LAB 6

LAB 5

1. Iowa has 99 counties
   
2. Fulton county has the highest population in Georgia as of 2001
3. Washington State has 39 cities with a population greater than 15,000
4. The total length of interstates in LA county is 3851 miles.
5. the total urban acres in LA County is 1367445.89

6. there are 522 zip codes in La County.
7. Provinces of Canada
8. Doncaster, Kitigan Zibi, Kahnawake, Kanesatake, and Akwesasne Indian reservations are within 75 miles of Thurso.

Lab 4

The first map in my series show the distribution of Asians throughout the contiguous United States, Alaska, and Hawaii. We can clearly see some trends in the distribution of Asians in the U.S. The most concentrated populations are found in Hawaii and California. Furthermore, there is also a relatively high concentration of Asians in isolated urban areas such as New York, Washington D.C. and Seattle. This suggests that Asian settlement is largely an urban phenomenon.

In my Black population map, clear trends also emerge. we see the highest concentration in the South region. Particularly in a large swath that extends from the southern portion of the Mississippi river to Virginia and the Washington D.C. area in a gentle arc . There is also a high concentration of African Americans in northern cities that used to be industrial centers such as Chicago and Cleveland. The distribution of the African American population is largely the result of historical circumstances. Specifically, the African American settlement in the south is a legacy of slavery. Furthermore, the settlement in northern cities is a result of migration to industrial jobs in the 20th century.

For my map showing the group know as "Some other race," a clear settlement pattern can be seen. Furthermore, I think I know the origin of at least a significant portion of the people who identify as "Some other race." This population is distributed along the U.S. Mexico boarder and extending northward, often in agricultural areas such as California's central valley. Therefore, I believe this population is of Hispanic origin, likely from Mexico and Central America. Furthermore, I think this group identifies as "some other race" because the term Hispanic refers to a linguistic group rather than a racial group. Hispanic people come from different racial backgrounds including Indigenous, European, African, and varies combinations of those. So, Hispanic people may choose to identify as "some other race."

These census maps are a easy way to visualize the makeup of the U.S. population. They are much easier to understand than data in a table. However, the reader still need to keep some things in mind in order to correctly interpret the map. For each map, the data classification is slightly different, so the reader must pay attention to the legend. For example, the darkest color on the Black population choropleth map doesn't represent the same percentage as the darkest color on the Asian population map. On the Black population map, the darkest color represents around 45 to 85 percent, while on the Asian population map, the darkest color represents 25 to 50 percent. The classifications are different to make the map more readable and so the reader can easily see the areas of relative concentration. This is simply a reflection of the data sets, and the relatively smaller number of Asians in the U.S.

Doing this exercise makes me think about the importance of classification in GIS. It seems like the default setting (natural breaks) does a reasonably good job of classifying the data. However, with the manual setting, it is easy to exaggerate the data to the point where it is meaningless. On a choropleth map it is important to remember that color is arbitrary. We have to look at the legend what is going on. A saturated red polygon may appear to have a high value, but it's actual value may only be 0.1%. So, GIS is a powerful tool that needs to be used thoughtfully in order to produce meaningful outcomes.

Map Projections (Lab3)

Understanding map projection is very important because each projection has benefits and drawbacks. There is no such thing as a perfect projection for a world map because flat world maps are fundamentally imperfect. Projecting the irregular sphere of the earth onto a flat map requires compromise. Every time the earth is projected onto a flat surface, the properties of shape, area, distance, direction, baring, and scale can be distorted. Which map projection we choose is determined by the properties we most need the map to preserve.

For my conformal projections, I used Mercator and Gall Stereographic. Conformal projections are designed to preserve angles locally. For the Mercator projection, I measured 10,125 miles between Washington D.C. and Kabul Afghanistan. On the other hand, I measured 7171 miles between Washington D.C. and Kabul in the Gall stereographic projection. There is clearly a massive disparity between the two projections in terms of the distance between the two cities. The actual distance between the two cities is about 6922, so the Gall Stereographic comes much closer to the great circle distance.

I used the Hammer Aitoff projection and the Sinusoidal projection for my equal-area page. These projections are designed to preserve area. Therefore, these projections are useful when we need to calculate land area. I measured 8316 miles between Washington D.C. and Kabul when using the Hammer Aitoff projection. On the other hand, I measured 8114 miles between Washington D.C and Kabul with the Sinusoidal projection. Again, these projections both overstate the distance between the two cities.

Finally, for my equidistant projections, I used Plate Carrée and Equidistant Conic Projections. These projections produced curious results. This is because I measured 10,120 miles between the two cities in the Plate Carrée, while I measured 7010 miles in the Equidistant Conic. The Equidistant Conic projection comes very close to the actual distance. However, the Plate Carrée projection is far from the correct distance. Out of all of the projections I used, the Equidistant Conic does the best job by far of approximating the distance between Washington D.C. and Kabul Afghanistan. It makes me wonder if the Plate Carrée projection in ArcMap is truly equidistant because it does such a poor job of preserving distance.

Intro to ArcMap (LAB2B)

I enjoyed the ArcMap tutorial. I have had some limited experience with ArcMap before, so I thought it might be too easy. However, I was pleasantly surprised by the tutorial because it introduced a lot of GIS functionality quickly. It was definitely worth while and I learned some new tricks.
The aspect of the tutorial that I found most interesting was ArcMap’s ability to select data based on its proximity to features on the map. I’m sure this function could be useful in many situations where one needs to know what is going on in a certain area. An obvious example of this is in the tutorial, where we had to use this function to determine what land uses are near the airport.
Another thing I found useful in this exercise was the section on formatting and layout. Although it is very simple, the align tool saves me a lot of time now that I know how to use it. Furthermore, the section on layout view was very helpful. I hadn’t worked with multiple data frames before. Now that I’ve been introduced to multiple data frames it opens up new possibilities.
ArcMap makes it very easy to put a lot of features on the map very quickly. I think a major challenge with GIS and ArcMap is having enough understanding to know what tool to use out of all of the options. We shouldn’t let the ArcMap tools dictate how we make our maps. Rather, we should first think about what we want to do, and then find the tool to do that specific function.

Environmental Hazards in the Northwest (lab2a)

View Environmental Hazards in the Northwest in a larger map

Neogeography, much like other web 2.0 applications, is all about making previously exclusive fields inclusive. Map making tools are now available to everyone with an internet connection. This means that people can make maps of what they care about. This is quite different from only professional cartographers choosing what to map. This democratization of mapping has some very positive aspects. For one thing, it encourages people to think about spatial issues in their lives that they may not have considered otherwise. Because people can easily put their own information on a map, it allows people to visualize spatial relationships instantly. Furthermore, people can attach information such as text or photos to points on a map and share it with people around the world. Because the information is authored by a peer group, people could potentially get more useful information this way than from older sources such as travel guides. Since people can easily make their own maps, more people will be interested in geography because they can participate in it.

However, there are also some drawbacks to neogeography. Applications such as Google maps may democratize mapping, but they may also be dumbing down maps. It is now so easy to create maps that there is less emphasis on good map design. Furthermore, there may also be less emphasis on making maps that contain important information. Personalized maps may be fun, but they often don't tell the reader anything of substance. Users of neogeography risk getting absorbed in personal information at the expense of more important issues.