Open alb0 opened 9 years ago
3D printing is an exciting area. I'll be interested to find out what datasets lend themselves well to physical printing. I have background in thinning polygons, smoothing objects, etc. using the VTK libraries (www.vtk.org) which might be of interest to participants.
DEMs lend themselves (somewhat obviously) to 3D printing, as is available for anywhere in Norway: http://www.geek.com/news/terrafab-offers-3d-printed-color-model-of-norways-landscape-shipped-to-your-home-1572139/ - I wonder from an outreach point of view whether other physical models might be helpful? e.g. holding arctic sea ice extent from different years, etc?
Great! I have found smoothing to be particularly challenging. I would be very interested in learning more about VTK libraries...
Here is an example of a model of Greenland I recently made using these data:
http://nsidc.org/data/nsidc-0092
I think sea ice extent from different periods would be a very nice model to make
I have also tried printing CReSIS radar data by mapping the radar returns to a height, but there is again a smoothing/data resolution issue here.
I can post some of the matlab code I have been working on, too, but in the hackathon spirit it would be nicer to make these with free software.
This is SUPER awesome, those 3d models are really neat @alb0 As for the code in terms of posting it, feel free to send a pull request to the Github here, and we can start to record preliminary code associated with this session. I'd be happy to host it, and suggest contributing it under the Apache Software License, version 2 ("ALv2").
I agree with @chrismattmann that these models are beautiful. I particularly like the gradient of color that comes with elevation. Smoothing is a known hard problem, but I can think of a few open source solutions. I'll listen to what you have tried so far, and maybe I'll be able to suggest something (VTK, ITK, Orfeo, QGIS, etc.)
@allenpope I really like the idea of 3D-printed models of sea ice. I'd also be curious to see a 3D model of the Arctic Ocean seafloor, especially given all the controversy over continental shelf extents.
Cool! We can think about the best way to do that - I liked (for example) how the Greenland bed & surface pieces fit together. Maybe there's something there about fitting different pieces together?
From the seafloor perspective - I think Mia Bennett (https://twitter.com/miageografia) might have some geopolitical insights to share there.
@allenpope Psst.. nordurljos is me, Mia :) I just chose a different screenname for once.
Ahahaha. Awesome.
i have added some data and code to a repository in my account called "3d greenland" since i couldn't seem to get pull request to work. more to follow
we can definitely print arctic bathymetry and i think it'd be really cool to overlay geopolitical data... i hadn't thought of that before!
Thanks @alb0 small pull request with the suggested ALv2 license: https://github.com/alb0/3d-greenland/pull/1
I was able to read the Greenland GeoTIFFs using QGIS. Nice datasets!
On Oct 27, 2014, at 9:54 AM, Chris Mattmann notifications@github.com wrote:
Thanks @alb0 small pull request with the suggested ALv2 license: alb0/3d-greenland#1
— Reply to this email directly or view it on GitHub.
Data visualization need not stop at a 2d image, especially since the data themselves are geospatial.
I have been 3D printing various polar datasets, but have met many challenges along the way which may prevent others from embracing 3D printing's potential. These include having to grapple with obtuse architectural modeling software, adjusting the resolution and scale of the data to suit the printer, physical limitations of the printer itself, changing the format of the data to suit that of the printer...
I would like to discuss: How to make 3D printing easy for scientists to use If 3D printing can be used for polar research purposes beyond data visualization. What tools would we need for this to happen? Can we make interesting and accurate models for people to download and print on their own?
Along the similar lines, I think it is possible to create an interesting "installation" of a these datasets using light or sound. This could be very effective and fun to make for data that are not inherently visual.
If there is an interest, there is a lot of potential for creating visualizations that go beyond the computer screen.