On the hunt for an article or two to get you through your afternoon or even reading to supplement with that third cup of coffee? No fear. We have you covered. Catch this week's picks for #DailyBrainCandiii posts as well as a quick #MapOfTheDay.
You know those maps circling social media telling you the most commonly searched word in each state or something just as silly? Of course you have. They're fun, they're silly, and they often poke good-humored fun. However, have you ever stopped to consider just how accurate they might be? The story is in the way the data is visualized, but some argue that the data underneath these infographics and maps is not as sound as people think it is in the first place. This article speaks to the trouble of applying maps in funky ways and the unreliability of search engine rankings when context is taken out of the equation.
There are people out there who are entranced by academia, buying overpriced scholarly books to read even if they're no longer anywhere near a university. (Oh, just me, then?) The History of Cartography is a great example of books that would be perfect for the picking. With six total volumes spanning from the 1980s to 2015, this series is a work of reference and scholarly interpretation for those who have are interested in how cartography began and has continuously morphed throughout space and time. Maps help to define the relationships between people and the world around them, and thanks to the University of Chicago you can geo-geek out with PDF downloads of the first three volumes. Consider this our encouragement of a little light reading.
Over the years, we've heard of the various ways in which institutions have sought to apply machine learning. This includes everything from anti-virus software to facial recognition - and now? Prediction of food supply. One start-up is on the path to exploiting satellite imagery to create a real-time forecast of commodity agriculture while analyzing land use and land change simultaneously. It's a fairly interesting application, the basis of which could potentially be applied to other industries who may be interested in commercial or environmental issues rather than crop production.
The title of this article boasts a bold statement. The content, just the same.
Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.
On the hunt for a way to test out ArcGIS Pro, ArcGIS Online customizable apps, an