Lmst

🚨 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

🚀 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

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

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: https://jakubnowosad.com/posts/2025-04-13-msca-bp2

#MSCA #SpatialML #SpatialPatterns #GISchat

🚀 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 #MachineLearning #Geospatial #DataScience #DeepLearning #GISchat

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

🛰️ A new paper "scikit-eo: A Python package for Remote Sensing Data Analysis" on a tool for #LULC analysis with various machine learning and neural networks algorithms.🛰️

Article: https://doi.org/10.21105/joss.06692
Software: https://yotarazona.github.io/scikit-eo/

#geopython #remotesensing #landcover #spatialml