Census Data!

This map gives a visual representation of the Asian population in the United States by density in the year 2000. The dark pink areas, areas with the highest Asian population density, tend to be in counties with large cities. Los Angeles, the San Francisco Bay Area, Seattle, Chicago, Philadelphia and New York City all show up in dark pink on the map. The lightest pink areas tend to be in Wyoming, Montana, and Nevada. Wyoming and Nevada are not heavily populated areas to begin with, and makes sense that they would be light pink. The light pink areas of Nevada are also not heavily populated.

This map is a visual representation of the Asian population in the United States as a percentage of the county in the year 2000. There are many counties in the Midwestern United States that have no values for an Asian population percentage, meaning that none or very few Asians live in those counties at all. Similar to the population density map, counties with the country's largest cities have a higher percentage of Asians living inside it.

This is a visual representation of counties with an Asian population greater than 25% as of the year 2000. Only two counties in the continental United States meet this criteria: San Francisco County and Santa Clara County. The cities of San Francisco and San Jose are within the borders of these two counties. These two counties have historically had a high Asian population due to migration patterns.

This is a visual representation of the Black population in the year 2000 by population density. Similar to the Asian population maps, the areas with the highest density (dark blue) are around the country's largest cities. Chicago, New York City, Detroit and Los Angeles all show up as dark blue. The Midwestern United States and Idaho, Wyoming, Montana Nevada, Utah, New Mexico and Oregon all have very low rates for Black population density.

This is a visual representation of the percentage of Black population by county in the year 2000. Counties with the percentage of Black population are in the southeastern United States, namely Louisiana, Mississippi, Alabama, Georgia, North and South Carolina, and up to Virginia. The rest of the United States pales (or blues) in comparison to these percentage numbers, even in the big cities. There are even a few counties in the Midwestern counties where there is no data at all. Even entire states are a dark blue (Montana), meaning there is less than a .01% Black percentage across the entire state. Reno, Las Vegas, and San Bernardino and Alameda Counties are the only areas in the western United States that are not some varying shade of blue, and are green instead.

This is a visual representation of counties with Black population greater than 25% in the year 2000. The southeastern United States from Louisiana up to Virgina are all a rose color representing this. There are pockets in the Northern United States with this same rose color, including Chicago, Detroit, and St. Louis. This reflects the history of the Black population in the United States dating back to slavery, and then the migration to the North to big cities to look for better jobs and less racial discrimination.

This is a visual representation of counties with a Some Other Race Population above 25% in the year 2000. All of the dark pink areas which represent above 25% are west of the Mississippi River. The majority of them are also in Texas and California, with one pocket in eastern Washington. My first guess is that these may be people of Native American descent answering the Census in this manner. My second guess is that it may be Hispanic/Latino people answering the Census instead of choosing 'White' as their race. However, we will never know why these people answered in the way they did.

This is a visual representation of counties across the continental United States that have Black, Asian or Some Other Race population greater than 25%. The southeastern and southwestern United States, with some pockets in the north, are the parts of the United States that fit these criteria. It does not seem there is any pattern when Black, Asian and Some Other Race are put together on one map. The only pattern is that they tend to be in the southern United States, which may be just a question of weather preference, a result of racial discrimination, or history. The map tells too little and I personally do not know.

My map series has taught me a lot about the distribution of races across the continental United States. Some patterns fit with historical facts, and some do not. I feel this map can help me understand electoral patterns in regards to race, income patterns in regard to race, and other demographic data that can make a difference when analyzed.

At the end of this exercise, I realize the GIS tests a person's patience skills more than computer skills. Simple mistakes can make an image look sloppy, and it takes a patient soul in order to go back and do everything all over again to get it just right rather than just letting things look the way they are. The attention to detail does not take away from the joy it produces, however. When I look at these maps and see how colorful and how informative they are, I know that it was a product of my blood, sweat and tears. GIS is only as useful as the person at they keyboard makes it out to be. Manipulating data is the most eye-opening part of GIS as it can solve urban planning issues, ethnic tension issues, and every other issue under the sun. I hope to continue working with GIS in this manner.

Lab 6: 3-D Elevation Models!

The Geographic Coordinate System this map receives data from is GCS North American 1983.

Decimal Degrees:
34.51694 degrees North, 119.5483 degrees West
34.51694 degrees North, 118.6316 degrees West
34.015 degrees North, 119.5483 degrees West
34.015 degrees North, 118.6316 degrees West

I chose this area because it encompasses the neighborhood I live in, Chatsworth. Chatsworth is known for its topography, with lots of peaks for hiking such as Stony Point and Rocky Peak. The topography of the area gets steadily more hilly and hits higher elevations as it goes more inland from the Pacific Ocean. These hills are important not only from a geographic standpoint, but serve as the political boundary lines between Los Angeles County and Ventura County. The slope map, unfortunately, does not show variation and is less useful than I hoped it would be.

Lab 5: Projections!

Map Projections
Map projections make all the difference when analyzing a map. They distort the size, the area, the distance, and even can distort our perceptions of the type of people that live in certain areas. For example, the Robinson Map convinced people in the United States that they were superior to people in the southern hemisphere because of the difference in land size. However, this map was skewed and made South America and Africa, two large continents, seem smaller than those of the northern hemisphere. This helped justify imperialism and other extremely racist attitudes towards these people. Projections also make all the difference in distance for sea captains, pilots, and the regular four-door sedan driver. Since distance can vary up to thousands of miles, and since gas is very expensive, the correct map and route is essential for an efficient trip.

Equidistant Projections!

As you can see, just being equidistant does not mean that all related projections are going to look exactly the same. Equidistant conic and equidistant cylindrical cover different parts of the Earth and, thus, produce different distortions of the Earth's land mass. In the equidistant conic projection Antarctica looks very large, as if it's encircling the Earth in an embrace rather than a continent on the South Pole. In the equidistant cylindrical projection Antarctica does not look nearly as imposing, merely large. The equidistant conic also centers the North Pole in the middle of the map, while the equidistant cylindrical projection places the North Pole as the top of the map.

Equal area projections!

The cylindrical equal area map skews the extreme northern and parallels to seem thinner than they actually are. Canada, Greenland, Northern Europe, Russia, and Antarctica seem thin and stretched out at the northern and southern edges of the earth when they are not that way in reality. The Bonne equal area projection makes the Earth into the shape of a heart. While an extremely endearing projection, it is not in any way accurate. Australia and South East Asia are extremely skewed in this projection, making them seem smaller than they actually are.

Conformal projections!

The Eckert I conformal projection map projects the Earth into the shape of a diamond. Another endearing shape, but only accurate in the bulge in the middle. The shapes of the landmasses are impressively well preserved, with only Australia's slight slant as the only thing that really bothers me. The stereographic conformal projection is decidedly different from many projections I've encountered growing up. Australia is an extremely large landmass on this map. So large it doesn't even fit entirely on the map. In fact, New Zealand does not even make it on to the map (nobody likes kiwis anyway). Meanwhile, as Australians assert themselves as the new hegemons, the continent of Africa has been reduced significantly. Could this be another justification for imperialism?

Lab 4

This introduction to geographic information systems was incredibly fun and a lot more rewarding and creative than I thought it was going to be. It took a lot of patience to figure out what exactly were the differences between ArcGIS 9 in the tutorial and ArcGIS 10 as the actual software that was being used. I can see now that geographic information systems takes a lot of patience in general, even if you know what you are doing. The painstaking process of following every direction meticulously drove the point home that this is a software that can do amazing things but only if used correctly. This is why neogeography is a cool phenomenon, but one with many downsides. Having a trained geographer create maps makes all the difference in cartographic processes.

I was concerned that maybe this first tutorial would turn me off from geographic information systems completely. I've thought about careers in public policy and planning and figured that GIS knowledge would assist me greatly in achieving those goals. I thought that if I did not like this experience, I would have to think of new fields to go into. Thankfully, although the process was long, it was fun and only piqued my interest in the planning field even more.

There are many advantages to using geographic information systems. One useful component are the layers. You can mix, match, and manipulate data to show only the information you want out of the tons of information available to you. The organization is impeccable and gets rid of a lot of work that would otherwise have to be done manually. Computers make the process of making maps much quicker than ones done by hand. In the event of an emergency, maps are critical to have, and the quicker processes make response more feasible.

However, the process of learning GIS is time-intensive and does not forgive mistakes easily. People can easily get frustrated with the software and stop from learning it altogether. The software market is also dominated by one company, ESRI, which hinders competition from developing possibly better tools. It is also easy to get carried away with the creativity allowed in GIS. Choosing a certain color scheme has all the effect in the presentation of the data and can either facilitate or harm the point you're trying to make.