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#rspatial

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Jakub Nowosad<p>Chapter 4: Spatial Operations 📌🗺️</p><p>Modify, analyze, and relate spatial data! 📌 Learn how to subset by location, compute distances, merge rasters, and use raster algebra for powerful spatial analysis.</p><p>🔗 <a href="https://r.geocompx.org/spatial-operations" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">r.geocompx.org/spatial-operati</span><span class="invisible">ons</span></a> </p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/geocompx" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>geocompx</span></a></p>
Jakub Nowosad<p>🆕 The "Machine learning of spatial data" section is now live on the CRAN Spatial Task View! 🌍</p><p>Check it out at <a href="https://cran.r-project.org/view=Spatial" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">cran.r-project.org/view=Spatia</span><span class="invisible">l</span></a></p><p>Have suggestions or improvements? Contributions are welcome!💡</p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://fosstodon.org/tags/gischat" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gischat</span></a></p>
Chris Toney<p>R package gdalraster 2.0 released on CRAN. This version adds bindings to the GDAL Vector API along with other new features and improvements.</p><p>Release notes: <a href="https://github.com/USDAForestService/gdalraster/releases/tag/v.2.0.0" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/USDAForestService/g</span><span class="invisible">dalraster/releases/tag/v.2.0.0</span></a></p><p><a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/gdal" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gdal</span></a></p>
Jakub Nowosad<p>Chapter 3: Manipulating Geographic Data 🏗️📊</p><p>Subset, aggregate, join! 📌 Learn to manipulate vector and raster data, create new attributes, and more in R. </p><p>🔗 <a href="https://r.geocompx.org/attr" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">r.geocompx.org/attr</span><span class="invisible"></span></a> </p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/geocompx" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>geocompx</span></a></p>
Raúl Nanclares 🍜<p>Seems <span class="h-card" translate="no"><a href="https://fosstodon.org/@loreabad6" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>loreabad6</span></a></span> passed away yesterday. Apparently she was hit by a vehicle while riding a bicycle.</p><p>Yet another amazing person leaves us at a very young age. RIP.</p><p><a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a></p>
Jakub Nowosad<p>Chapter 2: Geographic Data Models 🗺️📐</p><p>Vector or raster? Points, lines, polygons, or grids? 📌 This chapter covers spatial data structures in R, CRS basics, and how `sf` &amp; `terra` help handle spatial data efficiently! 🛠️</p><p>🔗 <a href="https://r.geocompx.org/spatial-class" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">r.geocompx.org/spatial-class</span><span class="invisible"></span></a> </p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/geocompx" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>geocompx</span></a></p>
Hugh Graham<p>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 <a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://github.com/Permian-Global-Research/vrtility" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/Permian-Global-Rese</span><span class="invisible">arch/vrtility</span></a> ✌️</p>
Jakub Nowosad<p>🔍 Interested in spatial machine learning with R?🌍<br>We compare caret, tidymodels, and mlr3 for spatial tasks — and show how their workflows differ.</p><p>Read it here: <a href="https://geocompx.org/post/2025/sml-bp1/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">geocompx.org/post/2025/sml-bp1</span><span class="invisible">/</span></a> </p><p><a href="https://fosstodon.org/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://fosstodon.org/tags/SpatialAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SpatialAnalysis</span></a> <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a></p>
Lorena Abad<p>As it’s becoming a tradition, this year’s biking to <a href="https://fosstodon.org/tags/EGU25" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>EGU25</span></a> was my longest so far, Salzburg to St. Pölten in two days with 300km and 14 hours on the saddle! Now I’m ready for the first conference day! </p><p>Come by my poster today 10:45 in Hall X2 poster X2.50 to hear about alpine river dynamics tracked with SITS. The whole workflow is powered by <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> </p><p>See you there!</p>
Jakub Nowosad<p>Chapter 1: Introduction to Geocomputation 🌍📊</p><p>What is geocomputation? Why use R for spatial analysis? 📌 This chapter traces its history, connects it to FOSS4G, and explores R’s power for geospatial work. Learn about R-spatial’s evolution! 🚀</p><p>🔗 <a href="https://r.geocompx.org/intro" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">r.geocompx.org/intro</span><span class="invisible"></span></a></p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/geocompx" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>geocompx</span></a></p>
Timothée Giraud<p>New package on CRAN: {valh}, an interface between R and the Valhalla API<br><a href="https://github.com/riatelab/valh" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/riatelab/valh</span><span class="invisible"></span></a></p><p>Valhalla is a routing service based on OpenStreetMap data.<br><a href="https://valhalla.github.io/valhalla" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">valhalla.github.io/valhalla</span><span class="invisible"></span></a></p><p>Co-authored by <span class="h-card" translate="no"><a href="https://fosstodon.org/@mthv" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>mthv</span></a></span> </p><p><a href="https://fosstodon.org/tags/GISChat" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GISChat</span></a> <a href="https://fosstodon.org/tags/RSpatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RSpatial</span></a> <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://fosstodon.org/tags/OpenStreetMap" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenStreetMap</span></a></p>
Hugh Graham<p>On the left is a standard median S2 composite. On the right is a geomedoid (cell with the smallest distance to the geomedian). It aint quick but this is what I've been working towards for a while now so I'm amped. Better compositing coming to vrtility 📦 soon. <a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/gdal" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gdal</span></a></p>
geocaruso<p>Felt the need to provide students with a visual summary of spatial regression models. Effective? Correct?<br><a href="https://mstdn.social/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a></p><p>Grateful for the great resources: <a href="https://r-spatial.org/book/17-Econometrics.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">r-spatial.org/book/17-Economet</span><span class="invisible">rics.html</span></a> and <a href="https://ruettenauer.github.io/Geodata_Spatial_Regression/05_regression-theory.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ruettenauer.github.io/Geodata_</span><span class="invisible">Spatial_Regression/05_regression-theory.html</span></a> </p><p>Interestingly I had to use sf and st_intersection before I could make a "CMY set" type plot and color its different pieces... <br><a href="https://github.com/geocaruso/MAGEO1642/blob/503746252822ab9cf9d04e96e91c0b4f9d4e840c/R/cmyk.R" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/geocaruso/MAGEO1642</span><span class="invisible">/blob/503746252822ab9cf9d04e96e91c0b4f9d4e840c/R/cmyk.R</span></a></p>
Jakub Nowosad<p>🚀 New preprint! "Spatial Data Science Languages: Commonalities and Needs" 🌍 </p><p>Exploring challenges &amp; insights from <a href="https://fosstodon.org/tags/Rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Rstats</span></a> <a href="https://fosstodon.org/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> &amp; <a href="https://fosstodon.org/tags/JuliaLang" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>JuliaLang</span></a> for spatial data handling—geodetic coords, data cubes, and more! </p><p>🔗 Read here: <a href="https://arxiv.org/html/2503.16686v1" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/html/2503.16686v1</span><span class="invisible"></span></a> </p><p><a href="https://fosstodon.org/tags/SpatialDataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SpatialDataScience</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/geopython" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>geopython</span></a> <a href="https://fosstodon.org/tags/juliageo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>juliageo</span></a></p>
Jakub Nowosad<p>Recently, I taught a session on landscape metrics in R—covering how to quantify spatial patterns in landscapes. 🌾📊</p><p>Slides + exercises here:</p><p>🔗 <a href="https://jakubnowosad.com/rgis2025/output/landscape_metrics.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">jakubnowosad.com/rgis2025/outp</span><span class="invisible">ut/landscape_metrics.html</span></a></p><p><a href="https://fosstodon.org/tags/rGIS2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rGIS2025</span></a> <a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/LandscapeMetrics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LandscapeMetrics</span></a> <a href="https://fosstodon.org/tags/GIS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GIS</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a></p>
Hugh Graham<p>{vrtility} gets its first vignette - how to make HLS composites. I think this example really starts to show how awesome the VRT format can be and how much we can do with it! <a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/gdal" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gdal</span></a> <br><a href="https://permian-global-research.github.io/vrtility/articles/HLS.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">permian-global-research.github</span><span class="invisible">.io/vrtility/articles/HLS.html</span></a></p>
Martin Fleischmann<p>"Spatial Data Science Languages: commonalities and needs" - that a preprint 11(!) of us wrote together as one of many outcomes of two workshops held in Münster (2023) and in Prague (2024). It summarised where we are, what we share between R, Python and Julia, what are the common challenges, lessons and recommendations - <a href="https://arxiv.org/abs/2503.16686" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2503.16686</span><span class="invisible"></span></a></p><p>Big thanks belongs especially to <span class="h-card" translate="no"><a href="https://mastodon.social/@edzer" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>edzer</span></a></span> who kickstarted the whole initiative! And to all the others who participated!</p><p><a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/geopython" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>geopython</span></a> <a href="https://fosstodon.org/tags/juliageo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>juliageo</span></a></p>
Jakub Nowosad<p>The bayesEO package provides a Bayesian approach to post-processing ML-generated images. It refines class probabilities, removes outliers, and improves labeling for more accurate classification.</p><p>🔗 <a href="https://github.com/e-sensing/bayesEO/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/e-sensing/bayesEO/</span><span class="invisible"></span></a> </p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://fosstodon.org/tags/RemoteSensing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RemoteSensing</span></a> <a href="https://fosstodon.org/tags/Bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayesian</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a></p>
Hugh Graham<p>WIP pkgdown site now up for {vrtility} <a href="https://permian-global-research.github.io/vrtility/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">permian-global-research.github</span><span class="invisible">.io/vrtility/</span></a><br>Managed to iron out a good few bugs and a bit more parallel stuff so it's starting to come together 😀 <br><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/gdal" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gdal</span></a></p>
Jakub Nowosad<p>🚩 Our poster, "An Inventory of Spatial Machine Learning Packages in R" was presented at <a href="https://fosstodon.org/tags/FOSSGIS2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FOSSGIS2025</span></a> in Münster.🚩 </p><p>It compares caret, mlr3, and tidymodels for spatial ML and highlights other relevant R packages. </p><p>Poster and related materials, including code: <a href="https://loek-rs.github.io/FOSSGIS2025-examples/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">loek-rs.github.io/FOSSGIS2025-</span><span class="invisible">examples/</span></a></p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rspatial</span></a> <a href="https://fosstodon.org/tags/machinelearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machinelearning</span></a> @FOSSGISeV</p>