Lab 7: Census 2K, ArcGIS

The map above outlines the distribution of Asian Americans as a percentage of county populations in the United States.  One can see that the highest percentages of Asian Americans live on the West Coast in coastal cities and large urban areas.  The makes sense based solely on the proximity of the West Coast to Asia.  Urban centers on the East Coast also have high density pockets of Asian Americans.  Overall however, Asian Americans seem to be fairly well distributed throughout the continental US, with the majority being in the large coastal urban centers.

This map illustrates the distribution of black populations by county.  It is obvious that the large majority of blacks live in the South Eastern United States.  Other pockets of black populations are in densely urban cities of the north and some on the West Coast.  Examples of these cities are Detroit, Chicago and Los Angeles.  The reason for these pockets outside the South is that during the World Wars of the 20th century, the Great Migration took place.  The Great Migration was the movement of blacks out of the South and into industrial centers in the North and on the West Coast.  These industrial centers provided jobs and a much less hostile environment for blacks.  Many of the counties in the South have extremely high percentages of black populations, due to the fact that many of these counties are small and therefore, lesser numbers are needed to for a high population distribution.  Larger counties elsewhere may have bigger populations of blacks that may make up a smaller percentage.

The term "some other race" is a new term for the US Census that applies to any race outside of the following:  White, Black, Asian American, American Indian, and Native Islander.  "Some other race" therefore constitutes Hispanics and lesser volume international heritages.  In the most recent census, the large majority of the population that classified themselves as "some other race" were Hispanics.  The map above illustrates the census data of those who declared "some other race."  The map above shows very high population densities in the South Western United States.  This is due to the close proximity to the border of Mexico.  Many border towns and counties in Southern California, Arizona, New Mexico, and Texas have very high Hispanic population percentages.  The pockets in Florida are caused by large populations of Dominican and Cuban ethnicity.  These population figures make sense in the context of geographic proximity since the high density Hispanic populations are close to Hispanic countries.

Lab 6: DEMs in ArcGIS

The area that I selected for this lab is in the Sierra Nevada mountain range.  The central part of my map focuses on a small area known as Mineral King, a place where I have been camping since I was born.  Surrounding this area are Sequoia National Park, Kings Canyon National Park, and the Sierra Mountain Range.  The whole geographic area is very mixed with high altitude peaks, river canyons, and low lying foothills, therefore the terrain reflects very well as a DEM and the various models created illustrate a beautiful and multi-faceted landscape.

The geographic coordinate system for this stretch of land is NAD 1983 UTM 11N.  The extant data is as follows.

Top:  36.6249

Left:  -119.0317

Right: -118.3078

Bottom: 36.2624


Shaded Relief Model:

Slope Map:

Aspect Map:

3-D Projection:

Lab 5: Projections in ArcGIS

It's amazing how one week can make a world of difference with regards to using a program.  After last lab, working in ArcGIS was a much more fluid experience, albeit, still taxing.  Basics of the program came naturally, while more advanced concepts were slightly easier to work through.  Creating a map projection in ArcGIS is one of the more simple tools seeing as how all the coordinate systems needed for these projections are already pre-loaded.

With these projections however, there is a large potential for misunderstanding with a user.  The differences between conformal projections and equal-area projections aren't common knowledge, which can lead to misuse of these maps.  From distortion of land masses to preservation of navigation angles, each map projection provides something different.  For someone to try and navigate with an equal area projection would be a grave mistake because conformal maps are the ones that keep navigation angles the same.

For this lab, the standard for measuring the distortion between projections was a linear distance between two points (Washington D.C. and Kabul, Afghanistan).  Some projections had distances around 7,000 miles, while others had distances of more than 10,000 miles.  This drastic difference is an example of how much a map can be distorted, and in the end, how big of a mistake it would be to use one of the projections wrongly.  Of course, it is entirely possible to use these maps correctly, and to utilize their benefits appropriately - for example, using a conformal map for navigation.

While many of these map projections can be confusing, they can also be very beneficial.  The most intricate projection that I created was the Fuller projection.  This one took a long time to render in ArcGIS, a testament to its immense data usage, and looks very intricate.  It uses triangles to correctly preserve area.  While this is the most confusing of the projections, it is also one of the best ones.  

In the end, each of these projections provide useful information to the user.  However, there is a lot of room for error in interpretation if one doesn't know how each projection changes the map, whether it be changes in area or angles.  Regardless, this lab continued to prove the usefulness and power of ArcGIS and the benefits of GIS technologies in general.

Lab 4: Introducing ArcMap

In my time at UCLA, I have been introduced to a few different programs through classes in the Geography department.  Up until this lab, I had never used ArcMap, although I had always seen it on lab computers and heard about it from friends in other GIS classes.  My "Statistics for Geography Majors" class required use of the program R to compute statistical data and assemble raster plots and "Environmental Modeling" required the use of Stella to run modeling equations.  While both of these programs have important roles in the field of GIS, neither of them have the power of ArcMap.

In comparison to Stella and R, ArcMap is a much more flushed out program.  There is the ability to integrate much more information in a more presentable and informative way.  R is severely limited in that is primarily a computational program.  Stella on the other hand is limited because it can only run modeling equations.  While each of these programs do different things, ArcMap has the most power and the widest range of functions.  The interface for ArcMap is also more friendly.  Both R and Stella are single windows with one single page for input.  ArcMap introduces layers and allows for a multitude of views, toolbars and functions to be performed.  It makes sense why ArcMap is one of the leading GIS programs.  It is incredibly powerful and has a flushed out interface.

One of the biggest problems with ArcMap however is its learning curve.  Learning to use ArcMap is very taxing.  Working through the 58 pages of the lab tutorial was a slow process, requiring multiple trips to the computer lab to finish.  Even me as the computer savvy person I am, had trouble at points using this program.  In my opinion, these problems stem from the fact that ArcMap is almost too powerful.  There are so many tools, so many options, and so many different functions that ArcMap can perform.  Of course this isn't a bad thing because it makes the program that much stronger, it just makes learning how to use it a more tedious process.

Another problem with ArcMap, a problem that most software programs have, is price and availability.  With all the programs I have worked with, there is a major barrier to using them.  These programs are very expensive, and in many cases aren't easily available to the general public.  In today's world, with the development of neogeography, programs like ArcMap give the power to make high quality informative maps to everyone.  With high prices and accessibility problems, a severe limit is placed on this possibility.

Overall, ArcMap is an incredible program.  It allows for the user to synthesize all different types of data to make powerful and informative maps, charts and diagrams.  Within a few hours, I, a first time user, was able to create density maps, make land use charts, design new roads and depict the effects of a proposed airport expansion in an easy to understand and easy to read map.  This ability highlights the benefits of powerful programs like ArcMap to the world of GIS.