Mapping Census Year 2000

The point of this assignment was to use our skills in ArcGIS in order to map the US Census in the year 2000. When looking at data that was essentially collected by counting, there are many ways to organize it and reflect it. Looking at the first map above, we can see that this map shows the number of people in the year 2000 by counties in the US. In order to map this data and make this first map as well the following two maps, it was essential to join our census data to the counties data. Specifically to this map, it is clear that the darker purple areas represent the most populated counties while the lighter blue areas represent the least populated counties. Using a gradient color ramp in the legend is very visually effective because anyone can simply glance at the map and notice the counties or regions in the US where most people reside. For example, one can look at Alaska and Hawaii and notice that almost no county in Alaska contains more people than any county in Hawaii. Furthermore, the intervals used in the legend are also effective because it neatly categorizes the data and allows us to only use a few colors in the color ramp. That way, no two colors are alike and it is easier to make distinctions.

This next map above reflects the difference in number of people from the census 2000 and the previous census of 1990 by county. Joining our census data to the counties data was also necessary for this map and while this map looks a bit more complicated (mainly because of the title), the data is easy to explain. The difference in the number of people between 1990 and the year 2000 is simply calculated by subtracting the number of people in each county in the year 1990 from the number of people in the corresponding county in the year 2000. Population gain is exhibited if the difference is positive while a negative difference reflects a loss. Once again, the color ramp is very efficient in this map because it makes it easy to see which counties grew in population in that 10-year time period. Clearly, the dark green shows a larger population increase while the bright pink shows a larger population loss. While the color ramp looks a bit odd because it is not necessarily a gradient, it is still very useful because clearly the green shows population increase while the pink shows population loss. Hence, it is very easy to tell at first glance which counties and/or regions had greater population increase as well as which had greater population loss. Taking Hawaii and Alaska again, one can easily see that some counties in Alaska exhibit population loss and most of the counties  that did gain in population did not gain as much any county in Hawaii. Moreover, the intervals used in the legend are once again useful at effectively separating the data.

This third map above shows the percent change from 1990 to 2000 in the total population per county. This map is a bit different from the previous two because the data is in terms of percentages as opposed to whole numbers. The data in this map is also simple to explain. The percent change in the total population per county is calculated by subtracting the total population in each county in the year 2000 by the total population in the corresponding county in the year 1990 and then dividing the difference by the total population per county in the year 2000. Of course, we then multiple each result by 100 to get our percent change. One may initially think that this map is very similar looking from the previous map when printing in black and white. However, this map does not just reflect population gain and loss per county. This map shows us the relationship between the population gain or loss per county and the total population per county. In a way, it tells us which of the two pieces of data dominates the ratio. Once again the color ramp is very useful because it shows which counties exhibited a large percent increase in population as well as which counties exhibited a large percent decrease in population. Looking at Hawaii and Alaska once more, we notice that the counties that have a net loss in population in Alaska also have a percent decrease in population. Meanwhile, in Hawaii some counties that exhibited the same or similar population gain have entirely different population percent increases. The ratio interval used in the legend is useful in this case because it neatly categorizes the percent changes.

This final map shows the population density for every county in the US according to the 2000 census. This map did not only require us to join our census data to the counties data but also to use the field calculator in order to compute the different densities. However, the calculations, while automatically done when inputting the formula, are quite simple. The densities are calculated by dividing the total population per county in the year 2000 by the total area (in square miles) of the corresponding county. Therefore, this map shows us how heavily populated counties are with respect to their areas. The gradient color ramp used for the legend in this map is reminiscent of the legend for the first map we observed. Since there are no negative values, it is not necessary to have contrasting colors in the legend. Furthermore, the gradient color ramp is effective because it makes it easy to notice which counties have a large population compared to their areas and which counties have more "openness and space." Taking our example of Alaska and Hawaii one last time, we can see that Hawaii is mostly made up of counties that are dense while Alaska is mostly made up of counties that are less dense. A map of population density such as this one can be useful for emergencies because it tells us that the darker navy blue areas are more difficult to evacuate due to how heavily populated the area is.

Overall, it is interesting to see how data such as counting the number of people in the United States can be reflected in maps when joined with other useful information. While the four maps above tell us different things about population, not one is more useful than any other. In fact, one map may be more useful for emergency purposes while another may be more useful for studies. However, this map series as a whole is very interesting especially because the same data source was used for every map. I think that ArcGIS was very easy to use for this assignment.  The tutorial was quite easy to follow and there were minimal complications along the way. This time, I felt that every step I did made sense, but that could be because I am getting more used to ArcGIS. All in all, ArcGIS served as a very useful tool to neatly and effectively create all four maps.