I've updated my Linux system to Karmic Koala over the weekend. It seems to work quite well. For the first time, I decided to kill all the binaries that somehow made it to my machine over a course of 2 years and do a fresh binaries install, keeping my home mount with data. That worked out well and the machine even booted my RAID-0 array with dmraid without any problems this time. Ubuntu 9.10 works like a treat, you should try it!
Getting down to business, if you want to find out how Google / TeleAtlas renders maps, here's a page that gives you an idea how the process works. A mapserver is basically an image server with a HUGE, HUGE, HUGE number of tiles behind it. Each zoomlevel maintains its own set of images basically, so that's why adding a zoomlevel to a finer-grained level will be costly space-wise. The tiles are constructed by adding GIS information of different types together from a rather large database. The tutorial that I found here is very easy to follow and the most comprehensive on the subject.
In this tutorial, they end up building a little world map, which I attempted and worked out, as you can see. The world map on the right was constructed by the information of SHAPE files on my server. The overview is a very generic image, but the information in the SHAPE file is so great, that I can zoom in to great extents and produce the complete coastline of Antarctica or any country in Europe. Thanks to the efforts of the Openstreetmaps project that is and people and organizations that collaborate with them. Notice also how the world seems to appear slightly distorted. I think this is related to the chosen projection method.
Well, once that is working, you can load your own spatial data in postgis and postgres and start drawing specific parts of your interest on detailed images. Instead of writing your own programs to do that, just use the utilities and scripts of the mapnik project. An example of that is here, central Amsterdam:
So this is great. I can now produce very detailed streetmaps of any region in Holland, reason about those places and ways through a database with spatial reasoning predicates, find out extents of regions, and so forth. Mapnik also provides scripts to generate tiles from a given 'planet' database. Tiling a country however can produce a very large amount of data on your PC, so use with care :). The above image was produced using standard styling rules. It is possible to adjust this styling or replace it entirely, such that it becomes more personal. These generated images, together with a bit of JavaScript and the original PostGis database as a backup to the locations of points of interest are at the core of Google Maps.
Well, another interesting application of GIS information is by super-imposing data from different sources over the data in the database, or not rendering specific sets of data from the source in the database so that they have less information, making it easier to focus on the important bits. You can see how Bjørn Sandvik made a thematic mapper for Google Earth by generating KML from thematic data merged with (simplified versions of) world boundaries. Although KML takes some time to render, especially when in 3D (he wrote a nice, detailed paper about the techniques though), you can generate 2D images by loading your thematic data in PostGis first, then relating your data rows with the geographical data. Using a clever query and the pgsql2shp tool, it should be possible to output a file with the attributes you require for rendering. The last step is then to spit out an XML rendering file for mapnik, which basically filters your attributes, assigns colors or other styling measures and then run it through the mapnik renderer.
There's lots of things one can do here. Be reminded that dealing with these tools can be a bit daunting at first. There's generally no need to write complicated mergers/processors, because you can use PostGis as an intermediate data store, which can output .shp files (the most portable format I reckon), which other tools can visualize or process further.
New tool in town: KnowledgeGenes.com
15 years ago
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