- Three types of vector files: points, lines, and polygons
- Each vector file contains two types of data: features (the visible geographic objects) and attributes (non-geographic information that is “linked” to an object)
As long as you know enough of the basic terminology (words underlined below) to properly describe what you want to know, you can find answers to most GIS questions online.
The two concepts below are fundamental to GIS and will come into play for almost any map you make.
The two slides above in PPT format.
Files used in the discussion:
- World map shapefile: website, file
- Hurricane path shapefile: website, file
- Access to electricity %: website, file (reformatted csv file)
Hurricane Map Example
GIS tools can be intimidating. There is an enormous number of menus, options, and settings, and many unfamiliar terms that have little or no meaning outside GIS.
The truth is that most of it applies only to very specialized tasks, mostly for data analysis rather than for making maps. In my experience, to make most maps, only about 6 or 7 of the menu items regularly come into play. The rest you are pretty safe to ignore.
The map below displays every recorded hurricane, cyclone, and typhoon going back about 150 years. Click to see a 3 minute video showing how to make it using QGIS and the files posted above.
Other GIS resources
QGIS – open source GIS program
Sources of GIS data:
- Natural Earth: world borders and water bodies
- GADM: each country broken down by administrative divisions (states, provinces, counties, etc)
- NASA SEDAC: lots of interesting data
- Data.gov: many geospatial datasets
Resources for choosing colors:
- Paletton: fun tool based on various color matching theories
- Color CC: Adobe’s version of Paletton
- Colour lovers: Reddit for color palettes
- Colorbrewer: color schemes for maps with maximum distinguishability