In my previous post, I described how I used a Python script to scrape power outage information from a local web site and convert it into an RSS feed. In this post, I’ll show how I used GeoCommons to visualize the changing information over time.
The process starts by creating a data set in GeoCommmons based on a URL link to the feed created in the previous post. The general process for doing that can be found here in the GeoCommons documentation.
It has been a truism for some time that GIS enables us to build models of the Earth. Esri Press has even offered a book on geodatabase design called “Modeling Our World” for a while. Traditionally, GIS has given us the ability to model the surface of the earth (in a broad sense), including our effect upon it. That can be extended to subsurface modeling and weather modeling and similar concepts but, in general, GIS has focused on the surface of the earth, plus or minus a few thousand meters or so. Continue reading
Ryan Sarver announced today the availability of a geolocation API for Twitter. It even supports GeoRSS and GeoJSON. This could be a potentially significant new step for Twitter. It looks like the API will be opened to
platform developers first everyone (see here).
Tying in location to the near-real-time nature of the Twitter timeline opens up lots of potential location-based applications. Let the slippy-mapping commence!
This will be my last post for a couple of weeks. I’m heading out to Florida tomorrow to spend time with my family and the Mouse. But before I head out, I thought I’d share a little something I’ve been working on.
I’ve been playing the last few days with the InMemoryWorkspaceFactory class in ArcObjects. I am looking at using it for a project I will be working on when I get back so I thought I’d do a little prototyping beforehand.
The fact that it works in memory is very attractive, especially for using volatile data. GeoRSS seemed like a natural source to use for prototyping.