Homework 7: Census 2000/2010

As we can see from the map above, the highest concentration of people who identify as Asian is along the West Coast, primarily in Southern California and Northern Washington. I expected to see this, but the high percentage of Asians on the East Coast and in parts of Texas comes as a surprise to me. The distribution ranges from 0.01% to 43.04%.

The legend in the map above tells us that the darkest shade of purple indicates that 49.74% to 86.49% of a county's population consist of people who identify as black. A majority of the counties that fall in this category are in the Southeastern United States, which doesn't surprise me at all. However, I thought that the concentration of blacks in Florida would be higher. The entire distribution ranges from 0.01% to 86.49%.

This map shows the percentage of county populations that consist of some other race. By "some other race", we are referring to people who do not identify as Asian, black, white, American Indian, Alaska Native, Native Hawaiian, or Pacific Islander (according to the Census data). Looking at the map, we can see that most people of "some other race" reside primarily in California, Arizona, New Mexico, and Texas. Because of these states' proximity with the Mexican border, it seems reasonable to believe that what is meant by "some other race" is actually "Hispanic." If this is the case, I found it interesting that the Hispanic population in Washington state is relatively dense.

Much of the information presented in this census map series will not come as a surprise to people who have a basic understanding of U.S. history. Although these maps don't really provide additional insight into the distribution of race in the United States, I found this lab to be very helpful. Creating these maps allowed me to work with real Census data as an application of GIS, increasing my familiarity with ArcGIS.

Over the course of the quarter, my overall impressions of GIS changed dramatically. It has always been clear to me that GIS is a powerful and highly informative tool for organizing, presenting, and analyzing spatial data, but when we first started working with ArcGIS, my frustration with the program's learning curve eclipsed my understanding of its usefulness. However, as we did more and more lab assignments, I became more and more comfortable with the program. Now I fully appreciate the versatility of ArcGIS and GIS in general. Anyone can use GIS to present virtually any kind of geographic information as long as the data is available, and while this accessibility has some drawbacks, I think the benefits of GIS far outweigh the cons.

Homework 6: DEMs in ArcGIS

For this lab, I chose to examine the digital elevation model of Northern Arizona (in the Grand Canyon area). As we can see from the shaded relief model, slope map, aspect map, and 3D image map below, there is drastic variation in the elevation throughout this region, reflecting the extreme highs and lows that characterize the Grand Canyon. In my opinion, the map that best visualizes elevation data is the 3D image map because it makes it much easier for me to perceive the heights. Information about the extent and the geographical coordinate system for this area follow:

Extent Info (decimal degrees): 

Top: 34.73

Left: -113.01

Right: -112.16

Bottom: 34.26

Geographical Coordinate System:
Spatial Reference: GCS_North_American_1983

Datum: D_North_American_1983

3D Image Map

Homework 5: Projections in ArcGIS

Equal Area Projections

Distance between Washington D.C., USA and Kabul, Afghanistan
Sinusoidal
Planar: 8,098 miles
Great Elliptic: 6,934 miles

Cylindrical Equal Area
Planar: 10,108 miles
Great Elliptic: 6,934 miles

Equidistant Projections

Distance between Washington D.C., USA and Kabul, Afghanistan
Azimuthal Equidistant
Planar: 8,341 miles
Great Elliptic: 6,934 miles

Two-Point Equidistant
Planar: 6,648 miles
Great Elliptic: 6,934 miles

Conformal Projections

Distance between Washington D.C., USA and Kabul, Afghanistan
Mercator
Planar: 10,112 miles
Great Elliptic: 6,934 miles

Stereographic
Planar: 9,878 miles
Great Elliptic: 6,934 miles

Because the Earth is a 3D object, a 2D map of the world is guaranteed to be distorted in some way. In  cartography and its applications to geographic information systems, map projections describe the process of this mathematical conversion from ellipsoid to plane. We can categorize these projections by the shape of the developable surface (e.g., planar/azimuthal, cylindrical, conical) and by their preserved properties (e.g., equal area, equidistant, and conformal). Every projection preserves particular surface aspects at the expense of another (or even several others), so the most appropriate map projection varies depending on the purpose of the map.

As indicated in the name, equal area projections (also called equivalent projections) preserve the area. That is, the areas on the map are proportional to the areas on the Earth that they correspond to. However, as we can see from the Sinusoidal and Equal Area Cylindrical projections above, the shapes of the land masses can get significantly distorted, especially as we move away from the center of the Sinusoidal projection or the equator of the Equal Area Cylindrical projection.

Equidistant map projections preserve distance from some standard point or line (generally in the center of the projection). Here these projections are exemplified by the Azimuthal Equidistant and Two-Point Equidistant. The former preserves distances along the great circles extending from the center of the projection, and the latter preserves distances from any point on the map to either of two chosen points. Although the Azimuthal Equidistant projection conserves distances, it compromises on the shape and area, distorting more and more in both aspects as we move away from the center. The same goes for the Two-Point Equidistant projection, but instead the shape and area become more distorted as we move away from the two chosen points.

Conformal projections preserve local shapes and angles. This means that the parallels and the meridians must intersect at the correct angles. The most common conformal map is the Mercator projection, which is shown above along with a Stereographic projection. Looking at these, we can see that the areas are completely misrepresented on the maps. For example, in the Mercator projection, Africa is shown to be only slightly larger than the United States, but in reality, Africa is large enough to fit the United States, China, India, and many other countries. The Stereographic map indicates that Africa is actually smaller than the United States.

Although it is impossible to have a map projection that is 100% accurate in every aspect, map projections are still a very useful and informative way of visualizing the world. What's important is that map viewers ask themselves, "What map projection is being used here? What surface properties have been preserved, and what properties have been distorted?" Those who do not employ this kind of critical thinking can be easily misled by textbooks or news information sources, further perpetuating poor geographical knowledge. In some cases, however, the type of projection used is not of critical importance because the map exists solely for illustration purposes. In addition, the type of projection is not important for large-scale maps because the distortions from projections are not really apparent.

Homework 4: Introducing ArcMap

Shown above is a compilation of several maps showing how the noise from a proposed airport expansion could potentially affect the surrounding areas. To create these maps, I utilized ESRI's geographic information system software, ArcGIS. GIS is a database that allows users to input, manage, view, edit, analyze, and display geospatial data in the form of maps. Used correctly, GIS is a very powerful and highly informative tool that can help with planning or presenting ideas, but as I learned from my experience with ArcGIS, there are detriments as well as benefits.

Much like neogeography, one of GIS's major strengths is its accessibility. Anyone, non-experts included, can create a map as long as they have access to data that is compatible with their GIS software of choice. This accessibility increases geographical awareness for both map creators and map viewers. Of course, the maps that come out of GIS wouldn't be very interesting or informative were it not for the system's ability to effectively handle large quantities of data. In this week's lab, I followed an ArcGIS tutorial which helped me get started on organizing and manipulating data sets related to school locations, land use, and population densities. Being able to visualize these data layers together makes it much clearer how these regional features relate to one another.

Another pro of GIS is its ease of customization. Not only is it incredibly simple to change colors, alter the arrangement of data layers, or add symbols, GIS software can automatically generate map features (e.g., legends, scale bars, and tables) that would otherwise be very time-consuming to create. From my ArcGIS experience, I also found the ease of manipulation to be very helpful as well. The ability to switch between views (i.e., data view and layout view) and to enable/disable data layer visibility made it possible to analyze the data in many different ways.

However, some of the features that make GIS such a useful and important tool are the very things that contribute to its pitfalls. For example, although customizing and manipulating maps with GIS is very easy, it takes a while to get the hang of it. ArcGIS in particular has a steep learning curve because the system's capabilities are seemingly endless, and the program isn't the most user-friendly one. Even though I've gone through the ArcGIS tutorial a couple of times, I still don't feel 100% comfortable with it.

GIS's accessibility is a double-edged sword as well. Regardless of their geography education and training, anyone can create maps using GIS, which means that these maps may not be completely trustworthy. Users of GIS can also be motivated by their own biases, intentionally misrepresenting the data in their maps by either hiding or selectively presenting certain information. Moreover, the technical nature of GIS output can make results seem more reliable than they really are, which may lead to map viewers passively trusting and accepting the professional-looking information in front of them.

Despite its pitfalls, GIS's strengths make it a great and powerful tool for managing, analyzing, and presenting geospatial data, and I look forward to continuing to work with ArcGIS over the course of this quarter.