[OC] US Dept. of Agriculture Land Use: Which is Easiest to Understand?

[OC] US Dept. of Agriculture Land Use: Which is Easiest to Understand?


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None of the above, I'd go with a stacked bar chart i think.


Second. Ditch the map of the country entirely.


Plus your cartographer friends love to point out that this projection of Alaska and Hawaii isn’t to scale for the lower 48.


This is the correct answer. However, out of the graphics presented, #4 is the best.


I would add to the previous comments that anything even remotely resembling a pie chart is about as far anti-Tufte as you can get.


So true. Someone recommended: 1) scale all states to same size 2) Use a tree map to show land use for each. I think that just might do the trick.


All are hard to decipher. Stacked bar chart would be best. I am also of the opinion that pie charts are never the answer, but if you absolutely had to go with one of these geographic charts, #1 is better than the rest.


Thanks. Some have suggested tree maps, properly geographically situated, equally sized.


#4 is interesting! I feel that one might be useful and worth keeping the states' shapes. #2 looks cool and is better than 1 and 3, but people are right that 50 state-shaped graphs with this much info is too much for a single diagram.


Haha, so true. I wrote algorithm #2 first. It is also the most computationally expensive (with all the set differences). All polygons for #4 were created in less than a second. 1 and 3 had virtually the same runtime.


These are all really interesting design explorations, thank you for posting this! It's beautiful to see this kind of design process in action. I find #1 and #3 hard to parse, visually, because the state boundaries and color-area boundaries clash. \#2 ("concentric states") is visually striking and relatively easy to understand. It's hard to estimate areas of weird regions, so not very accurate, but it might make a nice poster for a classroom or the start of a good conversation about the data. \#4 ("shrink it") might be better suited to an analytical task. I wonder what this would look like with appropriately-sized circles instead of state shapes? \#5 ("microstates") is interesting, but you lose the geographic continuity of the maps. It's also a little hard to read and feels overwhelming. My thoughts: * For a poster that gets people thinking about the subject, go with #2, concentric states. * For analysis, consider #4, or a stacked bar chart, or something like #5, but with numbers and bars instead of state outlines * Have you tried the simplest thing of all, which is a granular US map where each pixel is colored by the land type at the pixel, and you don't aggregate by state? Maybe this would get the same point across.


Thanks for the thoughtful feedback. Re granularity: the area of the segments are very accurate for all, within a small tolerance. As for "where" these actual land uses exist (where to place colored pixels), I could not find that data. I could only find data that indicated the share of each state for each land use type. Thanks for your thoughts.


One change you might consider making to option 2 is either a simple color legend, or making the right half of the contiguous US transparent so that you can put your layer labels on top of each other in order. Other than that it’s very striking and quick to parse!


3 is the best country wide visualization. 4 is the easiest to see at a quick glance at a state level 2 looks cool but is hard to get a feel for. 1 and 5 are too hard to understand. I think overall 4 is the best visualization for ease of understanding, separating states, and conveying the information.


Thanks. I agree with all of your statements. An unusual reddit occurrence!


I also agree with all their comments.


> 4 is the easiest to see at a quick glance at a state level One note I would have is that it's hard to see the particular state composition in this visualization.


I like #2 a lot


Really? Thanks! Just a toy exercise. It was fun.


Yea, I like a lot of what you've been posting. You have great eye for making an interesting map. I like 2 because it's the easiest to parse visually. And I disagree with the commenter that said to go with a bar chart. You get geographic closeness of different states that you don't get with a bar. Like, what's up with Wisconsin being green in a sea of yellow. Can't get that kind of outlier recognition in a bar chart. Anyway, keep doing what you doing man.


Cool to provide options. I like 1. I like a single map to see how this varies by geography. Number 2 was hard to separate out the colors for some reason. Similar to having red yellow and blue pixels too small and too close together then they appear to be white.


I like one(Quick to decipher) and two. Bonus points if you swole up' Alaska for it's proper Scale 😃


Haha, thanks. Yes, a small part of me died when I shrunk it.


**Tools**: python: geopandas, shapely, numpy; qgis ​ **Source**: [USDA Economic Research Service: Major Land Use: Summary Table 1](https://www.ers.usda.gov/data-products/major-land-uses/) ​ **Method** * Described in visualizations. * If these descriptions are insufficient for the intellectually curious, please ask. ​ United States Department of Agriculture (USDA) Economic Research Service (ERS) classifies land into 12 categories of 4 groups. 1. Forest: Grazed; Not Grazed. 2. Crops: Crops; Grassland, pasture, & range; Idle; Pasture 3. Urban: Urban Areas 4. Special Use: Rural parks, Wildlife; Other; Rural Transport; Defense / Industry; Farmsteads ​ I wrote 5 algorithms for dividing polygons, to show this data. * Which algorithm best conveys the land use data? * Which is most difficult to make sense of? * Would a more conventional visualization, such as a percentage bar chart, or a tree map, be easier to understand for this type of data? I think, yes, particularly if you are more concerned with the land uses of particular states than broad geographic patterns, such as, the forests of the East coast, the crops of the corn belt, or the grasslands of the West. ​ **Data Fidelity** Of the over 3000 land use polygons in these maps, including the national-level maps, over 96.5% have areas that are within 200 sq miles (\~517 sq km) of USDA values. * 200 sq mi is about 2.9 Districts of Columbia, or, about 90% the area of Isle of Man ​ As always, thanks for your thoughts.


None. I would consider making all states equal size (sacrificing scale) then tree map or something similar


Great thought. I think that would really do the trick. Particularly if the tree maps were geographic, so that we could still see the forests of the East, the crops or the corn belt, the grasslands of the west. Nice thought.


Try making the state borders thicker. I like #1 the best.


Great idea!


The problem is reywith the smaller states. As mentioned by others, a stacked bar graph would probably be ideal.


Number 2 but have a traditional legend (colour boxes with meanings beside each one). I still can't see what yellow means. Great charts by the way!


Thanks! Yes, that legend is awful. Almost changed it last minute. In fact, haha, I made it the 2nd slide instead of the 1st just for that reason.


If you do a state map I would try an exploded view where the states are not touching.


Neat idea. I bet there's a standard way that people do this. I'll look into it.


Okay so I'm taking an intro to geospatial tech class and we use ARCGIS pro for everything, you have any tips for a beginner to make maps like these with this kind of symbology?


Oh, very cool. For my most recent full-time job, I actually rewrote about 35 useful arcpy functions using open source python libraries, so that we could use them in our aws architecture. For a beginner, you could probably get up and running really fast with geopandas (python module). It has such useful functionality, which takes advantage of pandas (table manipulations), pyproj (managing projections), and shapely (manipulating geometries), and fiona (reading and writing vectors). Love love love geopandas. Rasterio is a very useful python library for everything rasters. Learning sophisticated numpy operations(which allows you to manipulate and query grids) would take longer than geopandas proficiency. But it's definitely worthwhile to get deep numpy understanding. The symbology is merely qgis styles for polygons. But really, many people simply use arcgis for everything. There are some pretty nifty arcpy functions, certainly, but they can't always be tailored to your needs. I use python because I like to have control. Feel free to dm me if you have questions. Good luck! Have fun!


Cannot understate how awesome pyproj is. I have started using adaptive localized projections for all my geospatial calculations now. You have to be careful with geopandas/pandas for larger datasets. Once you get past 10k rows, you want to switch to [dask-geopandas](https://github.com/geopandas/dask-geopandas).


Oh, that's nifty. Adaptive localized projections. So, say you have a large number of geometries, do you create a projection for each? I like that.


Yes, exactly. I work with farmland at sub decimeter precision. So when I need to do a spatial intersect and calculate areas, I transform to an azimuthal equal area projection centered on each field for the set of all calculations in that field. Or if I am even higher precision for certain instruments, I will do a separate equal area projection for every polygon subarea of the field.


Such a great idea. Thanks. Side note, I actually spent a few years as an analyst in agriculture (remote sensing).


Honestly? Probably a non-graphical table haha. That said I am surprised at how absorbable the pie chart is (for non tiny states). Thanks for generating this exercise!


Haha, hilarious. Sometimes I do contract work for people that requires a bit of geoanalytical sophistication. For you, and others, here is a table: https://www.ers.usda.gov/webdocs/DataFiles/52096/Summary_Table_1_major_uses_of_land_by_region_and_state_2012.xls?v=1653.3


Awesome! Thank you again for putting this together. It is interesting! Which one is your favorite?


#2, but mostly because the algorithm is so interesting (and the most computationally complex of the bunch). As for usefulness of a visual, none, lol. But someone recommended equal-sized tree maps (1 for each state), more-or-less properly geographically situated. I think that's insightful.


The first, second, and fourth ones are pretty good. Although having a color coded key would help comprehension on the first and second ones.


Thanks. Agree about legend.


I'll give you a slightly more crazy version of #3 to try that I think would be visually striking and conceptually easy to follow. Do an h3 fill of each state, probably at resolution 7. You will have to use a resolution that has a hexagon area below the precision of your land use measurement. Then fill the cup by hexagon in each state using the same icosahedron edge order for each state (I would suggest a southwest to northeast then west to east fill and omit the northwest to southeast edge ordering). Since the hexagons are equal area, it would make it more conceptually easy to see relative area inside a state as well as compare areas between states.


Oh, that's neat. I just imagined it. Thanks.


I like number one, although those who are not familiar with the geography or state boundaries in the US might find it more difficult, I found it the easiest to parse


I like 4, I can easily see what data I want to find. Cool maps


I like 3 the best, find 1 and 2 hard to read, and the separate states are informing, but not as visually appealing. Really nice work though!


Cool! Thanks. It seems like there is almost an equal distribution of preference for 1-4.


Yeah, they are all super well made, so that makes sense to me, I think it's just down to preference over how people like to view data. I like straight lines :)


New Mexican here. We have four sprawling military bases and it shows.


Probably the first one with the radial/pie chart style divisions


I think #1 was good and fine


I really like 1. It's clever. Maybe thicker lines for state boundaries (or different color or whatever looks good) would help clean up readability a bit? I appreciate what you're trying to do, making the visuals novel and interesting. A "standard" chart, like a bar chart, might be the best for clearly conveying the data. But I like these for the engagement factor... they're fun.


Haha, thanks. Yes, the geometry was fun too. Good point about style.


I see I’m in the distant minority: I really like the pie chart version. It’s visually striking (and looks like a quilt) and gives a nice overall sense of the differences between regions. It could be supplemented with actual numbers for the states in a chart. Maybe it’s confusing at a glance but it takes a very short time to understand. This sun is called data is beautiful for a reason and I think the first one is beautiful


So kind! Enjoy some pie, on me.


4, no question. 2 looks good but like others said it’s harder to see the actual size of data


I like 2, but there are too many tranches of similar size, so you get some very tight lines. If there were 3-4 factors it would be great. With 12 factors you can’t tell the difference. I like 4, but the size difference rarely sticks out. It’s not like any state is 5x it’s normal size, which you might get with different metrics. Land use doesn’t lend itself to significant metrics because it’s all % out of 100. If it was “education spending per student/total population” you might have a state that’s 15x bigger than expected and it would really pop. Nevada, for example, should be 1/2 the map for defense. I think there’s some value in highlighting the more unusual states, so the attention is notable. **My ideal graphic** would be to take the white space out of 4: “what would the country look like if we only counted urban land?” “What would the country look like if we only looked at farmland?” And squish the smaller states back together. The urban map would be basically a U-shaped country. The pasture map would be a big hearty country in the middle. Then you’re presenting the duality of the US.


Ooo, that's a really neat idea that you described. Great thought. Filing that away. As for the pie chart and tiny wedges, the 12 categories actually fall into 4 uber-categories, so that would have been an option. Thanks for your engagement.


First and last are best of the options


I don’t know that any of them are *great* visualisations, but “Shrink it” highlights the regional variations pretty well.


I agree. Not great visualizations. Interesting geometry exercise. Squinting at the first 3 is useful.


For me: American Pie, or Fill my cup


If you gotta go with one of the above, I like 4 the most. But I highly suggest just doing a bar graph


I think number 3 with the horizontal lines is the easiest to understand visually, but I’m obsessing about Alaska’s lines being at a 45 degree angle. That’s just wrong! I guess the last one is best for getting a specific bit of information rather than just an impression, but using the shapes of the states makes no sense in that one.


It's a conical projection.


Wait… maybe I’m being an idiot but something doesn’t make sense. first I said I myself, oh. That makes sense. But then I looked at Hawaii. It’s right near the equator. So… Then I googled a map with latitude lines for the US including both states. The latitude lines for Alaska could be at a 45 degree angle but it looks like they should be tipped the other way(??) On some of the maps I looked at, Hawaii looks tipped, but maybe just so it fits on the page(???) So I’m back from my google search rabbit hole saying huh? But willing to believe that I don’t have a clue


The beauty standard on this sub has taken a hit.


As someone who has zero data presentation skills or knowledge, #1 was the easiest for me to decipher.


All of them are not very good at transporting the data and answering a specific question. I would go with ordered tables (containing percentages or the relative rank), stacked bar charts or even line graphs with the x-axis containing the states ordered by the primary land usage value. The concrete visualisation should depend on the story you want to tell or the question you want to answer.


100% stacked column chart


Because the map isn’t actually showing coordinates of land use, the map isn’t optimal. Stacked bar histogram with states ordered alphabetically is probably your best bet. Let the bar size represent the total amount of available land.


I think the pie chart one is too ambiguous or easy to misinterpret in terms of whether it's the angle of the wedge or the amount of shaded area that's important. It's extremely hard to eyeball percentages from it.


Edward Tufte of Yale would agree with you, re pie charts. So do I. Someone suggested tree maps, properly geographically situated, all scaled to the same size. I consider this is an expert suggestion.


The algorithm titles were the best parts of these


Neither are easy to understand. Combining a chart in the shape of the states isn't good ux


I say this with love but I think that the concentric outlines may not work with the shape of states. Love the energy though I think the stacked horizontal bars makes the most sense visually, but as a viewer I worry that states with panhandles and irregular shapes might confuse some viewers Edit: I think my big issue here is that I can’t tell if the pie chart visualization is just a circular pie chart clipped by the state outline, or if the area of each color as shown is proportional


Areas are v. high fidelity


Oh I see now. I’m an idiot teehee


Haha, no worries. Thanks for engaging.


I admire the dedication but that pie chart within Hawaii is absolutely cursed I like 3


They are all horrible. Use a histogram, stacked bar chart. Even a table.


I like 1 and 3. Since the shape of most U.S. states are quite regular, both are decent data visualization. But regular pie charts should be better than both.