Lab 7: Census 2000

The above map shows black population as a percent of the total population by county with data provided by Census 2000.  According to the data and this map, the highest percentages of black individuals by county are located in the southeastern United States.  In addition to the counties with the largest percentage of African American being concentrated in the South, the map displays an interesting trend within the region.  The counties with the highest percentage black populations lie in the center of the region and overall become increasingly “less black” moving out from the South.  This pattern suggests that African-American populations could have diffused out from original high concentrations in the center of the South. It is also possible that large numbers of African-American individuals have moved from outlying regions into these “blacker” counties, thus raising the percentages of blacks in those counties.  The data presented in this map aligns with the country’s history as African Americans were brought to the South as slaves. While the South is generally thought of as having a large percentage of blacks, it interesting to see that even a century and a half after slavery was outlawed, these southern counties still have such high concentrations of African-American individuals.

The above map shows counties of the contiguous United Sates with Asian alone populations greater than zero ranked by percent with data from Census 2000.  Whereas the previous map shows counties with high percentages of African-Americans concentrated in a geographic region, this map shows high percentages of Asians in counties of global urban centers and city-regions, notably New York, San Francisco, and Los Angeles.  As on the map of counties ranked by African-American populations, this map shows counties of high Asian populations surrounded by increasingly less-Asian counties.  California and Washington have noticeably more counties with Asians and with higher percentages of Asians than the rest of the country.  This makes sense because the West Coast is the region of the United States that is closer to Asia.  Unlike the previous map, however, this map shows isolated counties with significant Asian populations scattered across the nation, especially in the Midwest.  To me this provokes questions of how and why these scattered inland counties have such high percentages of Asians and what culture in those counties is like, especially compared with the surrounding counties.  I also found it interesting that so many counties in the United States have almost non-existent Asian populations as shown by the beige color on the map. 

The above map shows counties of the contiguous United Sates with “some other race” alone populations greater than zero ranked by percent with data from Census 2000.  According the Census Bureau for Census 2000, the label “some other race alone” indicates an individual who identifies with one specific racial group besides the five minimum race categories required by the Federal Office of Management and Budget which are: White alone, Black or African-American alone, American Indian or Alaska Native alone, Asian alone, and Native Hawaiian or other Pacific Islander alone.  The lack of a required Hispanic/Latino race category and the high population percentages shown in counties in the United States Southwest, especially along the US-Mexico border imply that these counties do indeed depict counties with significant Hispanic/Latino populations.  Personally having lived my entire life in California, first in areas of agriculture in northern California and now in Los Angeles, it is shocking to me that so much of the United States has so many counties with very low percentages of individuals who identify as some other race alone.

Conclusion on Census Map Series:

I thoroughly enjoyed this lab assignment and am satisfied with the resulting map series.  Although this map series is fairly straightforward and for a lab assignment, making these maps felt productive and important.  Being able to see collected data expressed over space, both helps better me understand the information and realize the existing knowledge that I have but may not consciously consider.  I think that even without titles and legends, I, and several others, would be able to identify which map depicts the population percentages of each racial group.  Although expressing Census population data on ArcGIS’s maps appears both visually pleasing and helpful, it does have some shortcomings. While these maps do illustrate ranked percentages of racial groups in space, they do not completely show which counties have the highest (or lowest) actual numbers of these groups.  A county that appears to have a high Asian alone population, for example, may in reality only have a few Asian residents but they could make up a significant percentage of a small total population.  More complicated maps, accompany data tables, and/or using multiple complimentary and related maps could most likely overcome this pitfall of this map series and more truthfully display demographic data over space.  Another shortcoming, more of the Census than these maps, is the reliance on individuals to truthfully and accurately report their respective races.  Binary categories, confusion over labels and instructions, and overall participation in the Census could skew results and lead to inaccurate maps.  Because these maps focus on racial groups, it is possible that the information is even more inaccurate because of language barriers or immigration and residency status that deters or discourages participation by the entire population. 

My overall impressions of GIS are very similar to my conclusion from this lab assignment.  I think the discipline is both fascinating and fun, but I realize that its limitations must be realized and accepted, if not challenged, in order to effectively use and understand GIS.  GIS is an incredibly useful tool that can be used by individuals and professionals in several various fields.  I think that being able to visualize data over space makes the data easier to understand and intensifies its importance or main point.  Additionally, GIS can lead to new realizations or spur new queries and further research.  In this lab assignment, for example, joining the Census racial data to the mapped counties provoked questions for me about distribution of racial groups and the resulting cultures.  Although GIS is a powerful and effective tool, it is crucial to be aware of its pitfalls and challenges in order to best use GIS.  Patience and conciousness may be necessary to read GIS data correctly.  For example, it is important to realize that this lab assignment illustrates racial populations as perecetages and not absolute numbers, as mentioned above.  By maintaining awareness and cautiousness when using GIS, I truly think that individuals can better understand data, space and place, and the significane of spatial phenomena.     

Lab 6: DEMs in ArcGIS

This area is south of Monterrey Bay, directly south of the city of Salinas. It includes Toro Park, Laguna Seca Recreation Area, and the Carmel Valley. This area also includes part of Garrapata State Park; parts of the cities of Monterrey, Carmel, and Gonzales; and sections of the 101 and 1 Freeways. The area is about 21 miles North-South by about 26 miles East-West as very roughly approximated on GoogleMaps. The land contained by this area is utilized for a myriad of uses, including urban and suburban development, a military housing complex, a presidio, recreation areas, golf courses, parks, agriculture, an airport, and roads. The top left corner includes an area of Monterrey Bay and the bottom left corner includes a piece of the Pacific Ocean. The topography varies greatly across the area with hills and valleys.

The approximate location of this area is shown on this GoogleMap image.  The four points represent the four corners of the area's extent given by the DEM model.



The extent information in decimal degrees of this area is described in the DEM model as:
Top: 36.622499999247
Left: -121.91444444567, Right: - 121.450277778972
Bottom: 36.3163888881153

This area is defined by the Geographic Coordinate System North American 1983.

3D Image

Lab 5: Projections in ArcGIS

The variety of map projections and range of layouts and types within each projection category provide several opportunities for how to present geographic information.  For example, both the Bonne and Sinusoidal projections are equal are projections, meaning that they preserve the relative areas of continents and oceans on their maps.  Even so, the two projections appear very different from one another so could be preferred for different presentations of information or other uses.  The sheer number of available map projections mean that users have several options for selecting a projection that best fits a specific use.   

This same extent of options, however, can make choosing and understanding map projections difficult.  Certain map projections are surely better suited for particular purposes, but it can be hard to decide which map projection is most accurate or should be widely used.  The contortion of the graticule on some projections could make locating a point or determining distance especially difficult. 

In addition to complicating decisions about map usages, map projections can make thinking about the real world confusing.  Knowing which distances are accurate can be difficult, especially with limited knowledge of map projections or measurement types.  It is easier to understand why the Planar measurement changes projection to projection, but difficult to know when the Planar measurement is an accurate representation of distance.  Because the Geodesic and Great Elliptic measurements remained constant throughout the six projections and similar to one another, it seems reasonable to assume that the distance between Washington, D.C. and Kabul is indeed about 6,934.48 miles.  The Loxodromic measurement also remained constant across all the projections though, but gave a distance of 8,112.06 miles between the two cities.  The difference between the Loxodromic and Geodesic/Great Elliptic measurements is so great that it definitely can cause confusion about map projection measurements and possibly even uncertainty about the actual distance separating Washington, D.C. and Kabul.  

Because of these potential pitfalls, users must be especially when choosing and reading world maps.  Both map makers and users should be aware of the projection type, preserved properties, and contorted properties in order to read the map correctly.  Only being informed of the variety and staying alert to potential challenges, can we most effectively and truthfully convey and understand geographic information on map projections.  Once these pitfalls are understood and users cautioned, however, the range of available map projections can be utilized to most accurately and easily express geography. 

Week 4-6 Lab

ArcGIS has both many advantages and disadvantages. Its huge capacity and attention to detail make it incredibly applicable and useful, but this same complexity can limit its audience.  Regardless of these pitfalls though, ArcGIS’s storage capacity and the number of different things its users can look of and express with the software is amazing.  I was in awe of how much data and different types of data are available through the software, and as I worked through the tutorial I was excited and a little intimidated about using the software for a variety of applications. 

In addition to providing so much information, ArcGIS lets that information be presented in a clear and professional way.  The editor tool bar and ability to set colors and positions in every map, graph, and poster let the data appear clean and easy to read.  By editing and organizing the information, ArcGIS presentations can be accessible and understandable to individuals of varying knowledge and experience who can benefit the information.

Although ArcGIS is incredibly useful and informative; in some cases it can only benefit a certain group of people.  Both creating and reading ArcGIS maps and all of the information stored in the entities’ attributes require a significant level of computer literacy.  Individuals without high computer skills cannot take full advantage of ArcGIS’s expansive and intricate information and capabilities.  ArcGIS probably needs to be computer intensive to be able to do everything it does, but even so, it excludes a group of people who could potentially have high geospatial or social knowledge and insight that could greatly benefit society when applied to GIS technology. 

ArcGIS software is incredibly expensive and constantly being updated.  The high cost of the software further excludes individuals who may have useful geographic knowledge and/or computer skills but are unable to afford ArcGIS.  ArcGIS’s price in combination with its prevalence in the GIS field to some extent make GIS an elite field, requiring individuals to have experience with the expensive program and companies to buy the software.  The fact that ArcGIS constantly releases new versions requires that individuals and companies must continue purchasing and learning to use the software.