Lab Week 8

Week 8

US Counties with Black Population, 2000:

The “US Counties with Black Population, 2000” map that I created displays the distribution and concentrations of African Americans throughout the United States. The map is a Lambert Conformal Conic Projection of the US. It clearly illustrates that the black population is significantly higher in the southern and southeastern states than the rest of the country. I believe this is because the black American population has historical roots in the south. Slavery, although an unfortunate part of America’s past, greatly contributed to the dense black population in the southern and southeastern United States. The map portrays very low densities of black population in the Midwest, west coast, and southwest US. Many black communities throughout the south are low-income areas, and therefore residents do not have the financial capabilities to move. Thus, most of the black population born in the southern US stays there, and therefore we see this trend. I used a red color ramp and am pleased with how it turned out. I feel that the colors are distinguishable and easy to understand.    

US Counties with Asian Population, 2000:

The “US Counties with Asian Population, 2000” map shows the distribution of the Asian population throughout the US. The map itself is a Lambert Conformal Conic Projection. On the map, darker green represents a higher concentration of the Asian population, while lighter green represents lower densities. While creating this map in the university’s computer lab I was happy with the green color ramp that I chose. However, after viewing the map on a few other computers, I found slight variations in the color. Although the higher density dark green colors are easy to distinguish, the lower density light green colors are a bit harder to tell apart, depending on the computer being used to view the map. It is evident that there is a higher concentration of Asian Americans on the west coast of the US than the midwest, south, and eastern parts of the country. I believe this is due to the proximity of the west coast to Asia. California and other parts of the American west coast are the first points of entry for Asians migrating to the US. Highly concentrated populations of Asian Americans have settled on the west coast (especially California) and have established communities such as “Little Saigon” and “Chinatown”. This is why we see such a high concentration of the Asian population on the west coast of the country. However I do want to note that Hawaii is not included on this map. The instructions stated to exclude Alaska and Hawaii, but I believe that Hawaii should have been included, especially on the “Asian Population” map. The Hawaiian Islands contain a high density of Asian individuals due to the proximity to Asia. I believe Hawaii should have been included in this map in order to present a more thorough analysis. 

US Counties with Some Other Race Alone Population, 2000:

The map titled “US Counties with Some Other Race Alone” clearly illustrates what I believe to be the distribution of the Mexican population throughout the United States. The map shows a very high density of the “some other race alone” population throughout the American southwest. Therefore I presume that it is portraying the Mexican American population of the US, because the Mexican population throughout the country is heavily concentrated near the US-Mexico border. Many low-income Mexican immigrants do not have the financial ability to migrate deep into the interior of the United States, so therefore they either choose or are forced to stay near the border. As more immigrants establish communities near the border, new immigrants find it easier to settle in those communities rather than travel far into other states. Therefore the density of the Mexican population continues to be higher in the southwest US than elsewhere in the country. This map is a Lambert Conformal Conic Projection, and uses a light to dark blue color ramp.

Discussion:

I am very pleased with how my census map series turned out. At first I had trouble figuring out how to transfer my data from excel into ArcCatalog and then add it as a data frame onto the map, but once I figured out how to do this the rest of the project was fairly simple. Altogether I believe these three maps give a good representation of race distribution and concentrations throughout the country. The distributions vary widely. Asians seem to be concentrated on the west coast, Hispanics or some other race alone seem to be concentrated in the south and southwest, and blacks are concentrated in the southeast. This map series clearly shows that certain races tend to live within the same region of the country. These census maps show relationships and correlations for which deeper questions can be analyzed. This is the true essence of GIS.

Impressions of GIS:

My overall experience with GIS thus far as been enjoyable. There have been instances where I have felt stuck, lost, and confused with some tasks, but in the end I can usually overcome the challenges. The hardest part of this week’s lab was accessing the data once I had converted it in excel and saved it to my USB drive. I saved them correctly, but maneuvering through ArcCatalog and finding the correct file to upload was tricky. However once I figured out how to do this the rest of the lab was fairly easy.

I find that manipulating the actual layout of the map in ArcMap is fairly easy once you get familiar with the toolbars and the functions of the tabs. Changing the projection, adding a color ramp, adding a legend, adding a north arrow, adding a scale bar, etc. are not difficult to do. It just takes time, and most importantly trial and error, in order to get comfortable with these tools.

One concept that is difficult for me to grasp when it comes to GIS is that different data frames does not mean different maps. When I add new data frames my initial instinct is to want to see multiple maps on the screen. But I must remember that instead there is a base layer, and that all data is layered onto that base map. Instead of seeing multiple maps, I must remind myself to merely check or uncheck the layers in the table of contents in order to see the data portrayed on the base map.

I have enjoyed working with raster data much more than vector data. This weeks lab assignment (Week 8) showed the enormous benefits of raster data. It is able to show distributions, correlations, and patterns that are much harder to see using vector data. Raster depicts patterns and relationships that can be used to answer deeper questions. I prefer working with raster data over vector.

This week’s assignment forced me to realize that proficiency in Microsoft Excel is an important skill when working in the field of GIS. I am not comfortable working with Excel, therefore I will need to work on my own time to teach myself how to use the program. Although my experience with Excel this week was unproblematic, I know that in the future the tasks will become more complicated and I will need a deeper understanding of the program.

The major critiques I have of GIS is that it is not user-friendly, and it takes a long time to create a decent project. ArcMap is not a program like Microsoft Word where individuals can generally teach themselves how to perform basic functions of the program. GIS is not like this. The GIS software is very complicated to the unfamiliar user like myself. Furthermore, each project takes a very long time. Finding data, converting data, joining data, and manipulating that data on the map is a long process. And there are few shortcuts. But if you have the patience and dedication, the final product can be outstanding.

Another critique I have of GIS is that working between data view and layout view is a pain. Sometimes I forget which “view” I’m in and I will unknowingly move text or features of my map to an incorrect position. And there is nothing but a tiny box to tell you which view you are working within. I feel that ArcMap needs to make the view format more visible and noticeable for the user.

GIS is a fantastic tool. In the short time that I have been working with GIS programs I find that it takes a lot of time and patience to become familiar with it, but the more that I work with it the more confident I become. 

Lab 6 (Week 7)

The lab exercise for Week 7 was one of my favorites so far. I enjoy working with raster data much more than vector, as I believe it gives a better representation of reality. One of the main benefits of working with raster data is that it is easy to use, manipulate, and understand. The shaded relief model gives a clear picture of the true landscape, and it is easy to visually understand, even to an individual with no prior experience with GIS. I found that another benefit of working with raster is the ability to overlay data frames and adjust the transparency. This way, it is possible to view multiple layers at a time. Creating the 3D model was my favorite part of the lab, and I believe it is a huge benefit of raster data. The 3D model is a fantastic representation of topographic reality. Although I enjoyed working with raster data, I did notice some potential pitfalls. When a data frame contained too much data the difference in colors became difficult to distinguish. Maps with multiple data fields, such as the aspect map and slope map, consisted of a wide variety of colors that at times made it difficult to understand. The map ended up looking like a complicated rainbow and it was hard to tell the colors apart. Also, with multiple data frames came the challenge of correctly adjusting the transparency in order to view the multiple layers of data at the same time. If all data frames were checked, I found that the shaded relief model was more prominent than the others, which were hidden behind it. I was more interested in this lab assignment than most of the previous assignments. I felt for the first time that I was beginning to get comfortable with ArcMAp. I realize that my knowledge is still rudimentary, but I look forward to continue working with raster data.

Week 6

The creation of map projections has brought with it a number of different benefits. Map projections give humans the ability to view a 3D world on a 2D surface. Paper maps are much more convenient and transportable than spherical globes. Map projections also have been responsible for increasing the public’s geographic awareness and knowledge. Nearly everyone in the world has at one point in time been able to view a world map. Before map projections were created, individuals had to guess as to what the Earth looked like from a bird’s eye view. Now, map projections give an extremely accurate picture of the Earth. This creates a greater awareness of geography and a greater understanding of the world in general. 

The three main types of map projections (equal area, equidistant, and conformal) do indeed have their flaws, but they possess great benefits as well. Equal Area projections, such as the Behrmann Equal Area Projection, give an accurate picture of the true size and area of geographic features, such as countries and continents. This enables the public to understand the true size of geographic features, such as countries and continents. Africa is always portrayed as a small continent, but in reality it is huge. An Equal Area projection accurately depicts Africa’s true size. Equidistant and Conformal projections, such as the Azimuthal Equidistant and Van Der Grintin I, are extremely beneficial for navigation, both for ships and planes. Equidistant shows true distance, and Conformal shows accurate direction. During wartime, these maps are extremely beneficial when planning military attacks, or estimating the missile capabilities of enemy nations.

            Although map projections have great potential and benefits, the pitfalls and flaws are extremely significant. Map distortions are often used to exploit and misrepresent developing countries in the southern hemisphere, especially countries in Africa. Conformal Projections such as the Van der Grinten I and the Stereographic Conformal Projection portray Africa has extremely small in comparison to its actual size, whereas countries in the northern hemisphere are depicted as much larger than in reality. This distortion portrays countries in the northern hemisphere as larger, more powerful, and generally “better” than countries in the southern hemisphere. Unfortunately, the kinds of projections that distort the true size of continents, such as the Mercator Projection, are the kinds of projections used in classrooms across the United States. These map projections have created a northern hemisphere ethnocentricity, and have manipulated most of the world into thinking that countries in the north have dominance and power over poor, developing nations of the south. A map projection may seem objective, but many times there are subtle traces of subjectivity.

            Antarctica is a perfect example of the variability of map projections. Antarctica appears a different shape and size in nearly every map projection. The Ven der Grinten I Conformal and Equidistant Conic Projections portray Antarctica as extremely large, whereas the Azimuthal Equidistant and Stereographic Conformal Projections portray the continent as very small. This is very misleading. Fortunately there are no countries or large permanent colonies on Antarctica, for if there were there would be much debate and discussion over the continent’s portrayal in map projections.    

Furthermore, no map projection is perfect. Each one distorts the earth in a different way and carries with it a number of different flaws. At least one element of a map projection presents false information. This false information can be in regards to shape, size, distance, or direction. This is perhaps the most significant flaw of map projection. Map projections can be skewed and tweaked to purposely misrepresent information. This is why it is always important to reference multiple map projections, and most importantly a spherical globe.