This week we’ll broach the topic of datums, coordinate systems, and map projections in the GIS class that I teach at Cornell. It’s week 5+ of the semester, just enough into this stuff so that there’s some sustained knowledge growing and they now have enough of a framework onto which to hang the obvious-but-abstract-and-necessary-but-confusing-and-powerful topic. I used to be more GIS-traditional about this stuff and dive in during weeks 2 or 3. Not any more. Much more and deeper learning taking place now that students are more confident and competent at managing and manipulating spatial data. T
Just in time, XKCD has come up with another inspired projections example to share with the class.
I was a total newbie to R before spring 2014. Then it was a little trial by fire, trying to learn just enough to keep up with grad students in a class I was co-teaching. Thank goodness for the “co-” part, as my partner was an expert in the topic, and I could contribute in my own areas of expertise, which were/are not R! But I finished the semester with a new-found respect and, frankly, awe for what is possible with R. I have much to learn, and maybe, someday, the time.
Fast forward a few months and the topic keeps cropping up. I shared a beer in Salzburg with Lex Comber and learned about one of his forthcoming publications, an Intro to R for Spatial Analysis and Mapping. Haven’t got my own copy yet, but if it’s what it seems to be, it’ll be one of my assigned texts in the future. In one of our webinars, Trisalyn Nelson spoke about her use of R with her graduate students. And today, I silently scanned through Alex Singleton‘s recent presentation on the Changed Face of GIS, in which R figures prominently for him. There’s something going on here that some smart people have figured out.
Experimenting with reblogging some worthwhile posts.
Since its inception, Stories of the Susquehanna has been a collaborative, interdisciplinary digital project that has at its core a geospatial interface. What started out as historical/cultural mapping of the Native American landscapes of the Susquehanna in ArcMap Desktop with maps published in static image format (as discussed in the interviews of me and Emily Bitely) has evolved through the iterations of ESRI’s software development.
About a week ago, one of our Digital Scholarship Coordinators and SSV project manager, Diane Jakacki pointed to to the fact that ESRI was now publishing apps. At first skeptical, I proceeded to delve further into the Collector app and battled my way through tutorials designed for insurance adjusters gathering data in the field (no, I don’t need fields labeled “Habitable” or “Partially Destroyed”) to create a feature layer that could be added to any map in ArcMap online. This feature layer was supposed to be…
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There’s a hip trend going around, making simple maps with labeled spaces. At least one or two a week have been crossing my computer screen lately. I’ve always referred to this approach as using maps as organizational templates. In most cases the map-makers don’t go into telling a story about why the data are where they are. They’re just labeling a place with its information, and leaving the rest up to us. The map is serving as a way to represent data by virtue of its geographical location. That is, we start with some data, and that data happens to have a 1-to-1 relationship with some location, like a state in the US, or a country in the world.
We could use a spreadsheet as an organizational template instead. In fact, many of these maps started that way. Start with a spreadsheet with an alphabetical list of all 50 states (plus D.C., which often gets overlooked), and then another column in the spreadsheet has some information about each state (let’s call it an “attribute” of that State). And maybe we know different attributes for different years.
Problem: looking at an Excel spreadsheet is boring. And it’s virtually impossible for us to envision a “pattern” from a spreadsheet. States or countries arranged alphabetically tells us nothing about the geospatial relationships among those places. Did I already mention it’s boring. Our eyes glaze over. Who wants to have glazed eyes?
Instead, by labeling each state – or country – or region – with the attribute, we can appreciate the geographic pattern of said information. When the data are categorical or nominal, you might get a map like what the most popular boy’s name has been in each state over the last 60 years, or the girls’ names, or surnames in Europe, how the Russian language engenders the names of world countries, or what each world country is “best at” (which is a wonderfully subjective way to begin a discussion), with the label being a word or a phrase.
Such data can often be represented pictorially or through icons, like the “most famous book” in each State (again, who gets to decide that?!), or the Food of the States. At least they remembered D.C.!
I don’t know, maybe it’s just me. But I’m seeing these maps all over the place these days.
One small Norwegian town is geographically plagued by its position in a valley, leading to topographically-induced shading during its otherwise already dim winter days. An attempt at a targeted solution? Mirrors strategically placed.
Good luck to them! I love that it combines the best of geographical AND spatial thinking, or spatial thinking in situ. That’s also called geodesign.