Lab 6

Lab 5: Spatial Analysis

1. 99 counties in Iowa
2. Fulton
3. 39
4. 3851.14 mi
5. 263,4080 acres

6. 522
7.

8. Doncaster Indian Reserve 17, Kitigan Zibi Indian Reserve, Kahnawake Indian Reserve 14, Kanesatake Indian Reserve 16, and Akwesasne Indian Reserve 15.

Lab 4: Working with Tables

This map shows the percent of the population by county that is African American. I was actually very surprised to see that such a high percent of America's African American population is still concentrated in the South, an obvious vestige of slavery. I decided that a scale and a north star were unnecessary for this map (and the following maps). North is beyond obvious, in my opinion, and I felt a scale was irrelevant to this type of informational map.

This map shows the percent of the population that is Asian American by county. I was not surprised to see high concentrations on the West Coast, as well as the Northeast, Hawaii, and Alaska. I was glad Alaska and Hawaii came into play on this map, since I took the time to figure out how to add them!

This is a map of the percent of "other race" by county. I think this map is not very revealing, since "other race" is an extremely broad and obscuring category (as are all of these maps' categories to some extent). But, based on the patterns of concentration in the Southwest and Florida, I suspect many of these people are Latino/Chicano. This map is helps illustrate how significant this population actually is in America, as they are verging on majority status in many counties.

Together, these maps display that "minorities" are rapidly becoming the majority in America. We often hear statements along these lines, but seeing it graphically helps make it seem more real. I think this is an exciting time for America, and the near future holds a lot of potential for eliminating racist beliefs and laws as we all adjust to America's changing identity. It is obvious we as a country need to give more attention to the issues faced by so-called "minorities." As for my experience using the GIS software, I am definitely starting to understand and enjoy it more. By the time I constructed my last map, I could complete it in only a few minutes. I think my maps are coming out cleaner and more aesthetically pleasing than before as well.

Lab 3: Map Projections

Distances between Washington D.C. and Kabul
Gall stereographic: 7,123.7 miles
Mercator: 10,122.7 miles
Mollweide: 7,900 miles
Bonne: 6,835 miles
Sinusoidal: 8,092 miles
Plate carre 10,112 miles

A map projection is a way of interpreting the three dimensional surface of the Earth onto a two dimensional plane. This is useful because it is not often possible to view the Earth in 3D. Unfortunately, though, all projections have to sacrifice accuracy in area, distance, or shape. Projections can be classified according to what qualities they preserve, and each has specific advantages and disadvantages. Clearly, different projections can give startlingly varied representations of Earth's landmasses.

Mercator and Gall stereographic projections are examples of conformal projections. Conformal projections are characterized by parallels and meridians that intersect at right angles. The advantage of this type of projection is that local shapes and angles are preserved, but area can be variant. For example, on the Mercator, area near the poles is lengthened dramatically, which gives the impression that Greenland and Antarctica are extremely large.

The Mollweide and Bonne projections are examples of equal area projections, which maintain a proportional relationship to areas on the Earth the represent. These maps thus give a good idea of how large landmasses are in relation to one another, but are not so useful for determining how far apart things really are. The last set of maps, the Sinusoidal and Plate carre projections, are equidistant maps. These projections maintain uniform distance from the center of the map to any other place on the map. This is very useful when trying to determine distance from a particular location.

Although one usually thinks of distance as absolute, it is clear from the examples above that attributes like it can be warped depending on the map. Because angles, shapes, and areas can vary so much, one must carefully consider what projection is best for the purpose of the map. However, when the scale is very large, this becomes less important, because the distortion is so small.

Lab 2B: ArcGIS Tutorial

I had a fairly bumpy experience getting through the ArcGIS tutorial. I would not consider myself a "computer person," and being a Mac user thrown into the unknown world of out of date PCs didn't make things easier. I think the most difficult part was navigating Windows, and getting to know how the temporary workspace system worked. I ended up having to do a lot of things over due to improper saving, but it was probably for the better, because it made me more familiar with the software.

The tutorial itself was a little frustrating at first. When following directions from a book (and especially from a PDF), I think it's easy to get into a groove of clicking where you're told, without really understanding what's going on. Especially for some of the more complex operations, I felt there was a lot of jargon, and it was hard to grasp what was really happening. I think in-class/group tutorials are much better because they overcome a lot of these difficulties, and ensure the student is engaged. Regardless, by the time I finally finished the tutorial, I felt like I had a decent grip on what was going on.

It is clear to me that GIS software is very powerful and has a lot of potential. Even just scratching the surface, I was quite impressed with ArcGIS's ability for spatial analysis. I did feel like parts of the program were a little archaic, in a sense, like having to type out your own equations to get population density (vs. just clicking a button?). It seems like it would take a very long time to master all of the functions available in ArcGIS, and it's a little overwhelming.

But just as a tool, GIS is incredibly valuable. The ability to put many layers of information on one map, and to be able to update that continuously is pretty amazing. I'm sure there are applications for GIS that I haven't even begun to think about, which makes the field very exciting. I am glad to be getting into GIS at a time when most of the tedious groundwork and data entry has been completed (thanks!), and to begin analyzing geographic data in constructive ways.

Lab 2A: Participating in Google Maps

View Los Angeles Art Galleries in a larger map

I decided to make a map of art galleries in Los Angeles. I like visiting galleries, but I'm always overwhelmed by the amount of them in LA. So, I decided to use this class project to organize and locate them for myself. Most relevant galleries are located in 3 main clusters: Culver, Chinatown, and Downtown.

I think neogeography is a very exciting development for both geography, and the internet in general. To me, neogeography contains a lot of exciting potential to make insider knowledge more accessible. For example, I use Yelp to help me pick restaurants. This web 2.0 site allows users to submit reviews of all types of businesses, and one can then view them based on geographic location. It's a great way to see what's good in your neighborhood. I am thus able to benefit from the local expertise of many people. When I think about my own knowledge of Los Angeles, it is clear to me that a good deal of it comes from neogeography; where would I be without Google Maps, Yelp, and the Metro trip planner? Probably very, very lost.

Maybe I am naive, but the pitfalls of neogeography seem few. I am not too concerned with "my info getting out" on the net, since I can control what I put out there. I COULD see a problem if my favorite hole-in-the-wall restaurant gets a lot of good reviews and becomes too crowded, though. But overall I think the sharing of local knowledge will help eliminate bad businesses, and perhaps discourage elitism among Angelenos "in the know," as everyone gains access to insider knowledge.

Lab 1B: Reading Topo Maps

1. The name of the quadrangle is Beverly Hills.
2. The adjacent quadrangles are Canoga Park, Van Nuys, Burbank, Topanga, Hollywood, Venice, and Inglewood.
3. The map was first produced in 1966 (and most recently revised in 1999).
4. The datum used was the North American Datum of 1927 and 1983.
5. The scale is 1:24,000
6. a) 5 cm on the map = 1,200 m on the ground.
b) 5 in on the map = 1.894 mi on the ground.
c) 1 mi on the ground = 2.64 in on the map.
d) 3 km on the ground = 12.5 cm on the map
7. The counter interval is 20 ft.
8. a) the Public Affairs Building is at 34.07261 N and 118.43934 W / 34 degrees 4.3566' 21.396'' N and 118 degrees 26.3604' 21.624'' W
b)The tip of the Santa Monica pier is at 34.00743 N and 118.49992 W / 34 degrees .4458' 26.748" N and 118 29.9952 59.712 W
c) the Upper Franklin Canyon Reservoir is at 34.12042 N and 118.41016 W / 34 degrees 702252' 13.512" N and 118 degrees 24.6096' 36.576" W
9. a) the approximate elevation of Greystone Mansion is 560 ft / 170.69 m
b) Woodlawn Cemetary: 140 ft / 42.67 m
c) Crestwood Hills Park: 600 ft /182.88 m
10. The UTM zone is 11S.
11. The UTM coordinates for the lower left corner are around 3762950 and 0361500.
12. 250,000 square meters in each cell of UTM gridlines.
13.













14. The magnetic declination is 14 degrees east.
15. The stream flows south.
16.

Lab 1A: Pick Three Maps

This map created by the World Bank shows urban outdoor particulate air pollution. It assigns different colored points for varying degrees of pollution intensity. I think this visual representation of global urban pollution is interesting because it gives a good idea of which areas contribute the most. I was surprised to see US cities fared quite well, with most cities dark or light green, because the US is always getting blamed for global warming. Of course it is also no surprise to see developing areas like China and India did poorly. This map may be a little misleading, though, because it only counts PM10 particles, and some of the most dangerous particles to human health are much smaller than that.

Originally published in book called Nordisk Familjebok, the next map I picked is of Stockholm's Gamla Stan, or "old town" district. Although there is no scale on this map, the island is only about a kilometer across, making it an optimal size for walking. I am interested in urban geography, and when I visited Stockholm I was struck by how easy it was to get around without motorized transportation. Gamla Stan struck me as the exact opposite of Los Angeles, with its small, winding cobbled streets, and vibrant street life. Car infrastructure was minimal, but I can't imagine wanting to take a car through anyway. I like how this map pretty much tells you all of that, and that looking at a map of Los Angeles would tell you about its grid layout of megablocks, and you would know it was a city for cars. I love that the different character of the two cities can be ascertained just from looking at a map (at least to some extent).

The last map I selected also relates to my interest in urban patterns. This is a map of the growth of Baltimore, Maryland from 1792 to 1992, constructed by NASA using USGS Landsat data. The map therefore spans the majority of American history, and provides a very interesting view of American urban growth patterns. I think it is amazing that urban sprawl has spread so much that almost all land in this snapshot is covered in the last slide, and that was almost 20 years ago! Visuals like this are very helpful to show people how devastating human development has truly been to our environment. To me, the growing sprawl almost looks like a organism, like a mold spreading across the landscape, and I think in a way, the likeness is very telling.