#spatialml
Live, measured metrics for the hashtag #spatialml from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #spatialml
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-28 01:53 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-28 01:53 UTCNo related tags with measured usage found for #spatialml.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-28 01:53 UTCEverything below is measured over the latest 12 public posts (spanning ~24752 hours).
Posting hours (UTC) — busiest: 14:00
Languages: English (12)
Avg boosts / post: 6.4
Top of the latest posts
🛰️ 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://yota
🌍 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/s
🚀 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 #RSpa
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/spatialml