For folks who need precision in location-based targeting in workings, I have found What3Words to be very helpful.
TL;DR: Some cartographers and coders took satellite images of the surface of the world, gridded them into 3 meter by 3 meter squares, and gave each square a unique three-word name. Then, they made an app.
You can tell the app your address, or a set of GPS coordinates, and it will show you the grid overlay, and you can browse the squares and see their three-word names.
Or you can do lookups the other way; put in a three-word name and get back a pin on a map showing exactly where that is. For example, I’ve always wanted to visit workbook.remote.galloping.
It’s super useful for problems of delivering mail to places without streets let alone street names. Or showing someone what door on what wall they should use to get into your building. Or advertising where the rave will be on social media without triggering address scraper bots.
But it’s also useful for handling problems of remote magic involving locations, because it lets you denote linguistically in a spoken work where things should happen. Where exactly you want to draw the perimeter of a ward, for example. And the 3×3 meter resolution means you can discriminate between nearby areas cleanly. Say for focusing on one area of a large garden bed and not affecting its neighboring plants.
It is inconvenient in several ways, though. One is that the grid is X,Y only; no Z. It doesn’t differentiate vertically at all. That is, it would have the same three-word identifier for apartment 118, 218, and 818 in an apartment building, because they all occupy the same 3×3 square on the ground. So if you need vertical precision in your work, you need to specify that in other ways.
Another problem is that there isn’t much power behind the naming – the strings of names are somewhat meaningless (on purpose), and unlike postal addresses the name of any given square has nothing to do with the names of its adjacent squares (again, they did this on purpose), which means the three words don’t tell you anything about that square’s location relative to it’s neighbors, or to world landmarks. For example, foam.apple.proud is right next to guest.pest.senses but you would have no way of knowing that from their names. Nor would you have any way of knowing that both of them are in Times Square, which brings up another problem: there’s not a large egregor supported by this program. Many folks can picture “Times Square” easily but don’t have a shared collective experience of foam.apple.proud. But as the developers say, “The what3words system is fixed and will never change. So a 3 word address today will still be the same in 10 years’ time.” which means it should grow in utility over time, not diminish.
Regardless of these problems, I still find the grid to be useful in improving the effectiveness of location-based work, and maybe you will too. Happy mapping!
Yes And Further 