Ummmm….pancakes It all started with delicious pancakes and a glorified misconception. In a 2003 article published in the Annals of Improbable Research (AIR), researchers claimed to scientifically prove that . The experiment compared the variation in surface elevation obtained from a laser scan of an IHOP pancake and an elevation transect across the State of Kansas. And while the researchers’ conclusion is technically correct, it is based on two logical fallacies. First, the scale the analysis shrunk the 400 mile-long Kansas elevation transect down to the 18 cm width of the pancake, thereby significantly reducing the variability of the elevation data. Second, pancakes have edges, which creates some significant relief relative to the size of the pancake, approximately 70 miles (!) of elevation if applied to Kansas scale (). Using this approach, there is no place on earth that is not flatter than a pancake. Now, I can take a joke, and at the time thought the article was clever and funny.And while I still think it was clever, it began to bother me that the erroneous and persistent view that Kansas is flat, and therefore boring, would have negative economic consequences for the state. I grew up on the High Plains of southwestern Kansas, where there are broad stretches of very flat uplands. But even within the High Plains region there are areas with enough relief to certainly not be considered flat as a pancake…and this doesn’t include the other two-thirds of the state. Official Physiographic Regions for the State of Kansas. Note the large number of regions denoted by “hills.” The joke of it is that the official describes the majority of the state in terms of hills: Flint Hills, Red Hills, Smoky Hills, Chautauqua Hills, Osage Cuestas (Spanish for “hills”). Not to mention the very hilly Glaciated Region of northeastern Kansas, anyone who attended classes on can confirm that for you. And after travelling through other areas of the country, I realized that Kansas isn’tclassification. The data processing for this project was massive, requiring downloading all the individual tiles of the SRTM for the Lower 48 (55 tiles, over 4GB in total size), importing (r.in.gdal), mosaicing (r.patch), setting regions (g.region), then ultimately subsetting into four sections because of a bug in r.horizon (r.mapcalc conditional statements), running r.horizon 16 times on every raster cell in the Lower 48 (1,164,081,047 cells), running the cut point reclassification (r.recode), then compiling the final index score (r.mapcalc). Each segment of the DEM took about 36 hours to process in r.horizon, meaning the entire Lower 48 took about 6 days total. In the final step, each of the 16 individual azimuth scores were added together (r.mapcalc) to create a single index score ranging from 0-16 (0 being non-flat in all directions, 16 being flat in all directions). This index score was divided into four groupings, with Not Flat (0-4), Flat (5-8), Flatter (9-12), Flattest (13-16)categories. Zonal statistics (r.statistics) for each state were extracted from the final flat index, also known as the “Flat Map”, to calculate the rankings for flattest state. A water bodies data layer was used as a mask in the zonal statistics (r.mask) so as to eliminate the impact of flat surface water elevations (reservoirs and lakes) from the final calculation. A second mask was also used to eliminate the influence of two areas of bad data located in the southeastern U.S., mainly in Florida and South Carolina. Both total number of flat pixels and percent area flat pixels were calculated and ranked for the flat, flatter, and flattest categories. See the article below for a table of results. Results Below are a series of maps that display the final Flat Index. The spatial distribution of flat areas is intriguing, with some confirmations and surprises to our initial hypotheses. Interesting areas include the Piedmont and coastal plains of the eastern coastal states, Florida and thecoastal areas of the Gulf States, the Red River Valley in Minnesota and North Dakota, the glacial outwash in Illinois and Indiana, the Lower Mississippi River valley, the High Plains region of the Great Plains, the Basin and Range country of the Intermontain West, and the Central Valley of California. A complete table of the state rankings is available in the article, and there are several more zoomed in maps available below. Each image is clickable and will open a much larger version. Map shows the Flat Index, a.k.a the “Flat Map”, for the Lower 48 of the United States. Map displays the Flatter and Flattest Categories of the Flat Index. Useful for visualizing the patterns of flat lands within the continental United States. Map displays the Flattest Category of the Flat Index. These are the areas that can be called “flat as a pancake.” Rank order of States by the percentage of their area in the Flattest class. As initially thought, Kansas isn’t even close to the flattest. Media Themedia response to what Jerry Dobson, my coauthor and PhD advisor, and I refer to as the “Flat Map” took me by surprise. Jerry was always confident it would be well received, but the range of international, national, and regional coverage it received was beyond anything I imagined. Articles about the Flat Map were written in , , , , , , , , , , , and one of my favorites (just for the headline of the forum post) the . And just recently, Jerry sent along this little gem from the 2015 Kansas Official Travel Guide…that’s right, the Flat Map made the Tourism Guide. In the very chippy , the AIR editors indicate they got a call from the Kansas Director of Tourism. I’ll take this. Does the perception of flatness impact tourism? Seems the State of Kansas is interested in projecting that the Kansas landscape has hills. More Maps Map shows the Flat Index for the Lower 48 of the United States overlaid with the boundaries of the USGS Physiographic regions. Interesting correlation between flat areasand physiographic boundaries. Map displays the Flat Index over Florida, note large areas of flat land in southern half of the state and along the panhandle coast. Map shows the Flat Index over Louisiana and the Lower Mississippi Valley. Large areas of flat lands occur within the river valley and along the coastal areas. Map shows the Flat Index over Illinois and Indiana. Note the huge area of Illinois within the Flattest class, the result of glacial outwash geomorphic processes. Map shows the Flat Index over northern Texas and Oklahoma. Note large tracts of flat land in the western High Plains region. Map shows the Flat Index over Kansas. Note large areas of flat land in the western High Plains region and in the central area of the state corresponding to the Arkansas River valley and McPherson-Wellington Lowlands physiographic province. Thanks I would like to thank Dr. Jerry Dobson for his efforts on this paper. We worked together conceptualizing “flat” and how to build a novel,terrain-based, and repeatable method for measuring it. It was a long road to get the Flat Map out to the world, and Jerry was a constant source of inspiration and determination to get it published. When I was swamped with work at the State Department, Jerry pushed forward on the write up and talking with the media. Future In terms of the future, there is much more that can be done here. New distributed raster processing tools ( and ) could rapidly increase processing speeds, and provide an opportunity for using a more refined, multi-scalar approach to flatness. New global elevation datasets are also becoming available, and could potentially reduce the error of the analysis through lower margins of error in forested areas. If I was to do it again, the USGS National Elevation Datasets, particularly at the 30 meter and even 10 meter resolution, would be a great option for the United States. On the perception front, the terrain analysis results could be compared with landcover data todetermine how landcover affects perception. Social media polling could also gather a huge amount of place-based data on “Is your location flat?” and “Is your location boring?”. I would also like to get the data hosted on web mapping server somewhere, so people could interact with it directly. A tiled map service and the new viewer would be a great tool for exploring the data. If anyone is interested in working together, let me know. Article Below is a pre-publication version of the article submitted to Geographical Review. Please cite the published version for any academic works. 1268173 {84X6FRAF};{TBW3UCEC} apa author ASC no 3065
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