Heyo mappers!

Last month we promised a MapKnitter 1.0 by the "end of September" and although we're stretching that definition a bit, it's ready now. I submitted the last few changes today and we'd love it if you went in and tried it out: https://mapknitter.org (intro video)

I'm sure there are some small bugs out there, as well as plenty of things we ought to add in the next release, but you can now fairly reliably and easily go "from images to maps".

Some rough statistics: while there are lots of partially completed maps, MapKnitter is already host to 162 completed/exported maps of an average resolution of 26 cm per pixel. The most common resolutions are between 1-4 cm/px. That's somewhere around 10x better than Google Maps!

MapKnitter's 1.0 release was made possible in part by the John S. and James L. Knight Foundation, as part of its Knight News Challenge; it is open source software released under the GPLv3, and the full source is available here: https://github.com/jywarren/mapknitter. To keep in touch about MapKnitter, consider joining the Public Laboratory mailing list.

You can now:

• select an export resolution with a slider (fancy!)
• download a .zip of the OpenLayers and Google Maps web viewer files (the TMS) to carry with you on a USB stick or host on your own site
  
• dim the background reference map to see your own data better
  
• browse recently added maps and maps by author
  
• (experimentally!) run the entire MapKnitter system off a USB stick if you don't have an internet connection, or yours is too slow

For a look at what's upcoming, and to see where you can contribute: https://github.com/jywarren/mapknitter/issues

Finally i want to thank everyone who's contributed ideas, feedback, criticism, documentation, and code, as most of this latest round of features and bugfixes is based explicitly on input from you all!

--Jeff & PLOTS

P.S. if you're interested in helping tackle the next release, some of the big planned features include "layers" which will help composite infrared and visible photos into various vegetation index maps like NDVI or NRG and "masking" of individual images to select the best parts of each. Also on the horizon are edge blending and even a full mesh distort feature for topographically tough areas! Please get in touch at jeff@publiclaboratory.org or on the publiclaboratory or grassrootsmapping mailing lists.