Methodology used for county-level maps of most desirable locations for amenities criticized

UPDATED, Aug. 20: The index has come into question in many counties known for their natural beauties, especially because of the methodology, which penalized counties for having cold, wintry winters and lacking bodies of water and topography variation. Many people from Minnesota, known for its outdoor beauties, were upset that some the state's counties were ranked at or near the bottom. Louisiana counties, also known for beauty, were ranked low, for high humidity and lack of mountains. Most of the Great Lakes and Midwest were ranked fairly low and most of those residents would probably argue that the region's natural beauty can stack up against most any other region. Was your county unfairly ranked low? (Post map)

Where are the most desirable counties to live? Christopher Ingraham of The Washington Post has taken a federal government measure, the "natural amenities index," to create a county-level interactive map that reveals the most desirable counties to live in based on scenery and climate. "The index combines 'six measures of climate, topography and water area that reflect environmental qualities most people prefer,'" Ingraham writes. "Those qualities, according to the USDA, include mild, sunny winters, temperate summers, low humidity, topographic variation and access to a body of water."  

The top 10 ranked counties are all in California, Ingraham writes. "By contrast the Great Lakes region fares poorly, with most of the lowest rankings clustered around the Minnesota/North Dakota border region," with Red Lake County, Minnesota, ranking dead last, mostly because it's the only landlocked county in the country surrounded by just two neighboring counties. Hawaii and Alaska were not considered for the rankings.

"The USDA's original report on the natural amenities index found that these measures 'drive rural population change,'" Ingraham writes. "The USDA found that rural areas with a lot of natural amenities saw the greatest population change between 1970 and 1996." The report states: "The relationship is quite strong. Counties with extremely low scores on the scale tended to lose population over the 1970-96 period, while counties with extremely high scores tended to double their populations over the period."