Soil Map

source: http://en.wikipedia.org/wiki/Soil_map

A soil map shows the properties of multiple depths of soil such as pH, type, composition, texture, etc. These maps are great for determining soil quality of an area of viability of a particular land use such as agriculture or even engineering (like a building). The image above shoes a variety of parameters of a particular area of soil including the depth recorded and soil profile.

Google Earth

source: http://en.wikipedia.org/wiki/Google_Earth

Google Earth is basically the greatest map of all time. Not only is it extremely accurate in its projection (because it is shaped like a globe and as you zoom in it is able to adapt new projections) but it also has every kind of map embedded in it or available to download as a add-on. For instance, the map displayed above is a plainmetric map layered with a satellite image, with an application that lets you compare it to a historical black & white aerial map with the capacity to zoom into street view AND see images in 3D. I've seen maps that show the floods of a tsunami. You can travel along the mid-Atlantic ridge or the Rockie mountain ranges.

Bathymetric Map

source: http://en.wikipedia.org/wiki/Bathymetry

Bathymetric maps are similar in concept to hypsometric maps but instead are focused on the depths of underwater "terrain". Early measurements were taken using depth sounding (literally dropping a rope down to the ocean floor and taking a measurement of its depth). Now sonar is used (or LIDAR/LIDAR) to produce a digital read-out of the ocean floor depths.

Mental Map

source: http://www.fedstats.gov/kids/mapstats/concepts_mentalmaps.html

A Mental Map is simply an individual's mental perception of the world they may "know". For instance, my mental map of my drive to work really only consists of a few landmarks including the FSU campus, a few street signs, and the hobos on the corner of Monroe and Tennessee (bad joke). Mental maps come in all shapes, sizes, and creative tastes and are generally completely inaccurate...

Star Plot

source: http://start1.jpl.nasa.gov/caseStudies/autoTool.cfm

First used by Georg von Mayr in 1877, a star plot is a method of displaying multiple variables and characteristics of different statistical observations simultaneously. For a given observation, the length of each ray is made proportional to the size of that variable. This is an effective way of comparing many different observations on a single plain.

Continously Variable Circle Map

source: http://propagandica.wordpress.com/?s=circlesizeisproportionaltotheamounteachcountysleadingcandidateisahead.jpg

A continuously variable circle map demonstrates data points using circles with varying sizes which relate to the proportion of data that is measure at that specific location. For instance, in the example map above (given the appropriate map key), one may infer that where there are relatively large blue circles there were proportionally more Obama voters in those specific precincts.

Accumulative Line Graph

source: http://ingrimayne.com/econ/AllocatingRationing/MeasuringIncomeDist.html

Developed by economist Max Lorenz in 1905, the Lorenz Curve demonstrates the income distribution of a specific population. Economists generally use the Lorenz Curve to measure income inequality. The area between the line of perfect equality and the observed Lorenz Curve is known as the Gini coefficient; the higher the Gini coefficient, the higher the incidence of income inequality.