Making the imagery accessible

So in the time that we've been offline we've increased our stable to include ArduCopter and ArduPlane, and climbed the learning curve on the minutiae of MikroKopter to the point where we have it flying autonomously to take high resolution canopy mosaics and generating DEMs of canopy surfaces.  All very cool.

But this generates enormous amounts of data, and we have to be able to process it  and display it efficiently. Not only in ways that are good for us in terms of the science goals, but also in ways that people can use on the web.

So how to do it?

One of the ways that we are all familiar with that uses tremendous images in a friendly way is through Google Maps and Google Earth.  And the Google Map API can be used to serve and navigate our own images.  Let's take a large mosaic--in this case a section of Long Caye in Belize--and
cut it into Google Map friendly tiles using a variety of programs.  The easiest way might be found at Digital Insipration using the code there and the Google Map Tile Cutter.  The Bartlett Centre for Advanced Spatial Analysis has a couple of programs for tiling large images (GMap Image Cutter) and a neat interface for generating GMaps from data, the GMap Creator.  GDAL has scripting tools to do this (GDAL2TILES) and the MapTiler (www.maptiler.com) that looks like an interesting way to work this too.  When I get to a decent connection I'll tile a large image and see how it navigates, but it looks to be the ticket.

Now, how do we actually process these brutally complex point clouds?  The next post is on Big Deac, the 3D rendering machine that we have in the works.