Zorgloob, alors.

Zorgloob, a French Google blog, has now also started a forum and sightseeing section, with links to both Google Maps and Google Earth, and the ability to leave comments.

Atom 1.0

Ogle Earth now has an Atom 1.0 feed, if you’re so inclined, in addition to the usual suspects.

Vorsprung durch Google-teknik

e-ality, a German blog, busts out with two cool innovations. First, a page that converts International Gliding Commission (IGC) files into KML, so that anyone doing air-sports can now impress their friends with their paragliding escapades in Google Earth (as XAlps paragliding contestants did in an earlier Ogle Earth post).

Second, e-ality’s WordPress-driven blogging engine now features some kind of geodata integration that automatically generates Google Maps and Google Earth links for blog posts. This post says that it’s all a work in progress (translation into French, okay, kidding, English) and we’re not yet given a peek under the hood, but I am all for blog publishing plug-ins that allow us to treat geodata properly. Geodata is the missing link (literally, ha) to the real world, and so often blog posts are about specific locations.

But that’s not all. The German-language version of the IGC converter page links to another site that has KMZ files with translucent extruded polygons denoting all the no-fly zones for air-sports in all of Europe. It looks very impressive in Google Earth.

(More links: A German paragliding thread about IGC and Google Earth; a page that shows IGC files in Google Maps.)

BadHill’s backend

In a follow-up to yesterday’s post about Portland’s bike path plans, Brandon Martin-Anderson explains how his least-hilly bike trip finder works on Seattle’s BadHill:

The backend router works by finding a path which minimizes the total sum of energy expended riding from origin to destination. This is actually relatively simple, as there are well-established algorithms for finding the “least” path between two points in a network, and in my case the “least” that it finds is ‘energy expended on road link’.

Because you theoretically spend the same amount of energy climbing a given altitude no matter what the slope is, BadHill’s routing engine doesn’t really *care* what the slope is, as long as you never have to waste elevation gain. Say you have to travel five miles with 500 feet of elevation gain. BadHill would rather you shoot up those 500 feet in a block with crampons and caribiners if that meant it was totally flat the rest of the way, as alternative to a gentle slope upward which occasionally dips down a little bit.

This is obviously a problem in some circumstances, but it ends up being mathamatically simple and “workable” for the beta. I’ll fix it eventually.

Incidentally I went out riding last night to test out some of BadHill’s recommended routes and discovered that my algorithm needs some tweaking. There was a hill where there shouldn’t have been. It was bad.

If anyone else ever tries to patent this, you’ve got your prior art right here. Not sure whether Portland’s Metro is working on a similar solution and showing the results in Google Earth, or whether they are reying on Google for the backend. I’ll try to find out.

Bike trip planner via Google Earth?

Bike Portland has details of plans by Portland’s Metro transportation planning agency to integrate with Google Earth more deeply than anything else I have seen to date.

Metro’s got all of Portland’s bike paths available for download as KML, but now they’d also like to provide a trip planner for bikes using these paths, just like the trip planner that already exists for cars on roads. This sounds like it would take some work on Google’s end, and it doesn’t seem to be a done deal just yet, but Metro is asking for feedback:

Note: the trip planner is not yet available. Metro is exploring the use of this technology. Tell us what you think.

I wonder if there is a core trip-planning technology Google has that can then be adapted to arbitrary path topologies, or do trip planners for roads come riddled with exceptions to avoid nonsense results? If it’s the former case, then the work of providing a trip planner for bikes might involve little more than properly meshing a path network to a generic trip-planning API, and if that is the case, then perhaps soon anyone will be able to create their own trip planner services. But now we’re purely speculating.

Not that there is anything wrong with that. I wonder, would such a trip planner be sophisticated enough that it can use Google Earth’s altitude data to calculate gradients, and then offer cyclists is San Francisco the least upwardly steep route among its options?

Notes on the political, social and scientific impact of networked digital maps and geospatial imagery, with a special focus on Google Earth.