-
Notifications
You must be signed in to change notification settings - Fork 7
Open source workflow in R for spatial data and analysis #29
Comments
I'd be interested in this discussion. |
This went on CRAN yesterday: http://cran.r-project.org/web/packages/rgrass7/index.html |
@jafflerbach Good idea, i'm interested. In addition, I've been working on some geo utilities pkgs recently (geojsonio, lawn, wellknown, proj, http://ropensci.org/packages/#geospatial), so I'd be interested to hear what I can do with those to support use cases you have. |
@jafflerbach I'd be very interested in this session. On Wed, Mar 11, 2015 at 1:12 PM, Scott Chamberlain <notifications@github.com
|
I'm interested in learning more too, since we're publishing lots of geospatial data (https://github.com/ekansa/open-context-py and http://opencontext.dainst.org/). It would be very useful to know what people need to do analyses with confidence. |
I'm in too. |
I will follow along from afar. The raster s in leaflet is a great idea!
|
i'm in, thanks @jafflerbach |
ready whenever |
congregating in the back of the room now for those interested |
I am really interested in the results of this conversation. If there are any notes taken, I would love to see them after the fact. |
+1 |
here is the geo processing engine I was describing: https://github.com/USGS-CIDA/geo-data-portal |
Joe had some cool stuff w/ shiny+leaflet+raster+geojson |
Example for rstudio/leaflet raster branch: https://gist.github.com/jcheng5/a1c48a18d0ea3623c0e6 |
Thanks for the links @jread-usgs and @jcheng5
|
@jafflerbach @jcheng5 where is this at now? I assume the thing to follow is https://github.com/jcheng5/rasterfaster ? |
Yes. I'm just now turning my attention back to leaflet after focusing on a different project the last few weeks. |
Great, thanks! |
What are the best workflows and packages for spatial data and analyses?
We do a lot of geospatial processing in the Ocean Health Index (see Issue #28), and we would like to streamline our workflow and to ensure all our analysis is done on open source platforms, ideally R. We currently do some spatial analyses in R using packages such as raster, sp, maps, rgdal, and more, but we still rely heavily on Python and ArcGIS because of limitations we have encountered in R (e.g., dealing with large shapefiles, etc.).
If this is a problem others encounter often enough, it would be great to develop an effort to do/discuss/improve either or all of the following:
into the working memory, similar to the way that the raster package deals with raster files?
If this gains interest I'm happy to have this topic take a form that's most conducive to the community
The text was updated successfully, but these errors were encountered: