In his Washington Post article, Christopher Ingraham explains that the USDA relies on their natural amenities index for attractiveness ratings rather than social and economic values due to their natural state (Ingraham, 2015B). He mentions how California and Colorado have higher rankings for their counties while counties around Minnesota and North Dakota are the “worst” places to live (Ingraham, 2015B). Looking at Oregon, it’s shown that although winters aren’t the warmest and there is only some winter sun and water area, the state ranks very high for temperate summers, low summer humidity, and topographic variation (Ingraham, 2015B).

While providing maps showing the individual measures, Ingraham does point out the flaws in these rankings, such as Death Valley ranking so high when it’s uninhabitable for humans while Iowa’s Loess Hills region ranks lower than counties in Arizona (Ingraham, 2015B). He also mentions the strong relationship found between population concentration and the natural amenities index rankings (Ingraham, 2015B).

His second article reviewed displays the average amount of sunlight each state received over a period of time and also monthly. As mentioned, 2015 was peak daylight for the United States, meaning we should see shorter days ahead (Ingraham, 2015A). It isn’t surprising to see southern states have more sunlight each day, as more states in the Northeast and Pacific Northwest have much shorter days. For Oregon, the state’s counties have a wide variety of sunlight across time, along with their monthly measures. Their daily sunlight is of the lowest in the winter months but of the highest in the summer months (Ingraham, 2015A).

The data used is provided by the US Department of Agriculture Economic Research Service. The first data set records the Natural Amenities Scale for all US counties, a measure that ranks counties higher for warmer winters, more winter sun, lower summer humidity, temperate summers, more topography variation, and water area nearby (“Documentation”). This is because people are usually attracted to these features, so they would rank them higher on a scale. The second data set used (provided by the same source) is a record of four different macroeconomic variables for each county in the US: poverty rate for children under 18, poverty rate for all residents, median household income, and unemployment rate.

The first visualization evaluates the amenity score between counties in my selected state, Oregon. The variables here are each county in the state, which was taken directly from the data set, their amenity score, which has been explained previously, and the summer and winter average temperatures that are included in the tooltip, which are also statistics taken from the dataset. Oregon is a very beautiful place to live with a lot of highly ranked amenities. Every county is ranked above the national median (shown in Visualization 2). Douglas County has the highest score of 6.78, while Grant County has the lowest score for the state of 0.44. Looking at the criteria used for the natural amenity score, the difference could be from their proximity to water. Douglas County is partially coastal, while Grant County is landlocked. Also, in reference to the article’s map, Douglas County seems to have warmer winters than Grant County as well (Ingraham, 2015B).

The second visualization compares the counties’ amenity scores to a macroeconomic variable, unemployment rate, by using a scatterplot. Unemployment rate is calculated by dividing the number of unemployed people in the area by the labor force population in the area, and then multiplying by one hundred to get a percentage. The amenity score is on the y-axis while the unemployment rate (a percentage) is on the x-axis. In addition to these two variables, the color of each point on the chart corresponds to the ruralness of the county. The grey counties are more metropolitan while the teal counties more rural. Lastly, the size of each point is related to the labor force population, the last variable included in this visualization. As shown, there is a slight positive relationship between the variables on each axis. Interestingly, we do see that the more metropolitan counties have a lower unemployment rate and larger labor force population, while rural counties show the opposite. Douglas County and Grant County are also annotated here, and we see that Grant County is a lot more rural and has a higher unemployment rate than Douglas County. 

The third visualization uses the same legend from Visualization 1 to display how each state’s natural amenity scores vary. The variables recorded are each state, their score, and then again, the summer and winter average temperatures for each state. Since every state cannot possibly be above the amenity score’s national median, unlike counties in Oregon, we now see a larger color variance on this map. As discussed, states along the west coast (such as Oregon) and in the south have much higher amenity scores than states in the Midwest and north.

Earlier in class, we’ve talked about use values when valuing the environment. Use value means the asset is used directly, such as fish from the sea or scenic views. In the natural amenity score, the measures used relate to what people are attracted to because they want to experience its benefits. In this case, the score is creating a scale from how each county matches the use values preferred by the population. We also talked about how wind turbines disrupt scenic views. This disruption could possibly hurt counties’ valuation if the population is less attracted to areas with wind turbines present.

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References

Atlas of Rural and Small-Town America Selected Variables. [Data set]. United States Department of Agriculture Economic Research Service.

Hex Map Plot Coordinates. [Data set]. Taylor, Kevin (2017).

A. Ingraham, C. (2015, July 13). Map: Where America's sunniest and least-sunny places are. Retrieved March 18, 2020, from https://www.washingtonpost.com/news/wonk/wp/2015/07/13/map-where-americas-sunniest-and-least-sunny-places-are/

B. Ingraham, C. (2015, August 17). Every county in America, ranked by scenery and climate. Retrieved March 18, 2020, from https://www.washingtonpost.com/news/wonk/wp/2015/08/17/every-county-in-america-ranked-by-natural-beauty/

Natural Amenities Scale - Documentation. (2019, August 20). Retrieved March 18, 2020, from https://www.ers.usda.gov/data-products/natural-amenities-scale/documentation/

Picture of Crater Lake National Park, Oregon. Retrieved March 18, 2020, from https://www.travel-experience-live.com/7-crater-lake-national-park-attractions/

Natural Amenities Scale (including the 6 components) for U.S. Counties. [Data set]. United States Department of Agriculture Economic Research Service.