Census 2000/2010 (Week 8)

Blacks By Country In The Continental US

This choropleth map shown above illustrates the concentration of Blacks in the continental United States, particularly their percentage of the county population according to the 2000 Census. As we can see, counties with high percentages of blacks in their population are mostly located in the Southern U.S., but more specifically, they are located in the states of Georgia, Alabama, Mississippi, and Louisiana. Several counties in those states have the black population making up 47 to 87 percent of the total population. In a nut shell, one only needs to understand the unfortunate institution of slavery in American history to understand this trend. In the West Coast, East Coast, and Midwest, the black population seems to average around 4 to 20 percent of those respective county populations. However, in the Northwest the black population only makes up 0 to 4 percent of the county populations for the most part.

 Asians By Country In The Continental US

This choropleth map shows the concentration of Asians in the continental United States, particularly their percentage of the county population according to the 2000 Census. The asian population is much more dispersed throughout the country than the black population. Concentrations of adjacent counties with high Asian percentages of county population, specifically 7 to 47 percent, are located throughout the West Coast, most notably in California. Note that throughout the continental U.S. there are consistently one or two counties that also have this high density of population. Beginning in their roots in the West Coast until today, Asians seems to have successfully established strong communities throughout the U.S.

"Some Other Race" By Country In The Continental US

This choropleth map shows the concentration of "some other race", in this case Hispanics, in the continental United States. As shown by the previous two, this map shows their percentage of the county population according to the 2000 Census. Similar to the Asian population, Hispanics make up large percentages of county populations in the West Coast in California, specifically 20 to 40 percent. The Hispanics also make up similar large percentages of the Southwest county populations in Arizona, New Mexico, and Texas, where their native country is most nearby. The proximity of this region to Mexico, and the rest of Central and South America clearly explains this phenomenon. It is clear to see that Hispanics have also successfully created strong communities throughout the continental U.S.

This week's lab with emphasis on the census map series made me aware of how complex population analysis can be. It is definitely not as simple as just quantifying each ethnicity as a percentage of the whole United States, because then we would be missing out on most of the valuable spatial data. Only when the data is broken down by sections, such as a county, can we truly see the trends in population growth of each respective ethnicity. It then becomes easy to use the data to assess certain issues and to make the necessary changes to address them. In the bigger picture of utility from these maps, governments can decide where to establish organizations to benefit specific groups of people, and businesses can decide what kind of products to sell and how to advertise in specific areas. This lab, along with the previous labs in this class, have proven to me the invaluable role that GIS has in our world today. Looking at the big picture, powerful spatial analysis is necessary to understand complex social, political, and economic trends, which then enables the necessary policy changes and infrastructure upgrades. My experience with GIS was very straightforward and informative, and I am certain that I will be taking advantage of it in one way or another once I start working as an engineer.

DEMs in ArcGIS (Week 7)

The area I decided to choose is Big Bear Lake in San Bernardino, California. A huge personal fan of skiing, I consider Big Bear the closest and most popular ski resort destination in Southern California. My friends and I come to Big Bear very year and have a lot of experience skiing on its numerous slopes. 

SCALE 1 : 329,899
SPATIAL REFERENCE GCS_North_American_1983
DATUM D_North_American_1983
EXTENT

~top: 34.38 degrees
~left: -117.22 degrees
~right: -116.60 degrees
~bottom: 34.11 degrees

Shaded relief model of Big Bear Lake:

Slop map of Big Bear Lake:

Aspect map of Big Bear Lake:

 

3D image of Big Bear Lake:

Projections in ArcGIS (Week 6)

The process of converting a spherical model onto a planar mode (while preserving certain spatial characteristics, such as distance, area, or shape) is known as map projection. Typically constructed by projecting from within the sphere, map projection enables the creation and utilization of accurate flat maps. With all of its benefits, it must be noted that there is not one map projection type can accurately translate all the spatial characteristics from the sphere to the plane. As a result, we have different projection types which are conformal, equidistant, and equal area, with each having their own distinct advantages and disadvantages that are used accordingly. All these different types of maps, regardless of their accuracies and inaccuracies, enable the convenient representation of maps on a planar surface, conducive to easy distribution and storage of maps that would not be possible with globes.


Certain conformal map projections, such as Mercator and Gall stereographic above, are able to preserve both shape and local angles, creating a system of orthogonal latitude and longitude gridlines. Mercator maps in particular represents rhumb lines derived from an initial bearing as straight lines, and stereographic preserves the shape of circles. On the other hand, conformal maps distort areas which are made obvious by the disproportionate size of Antarctica in both the Mercator and Gall stereographic examples. Equidistant map projections, such as cylindrical and conic shown below, represent accurate distances along designated lines and outward from the center. Unfortunately this type of projection significantly distorts area sizes, and does not necessarily show true distances of the points along the center as we can see in the inaccurate distance between the Americas and Australia in the equidistant conic example. Equal area map projections, such cylindrical and sinusoidal shown below, preserve respective areas but also fail to accurately represent latitude-longitude grid angles. Cylindrical, also known as a Gall-Peters projection, only represent true distances along the 45th parallels north and south. On the other hand, sinusoidal represents the area of the Earth as the area between two symmetrically rotated cosine curves. From both, we can clearly see cylindrical and sinusoidal equal area examples that these gridlines are distorted, simply by comparing both to the conformal Mercator example.

For the purpose of this week's lab, we measured the distance between Washington, D.C. and Kabul and we clearly see the distinctions and differences between the various types of map projections. To determine bearing we can look at both the Mercator and Gall Stereographic conformal map projections. We see that the linearity in all directions dictates that traveling southeast in a straight line will conveniently get me from D.C. to Kabul. To determine true distance, we can look at both cylindrical and conic equidistant map projections. We can also see that mapping of longitudes and latitudes illustrates that the true distance between D.C. and Kabul is around 5,065 to 6,941 miles. And as the name alludes, we can accurately assess the areas of the United States and Afghanistan by referring to both cylindrical and sinusoidal equal area projections. I am certain that interchanging any of these map projection types with the data we are seeking will only result in false measurements.

All map projections have both positive and negative outcomes which depend on what information is being sought. Since it is impossible to accurately translate all spatial data from into a sphere and then to a plane, each projection will preserve some characteristics while significantly distorting the rest. As mentioned before, each map projection has its specific and proper use, which is why any spatial analysis can be rendered erroneous if the wrong type of projection is chosen. This is the reason why it is imperative to be aware of how each map projection was created, what its intention is used for, and what spatial data it excels in translating from the three dimensional to the two dimensional domain.

Learning ArcGIS (Week 4)

My initial experience with ArcMap was made very simple and straightforward by the tutorial that was provided. Parts one and two both took about two hours each of mindless work by simply following the step-by-step directions. Through the process, I was able to combine existing maps with spatial data to output a GIS model of a particular airport expansion project. Many aspects of this program, such as the use of layers and the organization of files, reminded me fondly of other programs such as Photoshop. Before working on this project, I had no idea that there was such powerful and fully-featured modeling software made just for GIS. I can definitely see its value in effectively creating a robust GIS model, while allowing its fast distribution and easy editing if needed.

One of the most important functions of ArcMap is to propose and to answer complicated GIS questions. For this particular lab, the general question that was being addressed was the feasibility of a proposed airport expansion project can be answered by applying various sets of spatial data onto a visual model that anyone can easily understand. For example, the most significant drawback of the project (the increase in the noise level in the area) is represented by a noise contour on the county map. We then overlaid additional layers which contained schools in the area, land use, and population density. This compilation allowed me to determine if the expansion significantly affects any schools, residential zones, or large groups of the county population. 

ArcMap has the ability to allow for the addition of all necessary legends and scales to completely show the information. Various tables, graphs, and colors are used to clearly present data. Within the noise contour, there is one school and a significant residential population. Then it would be up to local government officials to compare this GIS data with local laws and regulations to make a decision. As shown, the strength of ArcMap comes in its ability to analyze and organize a lot of spatial data onto a map, while retaining the flexibility to edit and add data on the fly which I must say is very impressive. The program and its presentation is very polished, allowing the use of many of these features to show GIS information, while remaining very stable and fast. It is definitely made with professional maps and large quantities of data in mind.



In retrospect, while I believe that ArcMap's biggest advantage, with its many features and functions, is also one of  its biggest pitfall. Personally, I feel that the menu-based user interface can be very complicated for casual users. The sheer amount of layers that one has to keep track of can get confusing. And the saving system and file extensions are additional details that a user has to keep in mind, thus further complicating things for the user. A casual user simply cannot pick up the program and start using it as a neogeography tool for their daily lives. This makes it necessary for a professional user to take an in-depth tutorial or class in order to take advantage of all its quirks and features, which limits the widespread use of the program to only within the GIS field and related industries.