Blog #9 – Peas and Carrots (and Corn)
Third time’s the charm! We are out here with the last rendition of “Beans!”, featuring a lack of beans. I made maps for corn and carrots this week using the same methodology from the last few blogs. I snagged the veg data from the agricultural census, plopped it into QGIS, and brought the shapefile into Arc to make some maps!
Honestly, I wasn’t sure if the ag census would have carrot data, but luckily it did, although Alberta is somewhat lacking in terms of carrot production.
In the table, you can see that almost all the divisions have suppressed data for corn, and some have even reported zeros. Corn, on the other hand, has data reported for most divisions, but with a significantly smaller number of hectares. Despite the suppressed data, I wanted to map all three crop types to see where in the province we are getting the most growth of each type. I used the CDUID column, the same as last time, to join the data to the Alberta census division shapefile and added carrots and corn to the list of maps we have made.
Compared to peas, there is a lot less data available to us. Also note the difference in the defined categories in the legend. Corn goes up to a maximum of 13,207 hectares, whereas carrots only go up to a maximum of 90 hectares. Not to mention that peas go up to a maximum of 44,544 hectares. It’s typical to standardize categories when comparing maps, meaning that all categories have the same minimum and maximum so the maps can be easily compared. However, the difference in the maximums for all three crops makes it impossible to compare them without losing the definitions between the divisions. The carrot map would be pretty boring if we used the legend that we used for peas. Although, it could be said that since the differences between the divisions are so small in the carrot map, that they might as well all be in the same category.
Setting the values for your legend is a complex process that involves understanding your data as well as the message you want to convey. There is a lot of power in creating visuals, because human minds can make very quick decisions based on the information presented.
A good example is the electoral map we all saw way too much of the last few weeks. The sea of red may look decisive, but a new type of visualization tells a different story:
For these vegetable maps, my question is about the differences between the divisions for each crop, not comparing between the types of crop. If I wanted to know which crop was grown the most in Alberta, I would need to use a different legend, and probably a different type of map. Check out this website for more information on defining legends in GIS.
That being said, looking at all three vegetables, it’s pretty clear that peas are the winner here. There are only two divisions with suppressed data, and the sheer number of hectares of peas being grown significantly outweigh corn and carrots combined. This is pretty surprising since corn is a very lucrative crop. In Ontario, the amount of corn grown each year is staggering, it’s one of the main crops produced in the province (see the green section of the figure). Peas are a winner in Alberta though, I wonder why?
When I looked it up, I found that peas are a lucrative crop for Alberta. Peas are used for livestock feed and are probably easier to grow in the prairies than corn is. Southern Ontario has a different climate than Alberta does, which might also explain the difference. The number of peas being grown is probably going to increase because of the market interest in Beyond Meat and other vegan products, because peas are an essential ingredient. This vegetable data is from 2006, so it will be interesting to see how these values change with the addition of the vegan meat market.
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