New R package: forestdata makes it easy to download forestry and land cover data from multiple sources (Copernicus, ESRI, EU-Trees4F, and more). Supports sf, SpatRaster, and tidy outputs.
Explore it here: https://cidree.github.io/forestdata/
#rspatial
2 posts2 participants0 posts today
Chapter 12: Spatial Statistical Learning 
Boost your spatial models! 
Learn about spatial autocorrelation, cross-validation, and machine learning with `mlr3`, using a real-world landslide prediction case study.
New R package alert: 
mbg for model-based geostatistics
Run spatial ML & geostatistical models to estimate continuous surfaces from point data + raster covariates.
Built on sf, terra, data.table, caret, and R-INLA.
Okay - further to my early rants about CDSE data, it aint as bad as I thought 
it also prompted me to properly sort out my approach to scaling/offsets which had been driving me mad! So if anyone cares for another way to download data from CDSE, with #rspatial / #gdal I made a gist:
https://gist.github.com/h-a-graham/86cd3403445cf163ce958efa2d29c621
There are still some improvements to be made for sure.
FYI @Micha_Silver
A heads-up about the Geocomputation with R book: some copies were mistakenly printed in black & white instead of full color. If you received one, please contact me or the publisher for a replacement. A new, correct copy will be sent to you!
Publisher: https://www.routledge.com/contacts/customer-service
I finally manage to watch @paleolimbot presentation at @RConsortium on "scaling the #Rspatial ecosystem" !
https://www.youtube.com/watch?v=tjNEoIYr_ag
Quick subjective key points:
- Use the database Luke and learn a bit SQL (I was already converted)
- the diversity of R packages to do some workflows also represent the diversity of standards (s.f.) and steps to reach similar results
- wkt_filter seems very nice (I was using "query" and GDAL/SQL instead)
Chapter 10: Bridges to GIS Tools 
Shows how to connect R with external GIS tools like QGIS, GRASS, and SAGA. Also includes guidance on working with GDAL, spatial databases, and cloud-based services.
Registration is open for Spatial Data Science across Languages (SDSL) 2025 – Sept 17–18 (+19), Salzburg, Austria.
Connect R, Python, Julia & more in spatial science.
https://forms.gle/E9fpG88V2VQQKmjk9 -- Apply for on-site by mid-July – limited spots.
From Brittany Barker: ‘My "GIS and Mapping in R" workshop for the Cascadia R Conference . . . is available at GitHub and includes four exercises that focus on using "sf", "terra", "ggplot2", and "leaflet" for geospatial analyses and creating static and interactive maps’
#RStats #RSpatial
(Barker is an asst research professor at Oregon State University in Portland)
https://github.com/bbarker505/CASCADIA_R_Intro_to_GIS_2025
GitHubGitHub - bbarker505/CASCADIA_R_Intro_to_GIS_2025: "GIS and Mapping in R" Workshop materials for 2025 Cascadia R Conf"GIS and Mapping in R" Workshop materials for 2025 Cascadia R Conf - bbarker505/CASCADIA_R_Intro_to_GIS_2025
Replied in thread
@MichaelTBacon @eliocamp here it seems #Rspatial is innocent, #GDAL error is helpful here.
I should start collecting all the ways in which #RSpatial can go wrong spectacularly.
Chapter 8: Geographic Data I/O 
Covers how to read and write spatial data in various formats, access open geoportals, and work with geographic web services in R. Includes tips on metadata and exporting maps.
Hey #RStats / #RSpatial friends, I'm experiencing this weird bug, I've reported it to sf but Edzer can't reproduce. Anyone else seeing the same? Pretty simple steps if you want to try it out and confirm.
https://github.com/r-spatial/sf/issues/2526
GitHubError in .subset2(x, i, exact = exact) after processing data with dplyr for the R session's first time, but not if same dplyr code is run a second time · Issue #2526 · r-spatial/sf
Exciting news! 
The 2nd edition of Geocomputation with R is now available as a physical book! 
Order your copy today and explore the latest in R for spatial analysis.
Learn more about the book's journey: https://buff.ly/3TZzc4L
Chapter 5: Geometry Operations 
Simplify, buffer, transform! Learn to modify vector geometries, clip spatial data, apply affine transformations, and resample rasters for better alignment.
Continued thread
Despite my talk’s quite frankly rubbish title it was still nice being back at Bristol R Users meet-up in person for the first time since 2019. Many thanks to @mhl20 for the inspiration on the postcode voronoi polygons.
Slides here: https://chrisdnewton.github.io/postcodes
chrisdnewton.github.ioFun with Postcodes in R
tmap.mapgl introduces two new modes for the R tmap package: mapbox and maplibre 
Still in development—requires dev versions of tmap and tmap.mapgl.
More info: https://github.com/r-tmap/tmap.mapgl
The "Machine learning of spatial data" section is now live on the CRAN Spatial Task View!
Check it out at https://cran.r-project.org/view=Spatial
Have suggestions or improvements? Contributions are welcome!
Seems @loreabad6 passed away yesterday. Apparently she was hit by a vehicle while riding a bicycle.
Yet another amazing person leaves us at a very young age. RIP.
This finally does what I wanted it to! Christ, this has probably been one of the biggest rabbit holes I've been down but who knows maybe it was worth it this time? Anyway, check it out if you're interested in building satellite image / raster composites with a bit more control and (maybe) some more performance in #rstats #rspatial https://github.com/Permian-Global-Research/vrtility 
GitHubGitHub - Permian-Global-Research/vrtility: An R package to explore GDAL VRT utilitiesAn R package to explore GDAL VRT utilities. Contribute to Permian-Global-Research/vrtility development by creating an account on GitHub.