We live in a world where technology is constantly advancing. One of them being the ability to digitize actual maps for others to see them. There are plenty of programs that allow you to do this, but a few of them are: Palladio, Google Fusion Tables, and CartoDB.
For this posting, we were required to create 2 maps, with either of the three programs; I decided to use Palladio for both, considering that I am not too comfortable with CartoDB or Google Fusion Tables.
For this mapping, I appointed everything to the “geocoordinates” of the Cushman data we were given. I edited things like: Terrain, Streets, Land, and Building/Areas. Throughout working with the different settings and options for the map, I was able to come up with the image above. Palladio seems to be a great tool for the customization of the map, as far as color choices work.
For this mapping, I also used: Terrain, Streets, Land, Building/Areas, but I also experimented with the Satellite options, as well as adding in another “streets” layer. Palladio turned out to be a great tool for these specific uses. It gave a real good depiction of every place in which the pictures in the Cushman Collection were taken.
Palladio Compared to Google Fusion:
This mapping was done in Google Fusion Tables, and has the majority of the points placed around the Bay Area, but a few were also up in the foothills. Believe it or not, this is the SAME exact data input that was used in Palladio (The Cushman Data). I’m not too sure as to why the actual placement of the points are different (Maybe this could be a great discussion topic for in-class). Palladio definitely beats Google Fusion in the cosmetic category, but in terms of actual data goes, Google Fusion is able to give a better depiction of it.
Relation to Patricia Seed’s Article:
In Patricia Seed’s article, “A Map Is Not a Picture,” we learned that maps all have a distinct meaning behind them; we just have to find out what it is. Essentially, a map really isn’t a picture, its a form of data. Maps can really show you many things; for example, look at the Cushman data. Without creation of the Palladio map, it would have just been data, but with the inclusion of it, we are able to see where each photo was taken, giving us more insight into the matter, not just strictly numbers or data.