Geog 408

Map Critique

Since my lab eight is completed and the population data for Texas has been animated I thought this map seemed appropriate for the end of the class and my work with the Texas census data.  I liked this map because of my work with the states population and thought it a fitting end to the class.  I find this map very humorous, just like the Reagan map that I posted.  The title and data of the map are showing how narrowminded the people of Texas are (not my personal opinion).  How large the map makes Texas follows the saying of “Everything is bigger in Texas” and is a play on their egos.  Another funny bit of the map is the names that the other states are given, except Alaska and Hawaii,  I guess Texans don’t consider them part of the U.S. haha.  A couple of my personal favorite of the state names must be: Uninhabitable (California), Arid Zone (Arizona), Misery (Missouri), Ill Noise (Illanois), Arch Insult (Arkansas), Swamp Land (Florida) – and my favorite of all “Damned Yankee Land” for the states from Pennsylvania to Maine.  The state names are a play on words that some are similar to the acctual state name (Arid Zone, Mint Soda), or just personal opinions or stereotypes about the land that Texans believe (Swamp Land and Damned Yankee Land).  This map is obviously not serious and not to be taken as serious like Reagan’s view of the World, although both are enertaining to look at and figure out what the maps creators think Texan’s are like.

http://chelseahotelnumbertwo.wordpress.com/2007/12/05/a-texan-map-of-the-us/

November 15, 2009

Geog 408

Map Critique

I chose this map because it shows how lopsided the gross deomstic product of the world is.  This is a map is titled “Eliminating the Bottom 5%.”  The article written with this map ask the question of, how do you eliminate half of the planet just by subtracting the bottom 5%.  The map shows that by erasing the countries in the bottom 5% of global GDP, you can eliminate about half of the population of the planet.  The regions of the world that were hit the hardest are most of Africa and Southeast Asia.  This clearly shows how lopsided the global GDP is.  This map would be even more different if Siberia was not included in Russia’s GDP because a major chunk of Asia would be off of the map and would express the lopsidedness even more.  The wealth of the world is located in a small number of countries which is a small portion of earth’s total population. 

 I would like to see a map of the world with the top 10% of the global GDP removed.  The map wouldn’t be completely reversed but most of Europe and North America would be gone.  Even more interesting would be too see a map of the top 10% of the global GDP and emission of green house gases.  I would be willing to bet that these maps, if created, would be very similar.  This one map can lead to the creation of several other maps that would have very political messages. 

http://strangemaps.wordpress.com/2009/07/02/397-eliminating-the-bottom-5/

November 2, 2009

Geog 408

Lab 5

            I chose manual classification because none of the pre-set options worked with my data.  Natural breaks classified data to the extremes with data to close to the middle of the change.  I tried making it equal interval but I wanted to keep the negative values separate from the positive values.  I essentially took equal interval and separated the positive from the negatives.  This was the best solution to keep my data as accurately represented as possible.  The colors were chosen because it kept data in the negative percentage separate from the data in with positive growth.  The lightest color meant it had the lowest percent of growth and the darkest color meant it had the greatest percent of growth.  The classification and color values work together to show which counties grew the most and which counties lost the greatest number of population.

              Again with this map the pre-set classifications would not work.  I chose a manual classification with 6 breaks.  I tried to keep the classification as close to equal interval as possible because that was the best pre-set classification but I wanted the negative percentages separate from the positive percentages.  This represents my data best and keeps similar percentage changes as close as possible.  For my colors I wanted there to be a difference in the negative and positive besides size of symbol so the negative percentages are grey with the largest percentage symbol bigger than the smaller percentage.  I believe this makes the map easier to read and differentiate between negative and positive growth.

October 23, 2009

Geog 408

Map Critique 3

I chose this map, entitled “The World According to Ronald Reagan” because just looking at it I had serious questions.  According to the author of the website the map was  made in 1983 or 1984 and was was also made by left wing opposition to Ronald Reagan.  The website author bases these assuptions on the fact that the cartgrapher included Grenada, Beirut, and The Falklands in the map.  Also it is assumed that the creator of the map is in opposition to Reagan because of the title and how the world is depicted.

The map has so many stereotypes and even racial implementations included in it that Reagan would obviously not agree that this is not how the world is depicted.  First stereotype is that Japan Corporation is in the shape of a litte car.  Next Australia is labled Kangaroos, China is split into their China and our China, Saudi Arabia and the Middle East is split into Israel, our oil and Muslim fanatics.  Cuba is called a Soviet colony, Africa is split into Egypt and “Negroes”, and India is labled “Injuns.” 

The purpose of the map is obviously to show a racial, stereotype minded president.  The map cannot be taken serious, it is offensive to everyone including the U.S. because it is split into California, Republicans and other real Americans, and finally Democrats and welfare Bums.  No person on earth, with any level of education, could have this point of view.

 
http://www.zombietime.com/reagan_world/

October 21, 2009

Geog 408/ Cartography

Lab 4

 DBF / Dbase file – a dbf. file is a form that is used for processing data in ArcGis

 Select by Attributes – is a function of ArcGIS to select features based on their attributes

 Query – tool to give commands, such as when calculating population change or selecting by attributes

 Fields (in a Table) – is the title of the column in the attribute table

 Records (in a Table) – is the information under the field, records are essentially the information in the rows under the fields

 Attributes – information about the data layer – can range from the county fips to information about race or population

 Relational Database – is a way to group different sets of data together by using common attributes or characteristics

 Join function – joins outside information to the data layer based on a common feature

 Monitor Fire – in ArcGIS when joining tables and there are errors it makes you want to set your monitor on fire, haha

 Calculate / Field Calculator – tool in the attribute table, when creating a new field, to do the math right in ArcGIS

October 2, 2009

Geog 408 – Cartography

Map Critique II

            The map I have chosen to critique this week is titled “Percentage of Light Hair in Europe.”  I enjoyed this map because it was not typically a map that would expect to see.  In my opinion, it is not a very serious map, based on the subject, but the creator of the map or someone who found it conducted a decent amount of analysis of the map.  After being serious about why some countries have light (blonde) hair he finishes his blog with a blonde joke. 

            The actual map did have a title, “Percentage of light hair in Europe”, and it also had a legend where the percentage breaks made sense.  Another factor of the legend that I liked were the colors he chose to represent each group i.e. the areas with 80% or more blondes was in a very light color on the beige scale and the people with the lowest percent of light haired people were in a dark brown.  For these factors it makes the map seem serious but the downfall to the map is that there is no scale or north arrow, which are key components to a map.

             The findings of the map and the map creator’s analysis point out the highest percentage of light haired people are found in Sweden, Finland and Norway.  The next highest percentage is on the boundaries of those countries, which is to be expected.  The lowest percentage of light haired people is which is to be expected, around the Mediterranean Sea.  An interesting fact that the creator points out that Germany does not have a high percentage of light haired people, 20- 49%.  All in all this is an interesting map to look at, but how serious a viewer takes it can vary.

Map taken from – http://strangemaps.wordpress.com/2007/12/04/214-the-blonde-map-of-europe/