Week 8: Census Maps

The first map I produced examines the distribution of African Americans throughout the United States by county. As the map shows, counties with a significant percentage african american are located primarily in the South, with the exception of isolated counties in the Midwest and North. This distribution is likely due to the historical presence of african americans in the South, first as slaves and later as inhabitants. Another interesting feature of this map is the relatively high concentrations of African Americans in certain counties, above 80% in some places. This is not seen in any other racial group outside of caucasian, neither Asian or “other races” ever reached above 50% concentration. This is a surprising and intriguing aspect of african american population dispersal within the United States.

The next map I made focused of the percentage of people of Asian decent by county in the United States. This map had quite a different distribution than African Americans, with populations primarily concentrated in the west coast, specifically California and Washington, with some outlying counties in urban centers in Texas and the East Coast. This data seems to intuitively make sense, as the west coast is much closer to Asia and immigrants would be likely to come through there. In addition, many immigrants come over to work in high tech industries, which are primarily based in the San Francisco-Bay Area. The fact that the highest proportion of Asians occurs in the South Bay, where silicon valley is located, seems to confirm this.

The final map showed “other race” population. The is population is primarily latino, but due to the phrasing of the census it is referred to as “some other race.” The population is distributed along the West Coast, with its highest concentrations in southern states. This makes sense, as most latino immigrants would be coming from Central and South American and would therefore enter the United States through the southern border. One unique feature of this population distribution is its presence in rural farming areas such as California’s central valley and eastern Washington. This is likely due to the presence of latino immigrants as farm workers in these ares. The one surprising aspect of this map, which I would like to look into more, is the high concentration of this population in central New Mexico, where neither of the populations I examined previously had been.

Overall this census map series was very interesting to produce. While I had some guesses about what the distributions of these populations would be, it was still informative to see the information displayed visually. The census is a very powerful tool due to the sheer volume of data it has. This data makes a wide variety of analyses possible, and GIS’s compatibility with databases makes it simple to create output such as the maps I made. The only adjustment I really had to make was deciding to map based on percentages instead of absolute numbers, to control for the differing population sizes of different counties. These maps are the tip of the information available for analysis from the census, and it is fortunate that the US government makes the data available for free. Overall, my experience with using GIS and census data to create these maps was a very informative and relatively simple one, and I look forward to visualizing and analyzing more data.

Week 7: Elevation and Raster

The region I selected for this lab is the San Francisco Bay Area in Northern California. San Francisco is at the center of the map at the very edge of the peninsula. The map also shows Napa and Sonoma counties to the North, Monterey at the very southern edge, and Sacramento in the North East. The decimal degree range of the area is from 36.527° to 38.829° North and -121.247° to -123.315° West. The Datum for these maps comes from the North American Datum of 1983. The following maps show elevation, slope and aspect value.

Finally, I made a 3d model of the elevation of the bay area.

Week 6: Map Projections

Map Projections show both the wide variety of uses of geographic data and the potential problems with analyzing that data. At first glance it seems odd that there would be such a wide discrepancy in the distance between Kabul and Washington DC along the maps. Although the great elliptic, which measures the root that would actually be traveled by a person on the earth, remains constant, the planar distance has a 4,000 mile variance, with an error of over 3,000 miles in some maps. It is surprising that map projection choice can have such a large effect.

However, when we look closer it begins to become clear why this happens. When going from a 3 dimensional globe to a 2 dimensional map, certain features will necessarily be lost in translation. Since we have a wide variety of uses for maps it begins to make sense. In some situations maintaining equal area will be important, and we will use the Eckert II, while in others shape will be most valuable and we will use a Stereographic projection. Since we were focusing on measuring distance in this lab, it is therefore unsurprising that some maps are better than others. Different tools are required for different situations, and the wide variety of projections makes it possible to take the same geographic data and use it to answer a wide variety of questions about various attributes.

However all this variety does have its drawbacks, however. The wide spread of results means that it is harder to trust that what you are measuring conforms to reality. Even with the equidistant map projections there was a large discrepancy in planar distance. With Equidistant Conic the planar distance from Washington DC to Kabul was 6,957 miles but with Plattee Carree it measured 10,098 miles. Since these maps are both supposed to be equidistant this result reinforces that every map projection will give slightly different results for planar measurement, making it hard to determine what the true value is.

For all the drawbacks of geographic projections, they are a valuable tool. While planar measurements may be inaccurate, the Great Elliptic distance is constant among all projections, and is a fairly reliable tool. In addition the different maps are helpful for visualization when examining different phenomenon. For example, if I was trying to look at the relative sizes of the United States and Brazil, the cylindrical equal area map would be very helpful while if I was trying to figure out the distance between two points I could use a Plattee Carree. Different map projections help us use a single geographic data set into a wide variety of maps and make it possible to visualize a wider variety of phenomena.

Larger Version of the Image available Here: http://www.flickr.com/photos/aroch/7219679272/in/photostream

Week 4 Lab: ArcGIS Intro

ArcMap and GIS in general are powerful tools, with great potential but also some large difficulties. One of the main strengths of GIS and ArcMap is the ease of editing. Using hand-drawn maps it is impossible to quickly reconfigure elements but with a click and drag on ArcMap one can move elements and even rearrange orders of layers. Drawing a parallel line is not a difficult and time consuming process, requiring geometry and a steady hand, but is as simple as checking the draw parallel box. GIS makes cartographic actions that would have once required extensive time and skill available to even amateur users.

One of the most fascinating applications of GIS, however, is spatial analysis. This is possible only on a computer and only with advanced software such as ArcMap, but it opens up whole new possibilities for geographic knowledge. With a few clicks I was able to produce a chart displaying the number of each type of parcels within the noise contour for the airport, valuable and relevant information that would have required a lot of time and energy to make without ArcMap. Since charts like the one I made are the ultimate reason why we are performing spatial analysis in the first place, to answer geographic questions, GIS and ArcMap’s ability to answer them directly and easily makes them an invaluable tool.

There are drawbacks to GIS and ArcMap however. One of the main strengths, the amount of manipulations possible, is also a drawback. There are so many tools oftentimes it can be difficult to figure out which one is best to use in a situation. I also had a slight interface problem with the zoom function. Many times it was hard to know if I was zooming in the workspace or the actual map, leading to problems I later had to fix. Finally, the computing requirements also present a large drawbacks for many users. While working in the computer labs I had no problems, but trying to use remote access on the internet slowed down the process considerably. In addition, people who don’t have access to relatively new, powerful computers will be unable to use GIS and software such as ArcMap to their full potential.

Even with these drawbacks, GIS and ArcMap are overall valuable tools which are being used to expand our geographic knowledge. Questions that would have before been time intensive to investigate are able to be easily done. Analysis is possible with built in wizards, and in a few clicks it is possible to create valuable info-graphics or whole new layers. This is best evidenced by this week’s lab, where with only 3 hours of time I was able to use the data to create a report that could be used by policy makers to decide if they want to build the airport extension. That is the ultimate purpose of GIS, and geography in general, to give us better ways to understand our world.