#geocompx — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #geocompx, aggregated by home.social.
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📢 The geocompx project has a new (and fully reproducible) logo!
geocompx is a community-driven initiative for reproducible geocomputation across languages, building open resources for spatial data analysis, modeling, and visualization in R, Python, Julia, and beyond, all rooted in open-source principles.
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📢 The geocompx project has a new (and fully reproducible) logo!
geocompx is a community-driven initiative for reproducible geocomputation across languages, building open resources for spatial data analysis, modeling, and visualization in R, Python, Julia, and beyond, all rooted in open-source principles.
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📢 The geocompx project has a new (and fully reproducible) logo!
geocompx is a community-driven initiative for reproducible geocomputation across languages, building open resources for spatial data analysis, modeling, and visualization in R, Python, Julia, and beyond, all rooted in open-source principles.
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📢 The geocompx project has a new (and fully reproducible) logo!
geocompx is a community-driven initiative for reproducible geocomputation across languages, building open resources for spatial data analysis, modeling, and visualization in R, Python, Julia, and beyond, all rooted in open-source principles.
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📢 The geocompx project has a new (and fully reproducible) logo!
geocompx is a community-driven initiative for reproducible geocomputation across languages, building open resources for spatial data analysis, modeling, and visualization in R, Python, Julia, and beyond, all rooted in open-source principles.
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✨What’s new in geocomputation this year?
The #geocompx 2025 update covers project milestones, current work, and future plans.
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✨What’s new in geocomputation this year?
The #geocompx 2025 update covers project milestones, current work, and future plans.
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✨What’s new in geocomputation this year?
The #geocompx 2025 update covers project milestones, current work, and future plans.
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✨What’s new in geocomputation this year?
The #geocompx 2025 update covers project milestones, current work, and future plans.
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✨What’s new in geocomputation this year?
The #geocompx 2025 update covers project milestones, current work, and future plans.
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Happy to see new newest member of the #geocompx family up on the geocompx.org website: Spatial Data Visualization with tmap is an awesome book that is still in progress 🏗️ Well worth a read to launch your reproducible map making journey 🚀
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Chapter 8 of Geocomputation with Python is all about cartography:
🎨 Designing maps
🖼️ Static maps with .plot & rasterio.plot.show
🌐 Interactive maps with .explore -
Chapter 8 of Geocomputation with Python is all about cartography:
🎨 Designing maps
🖼️ Static maps with .plot & rasterio.plot.show
🌐 Interactive maps with .explore -
Chapter 8 of Geocomputation with Python is all about cartography:
🎨 Designing maps
🖼️ Static maps with .plot & rasterio.plot.show
🌐 Interactive maps with .explore -
Chapter 8 of Geocomputation with Python is all about cartography:
🎨 Designing maps
🖼️ Static maps with .plot & rasterio.plot.show
🌐 Interactive maps with .explore -
Chapter 8 of Geocomputation with Python is all about cartography:
🎨 Designing maps
🖼️ Static maps with .plot & rasterio.plot.show
🌐 Interactive maps with .explore -
Chapter 7 of Geocomputation with Python shows how to:
🔹 Find spatial datasets (geoportals & download tools)
🔹 Work with different file formats (strengths & limits)
🔹 Read & write vector + raster files efficiently -
#30DayMapChallenge (10 minute map)
This is trees tended by the city of Zürich, sized by tree crown diameter.
Done in Python, with loading data into duckdb and graphing on lonboard. The map is actually clickable and gives you meta-info about the trees when clicking on a tree.
I wanted to actually intersect this with street names containing tree names, but 10 minutes were not enough for that :).Crazy how quick you can get to something with open government data (OGD) and these modern #geocompx tools I am just discovering...
OGD data found via:
https://opendata.swiss/de/dataset/baumkataster/resource/d0ecd9ca-45fb-499b-9171-aac76b00fb42 -
My contribution to today's #30DayMapChallenge (Minimal Map)
This is a map of two months of cycling to work, two days a week, between Zürich and Winterthur (and exploring my options for gravel and beauty).
Done with duckdb + lonboard in Python. Repo here: https://codeberg.org/marioangst/winti-zh-gpx
I am quite new to doing spatial data, coming very much from the non-spatial data science side, but I'm having fun and I've got to say the #geocompx resources out there are really cool nowadays.
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Confused about coordinate reference systems (CRSs)? 🧭🌍🐍
Chapter 6 of Geocomputation with Python dives into:
- Geographic vs projected CRSs (lon/lat vs meters)
- Getting, setting & reprojecting CRSs
- Why ignoring CRSs can break your analysis 🚨 -
Working with raster + vector together in Python? 🗺️🌍🐍
Chapter 5 of geocompx talks about:
- Cropping & masking rasters with vectors
- Extracting raster values via vector data
- Raster ↔️ vector conversion (polygonize & rasterize) -
Want to transform the geometry of spatial data in Python? ✨🌍🐍
Chapter 4 of geocompy covers:
- Vector: simplify, buffer, centroid, clip, unions, affine transforms
- Raster: crop, resample, aggregate, align datasets -
Spatial operations in Python? 📍🌍🐍
Chapter 3 of Geocomputation with Python covers:
- Vector: spatial joins, subsetting, aggregation, etc.
- Raster: map algebra (local, focal, zonal, global), tiling & merging -
🗺️ New blog post: introducing Spatial Data Visualization with tmap, a work-in-progress guide to thematic mapping in #RStats.
Learn about the book, its progress, and how to contribute: https://geocompx.org/post/2025/tmap-bp1/
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🚀 Book in progress: Spatial Data Visualization with tmap
A practical guide to creating clear thematic maps in R with the tmap package.
Covers everything from loading data to interactive and animated maps, with reproducible code and examples.Read online: https://tmap.geocompx.org/
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We’ve updated the geocompx README.
Find guides, books, and tools for geocomputation in R, Python, and Julia — plus ways to get involved.
Take a look: https://github.com/geocompx
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We’ve updated the geocompx README.
Find guides, books, and tools for geocomputation in R, Python, and Julia — plus ways to get involved.
Take a look: https://github.com/geocompx
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We’ve updated the geocompx README.
Find guides, books, and tools for geocomputation in R, Python, and Julia — plus ways to get involved.
Take a look: https://github.com/geocompx
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We’ve updated the geocompx README.
Find guides, books, and tools for geocomputation in R, Python, and Julia — plus ways to get involved.
Take a look: https://github.com/geocompx
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We’ve updated the geocompx README.
Find guides, books, and tools for geocomputation in R, Python, and Julia — plus ways to get involved.
Take a look: https://github.com/geocompx
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Chapter 16: Summary & Future of Geocomputation 🚀📖
What’s next? 📌 This final chapter reflects on key themes, gaps, and the future of geocomputation. Crucially, learn how to contribute to open-source spatial communities!
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Chapter 15: Ecological Modeling & Geocomputation 🌱🗺️
Modeling the floristic gradient to reveal distinctive vegetation belts! 📌 Learn spatial modeling techniques with random forests & hyperparameter tuning to analyze ecological data in R.
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Chapter 14: Geomarketing & Location Analysis 🏪📍
Where should you open a bike shop? 📌 Learn how to use census & OpenStreetMap data for spatial decision-making in geomarketing & site selection.
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Have you read Geocomputation with R?📘
If you found it helpful, we’d really appreciate a quick review — it helps others find the book too!Goodreads: https://www.goodreads.com/book/show/214736719-geocomputation-with-r
Amazon: https://www.amazon.com/dp/1032248882
Book: https://r.geocompx.org/ -
Chapter 13: Transport Systems Analysis 🚶🚴🚌
Model transport networks! 📌 Analyze travel patterns, desire lines, routes, and accessibility using open data and reproducible geospatial workflows in R.
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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.
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Chapter 11: Writing Geoalgorithms 💻🧩🔁
Focuses on developing reusable and reproducible code for spatial tasks in R. Demonstrates algorithm design using examples like calculating polygon centroids.
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🪡 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
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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.
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Chapter 9: Mapping & Visualization 🗺️🖼️📊
Introduces tools for making static, animated, and interactive maps in R. Covers the tmap package and web-based options for sharing geographic data visually.
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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.
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Just signed-up to the #UTSG2025 conference in Dublin, 25th-27th June. Looking forward to presenting our work on integrating multiple network datasets for the Network Planning Tool, funded by Transport Scotland and developed in collaboration with Sustrans. This is the first time that cycling Level of Service (LoS) has been calculated for every road and presented alongside estimates of cycling potential nationwide anywhere, to the best of my knowledge. See you there! #NPT #geocompx
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Chapter 7: Coordinate Reference Systems 🧭📐🌐
This chapter explains how to work with coordinate reference systems (CRSs) in R. Learn how to reproject vector and raster data, and understand how CRS choices affect spatial analysis.
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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
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Chapter 6: Raster-Vector Interactions 🗺️🔄🌍
Crop, mask, extract, and rasterize! 📌 Learn how to convert between raster & vector data and perform spatial extractions in R.
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Chapter 5: Geometry Operations 📏🔄
Simplify, buffer, transform! 📌 Learn to modify vector geometries, clip spatial data, apply affine transformations, and resample rasters for better alignment.
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Chapter 4: Spatial Operations 📌🗺️
Modify, analyze, and relate spatial data! 📌 Learn how to subset by location, compute distances, merge rasters, and use raster algebra for powerful spatial analysis.
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Your feedback matters! If you’ve read Geocomputation with Python, consider writing a review on Amazon or Goodreads, etc.
https://www.amazon.com/Geocomputation-Python-Chapman-Hall-CRC/dp/1032460652/
https://www.goodreads.com/book/show/218000479-geocomputation-with-python
Thanks for your support! 🌍📖
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Ever struggled with the Modifiable Areal Unit Problem (MAUP) in your urban analysis? 😩 Good news! 🎉 The {zonebuilder} R package is BACK on CRAN after a short break! It provides standardized zoning systems to help you tackle this tricky issue. 💪 Search for "zonebuilders" to learn more and install! #rstats #geocompx #MAUP
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🚀 Online recording alert! 🚀
"Spontaneous growth of the geocompx FOSS4G community" from the #foss4ge2024 conf in Tartu.