Doppler Radar

 http://www.bom.gov.au/australia/radar/

     Doppler radar is a tool that makes use of the doppler effect to track objects at a distance. This type of technology is most commonly used in meteorology; more specifically used in tracking storms. Doppler radar allows us to pick up a storms size and speed; it can give us this information even days before it hits and area. The doppler radar shown above shows the size and speed of Hurricane Ivan before it hit the Gulf coast. The colors represent the intensity of the storm with red being the strongest.

Univariate Maps

 http://www.dailyyonder.com/poverty-rate-jumps-rural-america/2009/11/23/2466

     A univariate choropleth map is a type of thematic map in which the non-location data is all of the same kind; they only display a single variable. Population density, annual rainfall, and birth rates are all examples of univariate data. This map example shown represents the percentage of Americans living in poverty in different rural countries within the United States in 2008; people in the south seem to have higher poverty rates than those living in the north.

Unstandardized Choropleth Maps

http://jutiagroup.com/20081105-2008-presidential-election-maps-obama-takes-key-swing-states/ 

     Unstandardized choropleth maps are thematic maps which contain data that has not been areally-averaged, though it still allows comparison between variables. This example shows the predictions of the 2008 Presidential Election. It displays the number of electoral votes of each state and is colored (red for republicans, blue for democrats) to indicate which candidate those electoral votes are predicted to go to.

Bivariate Choropleth Map

http://www.geog.le.ac.uk/russianheartland/DemographicMaps/Raions.html    

     A bivariate choropleth map is a thematic map that displays two variables or statistics by using two different sets of symbols or colors in order to illustrate a relationship between the two variables. This example shows the population density and percentage change in that population over a period of time in Russia. This is is considered a bivariate choropleth map because it is displaying the relationship between two variables, population density and percentage population change, and a different color scheme is being used for each variable.

Unclassed Choropleth Map

    

    

 http://www.flickr.com/photos/geminicollisionworks/2108838790/

     Unclassed choropleth maps are similar to classed choropleth maps; however, unclassed choropleth maps do not have an averaged statistic towards each particular color. If you wish to create a map that maintains the data relation, unclassified data theoretically does a better job than classified data because unclassified data allows us to maintain the numerical relations between data. This means that the color shades on an unclassified map are directly proportional to the values of each enumeration unit; there are many shades of each color to show the diversity of the statistics. This unclassified map contrasts the democrats (blue) from the republicans (red). Most states are not completely republican or democratic so there are many shades of the combined blue and red which make a purple hue.

 

Classed Choropleth Maps

https://www.e-education.psu.edu/natureofgeoinfo/book/export/html/1553 

     This type of map allows a variable within different areas to be mapped; this helps with understanding the spatial distribution of this variable over larger distances. The variables that can be measured with this method are limitless. This classed choropleth map was created to show the population of Hispanic people per square kilometer in each state.

Standardized Choropleth Maps

 

http://www.directionsmag.com/articles/choropleth-mapping-with-exploratory-data-analysis/123579 

     Standardized choropleth maps normalize data according to a certain area. They analyze data in the form of a percent so that areas of varying size can be compared to one another. In the choropleth map catagory, the standardized map is a better mapping technique for analyzing data because of the modifiable areal unit problem (MAUP). This example shows the population per square kilometer that is represented for an area divided into multiple areas. This map is standardized because it shows areas of different (population) sizes and depicts them by color so that they can be compared to one another. The darkest areas indicate locations with a higher population.