🌍 Blog series: Spatial Machine Learning with R
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 geocompx.org/post/2025/sm...
#RStats #SpatialML #MachineLearning #RSpatial
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 geocompx.org/post/2025/sm...
#RStats #SpatialML #MachineLearning #RSpatial
October 22, 2025 at 1:05 PM
🌍 Blog series: Spatial Machine Learning with R
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 geocompx.org/post/2025/sm...
#RStats #SpatialML #MachineLearning #RSpatial
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 geocompx.org/post/2025/sm...
#RStats #SpatialML #MachineLearning #RSpatial
🌍 New paper on key challenges in spatial machine learning!
We discuss six major topics shaping the field: model validation, performance metrics, uncertainty quantification, algorithmic diversity, software implementation, and modeling protocols.
www.erdkunde.uni-bonn.de/article/view...
#SpatialML
We discuss six major topics shaping the field: model validation, performance metrics, uncertainty quantification, algorithmic diversity, software implementation, and modeling protocols.
www.erdkunde.uni-bonn.de/article/view...
#SpatialML
June 14, 2026 at 1:02 PM
🌍 New paper on key challenges in spatial machine learning!
We discuss six major topics shaping the field: model validation, performance metrics, uncertainty quantification, algorithmic diversity, software implementation, and modeling protocols.
www.erdkunde.uni-bonn.de/article/view...
#SpatialML
We discuss six major topics shaping the field: model validation, performance metrics, uncertainty quantification, algorithmic diversity, software implementation, and modeling protocols.
www.erdkunde.uni-bonn.de/article/view...
#SpatialML
🚨 Final part of our Spatial ML with R series ! 🚨
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
July 9, 2025 at 2:07 PM
🚨 Final part of our Spatial ML with R series ! 🚨
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
🚦 New workshop from #ML4EO2026: "Where your models can be trusted"
Learn how to evaluate spatial ML using kNNDM CV, Area of Applicability, and more. All with R examples.
Materials: jakubnowosad.com/ml4eo2026wor....
#SpatialML #MachineLearning #RStats #RSpatial
Learn how to evaluate spatial ML using kNNDM CV, Area of Applicability, and more. All with R examples.
Materials: jakubnowosad.com/ml4eo2026wor....
#SpatialML #MachineLearning #RStats #RSpatial
July 2, 2026 at 2:03 PM
🚦 New workshop from #ML4EO2026: "Where your models can be trusted"
Learn how to evaluate spatial ML using kNNDM CV, Area of Applicability, and more. All with R examples.
Materials: jakubnowosad.com/ml4eo2026wor....
#SpatialML #MachineLearning #RStats #RSpatial
Learn how to evaluate spatial ML using kNNDM CV, Area of Applicability, and more. All with R examples.
Materials: jakubnowosad.com/ml4eo2026wor....
#SpatialML #MachineLearning #RStats #RSpatial
What are the key challenges when using machine learning for spatial prediction?
In a new blog post, I summarize our recent paper, where we discuss spatial dependence, validation, sampling, uncertainty, applicability, and reproducibility in spatial ML.
jakubnowosad.com/posts/2026-0...
#SpatialML
In a new blog post, I summarize our recent paper, where we discuss spatial dependence, validation, sampling, uncertainty, applicability, and reproducibility in spatial ML.
jakubnowosad.com/posts/2026-0...
#SpatialML
September 8, 2026 at 2:02 PM
What are the key challenges when using machine learning for spatial prediction?
In a new blog post, I summarize our recent paper, where we discuss spatial dependence, validation, sampling, uncertainty, applicability, and reproducibility in spatial ML.
jakubnowosad.com/posts/2026-0...
#SpatialML
In a new blog post, I summarize our recent paper, where we discuss spatial dependence, validation, sampling, uncertainty, applicability, and reproducibility in spatial ML.
jakubnowosad.com/posts/2026-0...
#SpatialML
🚀 New blog post! Part 5 of our series on spatial ML with #RStats explores specialized packages: RandomForestsGLS, spatialRF, and meteo -- tools beyond caret, tidymodels, & mlr3.
URL: geocompx.org/post/2025/sm...
#SpatialML #RSpatial #MachineLearning
URL: geocompx.org/post/2025/sm...
#SpatialML #RSpatial #MachineLearning
June 25, 2025 at 2:05 PM
🚀 New blog post! Part 5 of our series on spatial ML with #RStats explores specialized packages: RandomForestsGLS, spatialRF, and meteo -- tools beyond caret, tidymodels, & mlr3.
URL: geocompx.org/post/2025/sm...
#SpatialML #RSpatial #MachineLearning
URL: geocompx.org/post/2025/sm...
#SpatialML #RSpatial #MachineLearning
🌍 My #ML4EO2026 talk focused on spatial machine learning and prediction-domain adaptive evaluation: defining the prediction domain, adapting validation, and weighting evaluation by deployment location properties.
Slides: jakubnowosad.com/ml4eo2026/
#SpatialML #MachineLearning #RSpatial
Slides: jakubnowosad.com/ml4eo2026/
#SpatialML #MachineLearning #RSpatial
June 29, 2026 at 2:02 PM
🌍 My #ML4EO2026 talk focused on spatial machine learning and prediction-domain adaptive evaluation: defining the prediction domain, adapting validation, and weighting evaluation by deployment location properties.
Slides: jakubnowosad.com/ml4eo2026/
#SpatialML #MachineLearning #RSpatial
Slides: jakubnowosad.com/ml4eo2026/
#SpatialML #MachineLearning #RSpatial
🚨 Final part of our Spatial ML with R series ! 🚨
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: https://geocompx.org/post/2025/sml-bp6/
#rstats #spatialml #rspatial
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: https://geocompx.org/post/2025/sml-bp6/
#rstats #spatialml #rspatial
July 9, 2025 at 2:03 PM
🚨 Final part of our Spatial ML with R series ! 🚨
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: https://geocompx.org/post/2025/sml-bp6/
#rstats #spatialml #rspatial
We explore spatial cross-validation with sperrorest & blockCV — tools outside the usual ML frameworks 📦
URL: https://geocompx.org/post/2025/sml-bp6/
#rstats #spatialml #rspatial
New blog post by Jan Linnenbrink: Spatial machine learning with caret 📍
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
May 19, 2025 at 2:04 PM
New blog post by Jan Linnenbrink: Spatial machine learning with caret 📍
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: geocompx.org/post/2025/sm...
#rstats #SpatialML #rspatial
🚀 Exciting developments in blockCV v4.0 by Roozbeh Valavi!
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
github.com/rvalavi/bloc...
#rstats #rspatial #spatialML #GISchat #MachineLearning
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
github.com/rvalavi/bloc...
#rstats #rspatial #spatialML #GISchat #MachineLearning
September 2, 2026 at 2:02 PM
🚀 Exciting developments in blockCV v4.0 by Roozbeh Valavi!
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
github.com/rvalavi/bloc...
#rstats #rspatial #spatialML #GISchat #MachineLearning
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
github.com/rvalavi/bloc...
#rstats #rspatial #spatialML #GISchat #MachineLearning
Want to showcase your work on #MachineLearning in #Geography? 🌍
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
December 18, 2024 at 4:00 PM
Want to showcase your work on #MachineLearning in #Geography? 🌍
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
🌍 Blog series: Spatial Machine Learning with R
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 https://geocompx.org/post/2025/sml-bp1/
#rstats #spatialml #machinelearning #rspatial
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 https://geocompx.org/post/2025/sml-bp1/
#rstats #spatialml #machinelearning #rspatial
October 22, 2025 at 1:02 PM
🌍 Blog series: Spatial Machine Learning with R
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 https://geocompx.org/post/2025/sml-bp1/
#rstats #spatialml #machinelearning #rspatial
From caret to tidymodels, mlr3, and specialized spatial ML packages — explore how spatial context changes the way we build ML models in R.
Start with Part 1 👉 https://geocompx.org/post/2025/sml-bp1/
#rstats #spatialml #machinelearning #rspatial
🚀 Last week, we hosted "Advances in Spatial Machine Learning 2025", a two-day workshop tackling open challenges in the field.
From validation to uncertainty analysis, we explored key topics with top researchers.
Now, we're working on synthesizing outcomes—stay tuned!
#SpatialML #GISchat
From validation to uncertainty analysis, we explored key topics with top researchers.
Now, we're working on synthesizing outcomes—stay tuned!
#SpatialML #GISchat
April 3, 2025 at 1:02 PM
🚀 Last week, we hosted "Advances in Spatial Machine Learning 2025", a two-day workshop tackling open challenges in the field.
From validation to uncertainty analysis, we explored key topics with top researchers.
Now, we're working on synthesizing outcomes—stay tuned!
#SpatialML #GISchat
From validation to uncertainty analysis, we explored key topics with top researchers.
Now, we're working on synthesizing outcomes—stay tuned!
#SpatialML #GISchat
🚀 New blog post! Part 5 of our series on spatial ML with #rstats explores specialized packages: RandomForestsGLS, spatialRF, and meteo -- tools beyond caret, tidymodels, & mlr3.
URL: https://geocompx.org/post/2025/sml-bp5/
#spatialml #rspatial #machinelearning
URL: https://geocompx.org/post/2025/sml-bp5/
#spatialml #rspatial #machinelearning
June 25, 2025 at 2:01 PM
🚀 New blog post! Part 5 of our series on spatial ML with #rstats explores specialized packages: RandomForestsGLS, spatialRF, and meteo -- tools beyond caret, tidymodels, & mlr3.
URL: https://geocompx.org/post/2025/sml-bp5/
#spatialml #rspatial #machinelearning
URL: https://geocompx.org/post/2025/sml-bp5/
#spatialml #rspatial #machinelearning
this week in #rstats 🕺
- spatialML pkgs 🌐 @jakubnowosad.com
- {futureverse} 🔮 @henrikbengtsson.bsky.social
- file-opening code 📂 @masalmon.eu
- {mirai} 🚅 @shikokuchuo.net
- Quarto speaker notes 🗣️ @rfortherestofus.com
this and more below! 🔥
#news #quarto #data
www.linkedin.com/pulse/week-r...
- spatialML pkgs 🌐 @jakubnowosad.com
- {futureverse} 🔮 @henrikbengtsson.bsky.social
- file-opening code 📂 @masalmon.eu
- {mirai} 🚅 @shikokuchuo.net
- Quarto speaker notes 🗣️ @rfortherestofus.com
this and more below! 🔥
#news #quarto #data
www.linkedin.com/pulse/week-r...
This week in R (2025-06-27)
The latest in asynchronous programming in R, from two big frameworks; file-opening helpers; specialised spatial ML; Quarto presentation tips, and more!
www.linkedin.com
June 27, 2025 at 12:20 PM
this week in #rstats 🕺
- spatialML pkgs 🌐 @jakubnowosad.com
- {futureverse} 🔮 @henrikbengtsson.bsky.social
- file-opening code 📂 @masalmon.eu
- {mirai} 🚅 @shikokuchuo.net
- Quarto speaker notes 🗣️ @rfortherestofus.com
this and more below! 🔥
#news #quarto #data
www.linkedin.com/pulse/week-r...
- spatialML pkgs 🌐 @jakubnowosad.com
- {futureverse} 🔮 @henrikbengtsson.bsky.social
- file-opening code 📂 @masalmon.eu
- {mirai} 🚅 @shikokuchuo.net
- Quarto speaker notes 🗣️ @rfortherestofus.com
this and more below! 🔥
#news #quarto #data
www.linkedin.com/pulse/week-r...
New blog post by Jan Linnenbrink: Spatial machine learning with caret 📍
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: https://geocompx.org/post/2025/sml-bp2/
#rstats #spatialml #rspatial
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: https://geocompx.org/post/2025/sml-bp2/
#rstats #spatialml #rspatial
May 19, 2025 at 2:04 PM
New blog post by Jan Linnenbrink: Spatial machine learning with caret 📍
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: https://geocompx.org/post/2025/sml-bp2/
#rstats #spatialml #rspatial
Using `caret` to predict air temperature in Spain with spatial data, addressing autocorrelation and extrapolation with `blockCV` and `CAST`.
Read here: https://geocompx.org/post/2025/sml-bp2/
#rstats #spatialml #rspatial
It’s been 8 months since I started my MSCA-PF fellowship 🇩🇪
Read the latest blog post for updates on research, collaborations, and life in Münster.
URL: jakubnowosad.com/posts/2025-0...
#MSCA #SpatialML #SpatialPatterns #GISchat
Read the latest blog post for updates on research, collaborations, and life in Münster.
URL: jakubnowosad.com/posts/2025-0...
#MSCA #SpatialML #SpatialPatterns #GISchat
The PRISM project’s progress report: 8 months into the MSCA-PF journey – Thinking in spatial patterns
Hi! I’m Jakub Nowosad, an Associate Professor at Adam Mickiewicz University and a Visiting Scientist at the University of Münster. My work focuses on developing spatial methods to better understand…
jakubnowosad.com
April 16, 2025 at 2:13 PM
It’s been 8 months since I started my MSCA-PF fellowship 🇩🇪
Read the latest blog post for updates on research, collaborations, and life in Münster.
URL: jakubnowosad.com/posts/2025-0...
#MSCA #SpatialML #SpatialPatterns #GISchat
Read the latest blog post for updates on research, collaborations, and life in Münster.
URL: jakubnowosad.com/posts/2025-0...
#MSCA #SpatialML #SpatialPatterns #GISchat
My PhD student Ebby Samson (jointly supervised by Wayne Luk) now has a seminar "Exploring FPGA designs for MX and beyond" as part of the SpatialML seminar series, now at www.youtube.com/watch?v=-AKQ.... Thanks to Andrew Boutros for hosting!
Exploring FPGA Designs for MX and Beyond - Ebby Samson
YouTube video by Spatial ML Seminar Series
www.youtube.com
January 29, 2025 at 7:54 PM
My PhD student Ebby Samson (jointly supervised by Wayne Luk) now has a seminar "Exploring FPGA designs for MX and beyond" as part of the SpatialML seminar series, now at www.youtube.com/watch?v=-AKQ.... Thanks to Andrew Boutros for hosting!
Want to showcase your work on #machinelearning in #geography? 🌍
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
December 18, 2024 at 4:22 PM
Want to showcase your work on #machinelearning in #geography? 🌍
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
Submit to Erdkunde's Special Issue: Machine Learning in Geography – Challenges & Perspectives.
🔗 More info: https://buff.ly/3VLlPGq
#ml #spatialml #gischat
Thanks, Andrei. I just tried it on the provided example and its seems limited in the same way as the SpatialML package: it works on small data, but does not seem to be suitable for larger (raster) data problems I usually work on. Or maybe I am missing something?
April 14, 2025 at 2:44 PM
Thanks, Andrei. I just tried it on the provided example and its seems limited in the same way as the SpatialML package: it works on small data, but does not seem to be suitable for larger (raster) data problems I usually work on. Or maybe I am missing something?
🚀 Exciting developments in blockCV v4.0 by Roozbeh Valavi!
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
https://github.com/rvalavi/blockCV#whats-new-in-v40
#rstats #rspatial #spatialml #gischat #machinelearning
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
https://github.com/rvalavi/blockCV#whats-new-in-v40
#rstats #rspatial #spatialml #gischat #machinelearning
September 2, 2026 at 2:04 PM
🚀 Exciting developments in blockCV v4.0 by Roozbeh Valavi!
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
https://github.com/rvalavi/blockCV#whats-new-in-v40
#rstats #rspatial #spatialml #gischat #machinelearning
A major update for spatial cross-validation in R, adding new tools for kNN distance matching, fold diagnostics, and more.
https://github.com/rvalavi/blockCV#whats-new-in-v40
#rstats #rspatial #spatialml #gischat #machinelearning
CRAN removals: AICcPermanova alphaci BT CAMML clrng depigner distreg.vis DMQ egcm epiCleanr FACT KODAMA MetChem MTAFT PStrata RXshrink SBCK SpatialML SWMPrExtension XRJulia #rstats
November 28, 2025 at 11:02 AM
CRAN removals: AICcPermanova alphaci BT CAMML clrng depigner distreg.vis DMQ egcm epiCleanr FACT KODAMA MetChem MTAFT PStrata RXshrink SBCK SpatialML SWMPrExtension XRJulia #rstats
New on CRAN: SpatialML (1.8.2). View at https://CRAN.R-project.org/package=SpatialML
SpatialML: Spatial Machine Learning
Implements a spatial extension of the random forest algorithm (Georganos et al. (2019) <<a href="https://doi.org/10.1080%2F10106049.2019.1595177" target="_top">doi:10.1080/10106049.2019.1595177</a>>). Provides a Geographically Weighted Random Forest regression and a routine to find the optimal bandwidth (Georganos and Kalogirou (2022) <<a href="https://doi.org/10.3390%2Fijgi11090471" target="_top">doi:10.3390/ijgi11090471</a>>). A lightweight cross-validation helper for tuning the 'mtry' parameter of a random forest and a generator of synthetic spatial test data are also included. The package depends on 'ranger' as its single random-forest back-end.
CRAN.R-project.org
July 6, 2026 at 12:41 PM
New on CRAN: SpatialML (1.8.2). View at https://CRAN.R-project.org/package=SpatialML