As the name suggests, the first map shows the black population of almost every county in the United States. The data are from the US Census Bureau, and were collected in 2000. It measures the population of interest as a percentage of the total county population. These data are represented by various colors, and is displayed on the Lambert conformal conic projection of the contiguous United States. A yellowish color denotes a relatively low percentage (less than or equal to 5 percent) whereas a reddish color denotes a relatively high percentage (55-90%). The map legend breaks the size of the black population into 6 categories: 0.0103-5%; 5-15%; 15-25%; 25-35%; 35-55%; and 55-90%. There is a concentration of counties with a large black population in the southern United States, most notably in the states of Louisiana, Mississippi, Alabama, Georgia, South Carolina, North Carolina, and Virginia. Most of the remaining states have a majority of counties that contain a black population less than 5 percent of the total population, with a few counties in the midwest that have a relatively large black population. Counties that are white indicate that there were insufficient or no data.
The second map shows the asian population of nearly every county in the United States. Like the first map, the data used in this projection are also from the US Census Bureau, collected as part of the 2000 census. Again, the population of interest (asian) is measured as a percentage of the total population of the entire county. Counties with different asian populations are represented with a different set of colors, and this map utilizes the North American conformal conic projection as well. A light blue color represents a relatively small asian population (less than 1 percent) whereas a dark blue indicates a county with a relatively large asian population (greater than 20%). The map legend breaks the sizes of the asian populations into 6 categories: 0.0085-1%; 1-3%; 3-5%; 5-10%; 10-20%; and 20-50%. Counties with the largest Asian populations are found along the west coast of the US, with a concentration of these counties near the bay area of San Francisco, as well as Los Angeles. The Asian population of the remaining counties is sparse and relatively low, with a few counties throughout the midwest and east coast that have large Asian populations. Counties that are white indicate that there were insufficient or no data.
The third map shows the population of some other race in almost every county in the United States. Like the other two maps, the data used are from the US Census Bureau from the 2000 census. The population of interest, which is neither black nor asian, is again measured as a percentage of the total population of the whole county. Counties that have different sized populations of "some other race" are again represented by varying shades of a color. Like the other two, this map also uses the same Lambert conformal conic projection on which to display the data. Light green represents counties with a relatively small "other race" population (less than 2 percent), whereas dark green represents counties with a relatively large "other race" population (greater than 20%). The legend breaks the sizes of the "other race" population into 6 different categories: 0.00795-2%, 2-5%, 5-10%, 10-15%, 15-20%, and 20-40%. Counties that have a large "other race" population are found throughout the western portion of the US, especially in the states of California, Arizona, New Mexico, and Texas. Based on existing cultural and social knowledge, one might infer that "some other race" might refer to Hispanic or Latino. Counties that are white indicate that there were insufficient or no data.
All three of these maps were created by joining spatial data and attribute data. Every map used the same spatial data, which was the Lambert conformal conic projection of the contiguous United States, with the county boundaries present. Each map had its own attribute data, which gave the size of certain populations of interest within counties. Furthermore, each map tells its own story, and certain social or historical implications can be made by a simple analysis of the projections and their data. These three census maps provide an excellent example of the advantages of "joining" data sources, and how GIS can be used to aid in the interpretation and analysis of data of all kinds. They are easily understandable and straight forward, thus making them universal and intended for all.
At the beginning of the quarter, I had absolutely no knowledge of GIS, or how it is used. I have a relatively mild understanding of geography, and I like to see myself as more geographically aware than the average person, but I had no prior knowledge of GIS. It quickly became evident that GIS is a critical component of a large number of fields, and has developed alongside a rapidly evolving technological world. My ineptitude with computers served only as a catalyst for frustration, as the labs at the beginning of the quarter seemed exceedingly difficult and time consuming. As ArcGIS was used more and more in each subsequent lab section, I slowly built up my confidence, and simple tasks and map-making in ArcGIS became easier. I now sufficiently understand the important of geographic information systems, and how it is utilized by almost everyone on a daily basis. Additionally, I also have an understanding of the limitations technology places on GIS, and how knowledge of computers is often required for a productive and stress free GIS experience. GIS is critical in how we perceive and analyze our world, and is only becoming more and more important for all of us.
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