There's a third party Julia extension for Positron! It makes Julia a peer of R and Python in Positron. open-vsx.org/extension/nt...

The Potsdam Soil Moisture Observatory: high-coverage reference observations at kilometer scale Abstract. Cosmic-ray neutron sensing (CRNS) has gained popularity for estimating soil moisture due to its innovative capability to measure at an intermediate scale – a notable advantage over point-sca...

Just published: PoSMO dataset. 16 CRNS stations, 1 km², 2 years of continuous soil moisture. Perfect reference for validating satellite products where it matters — the root zone. Open access.
essd.copernicus.org/articles/18/...

Como me habéis picado, vamos a hacer un (otro) hilo con páginas de ilustraciones y fotos en dominio público.

Guardaos el hilo y darle repost si os parece interesante, porque se vienen curvas (quizás).

Anyone using raster pipeline in gdal 3.12? Why would "--add-alpha" work in standalone gdal raster reproject but not in the pipeline?

Positron plus JupyterHub logo, with the Posit logo in the corner.

We are thrilled to announce that Positron Server is now available for academic use via JupyterHub!

This gives students a robust #RStats & #Python data science IDE without needing a local install or new infrastructure.

Learn more: positron.posit.co/blog/posts/2...

cover of the book "Bayesian Workflow" by Gelman, Vehtari, et al. Coming out later this year, in the summer probably.

I would have preferred to have the "draw the rest of the owl" meme on the cover, but this will do. Seems like it is on schedule, and we'll leave some typos so you know we didn't write it with AI.

What’s next: Quarto 2 – Quarto We’ve started working on quarto-dev/q2, a full rewrite of Quarto in Rust.

And another Quarto announcement; I've alluded to it before, but we're making it "official".

We've started work on Quarto 2. The blog post has an overview: quarto.org/docs/blog/po...

We'll share more in future blog posts, but here's what you can expect from the Quarto 2 dev effort:

(1/)

Train Custom Deep Learning Models Without Coding using QGIS, Roboflow and Ultralytics Want to bring AI-powered object detection into your geospatial workflows without writing a single line of code? In this video, you’ll learn how to train your own custom deep learning model and use ...

New video: train custom #deeplearning models without coding using the #QGIS Deepness plugin, @roboflow.com & #Ultralytics.

Watch it on:
▶️QwastTube: videos.qwast-gis.com/w/ucEzYZ8tSV...
▶️YouTube: youtu.be/HIsheKG-lE4

#GIS #GeoAI

Part 2 of my shrinkage estimator series is out! Part 1 covered the univariate case, but now we dive into multivariate shrinkage 🤓

We cover Spearman's classic correlation disattenuation formula, multivariate James-Stein estimators, and hierarchical methods too

haines-lab.com/post/how-to-...

A screenshot showing: Introduction These are notes for my class on probability models. In these notes, I walk through the concepts and computation that support modern probability modeling in political science using both maximum likelihood and Bayesian approaches. The Goal There are many excellent books on probability models. But I felt the need to write my own. Why? I saw three problems. First, some classes assign a huge textbook. It might be possible for the strongest and most motivated students to become familiar with the range of topics covered in these textbook, but impossible to master. Instead, these textbooks seem like references, something you’re supposed to constantly be referring back to throughout your career. I know this because many of these books have instructors’ guides that suggest what should be covered in a single semester, what should be skipped, and how one might jump around. Instead, I want a book that students can work through beginning to end and master each idea. Second, some classes assign a variety of sections from several books and a collection of articles. But then the story told in the readings isn’t coherent. The styles are changing, the author’s tastes are changing, and the notation is changing. Switching among authors can feel like whiplash when learning a difficult subject. Instead, I want a book that tells a continuous story with consistent style, tastes, and notation. Third, some classes assign readings that support the lecture material, without exact alignment between the two. For better or worse, the content covered by the instructor in class feels like the most important material. Thus, I want a book that exactly aligns with the material I cover in class.

You guys @carlislerainey.bsky.social has a free textbook online and it seems really useful pos5747.github.io/notes/

Explainable Linear and Generalized Linear Models by the Predictions Plot Multiple linear regression is a basic statistical tool, yielding a prediction formula with the input variables, slopes, and an intercept. But is it really easy to see which terms have the largest e...

#rstats #dataviz

A new kid on the dataviz block is the predictions plot, showing how predictors in lm()/glm() contribute to
the predicted response. A novel and useful idea!

TAS: doi.org/10.1080/0003...
Implemented in the {classmap} package.

Statistical Rethinking 2026 is done: 20 new lectures emphasizing logical and critical statistical workflow, from basics of probability theory to causal inference to reliable computation to sensitivity. It's all free, made just for you. Lecture list and links: github.com/rmcelreath/s...

GitHub - posit-dev/great-docs: Great Docs lets you easily build a Python package docs site Great Docs lets you easily build a Python package docs site - posit-dev/great-docs

Anyone else spoiled by R's pkgdown and find python's mkdocs or sphinx a bit tedious and config-heavy. Check out @richmeister.bsky.social 's awesome new {great-docs} as a batteries-included alternative to spin up an effective docs site in <15 min!

1/n 🧵

github.com/posit-dev/gr...

Quarto v1.9 is out! We'll have an announcement blog post soon, but quarto.org/docs/download/ has the main highlights, including:

- PDF accessibility in latex and typst
- llms.txt support
- third-party engine extensions

Give it a whirl, and thanks!

Introducing Jupyter Book 2: Next-generation Tools for Creating Computati... C. Holdgraf & R. Cockett YouTube video by JupyterCon

At JupyterCon 2025, Chris Holdgraf (2i2c) and Rowan Cockett (Curvenote) introduce Jupyter Book 2 and the MyST Markdown engine powering the next generation of computational publishing.

Watch the talk:
www.youtube.com/watch?v=3MUS...

#Jupyter #OpenScience #DataScience #OpenSource

ArviZ: a modular and flexible library for exploratory analysis of Bayesian models Martin et al., (2026). ArviZ: a modular and flexible library for exploratory analysis of Bayesian models. Journal of Open Source Software, 11(119), 9889, https://doi.org/10.21105/joss.09889

New paper out in JOSS:

“ArviZ: a modular and flexible library for exploratory analysis of Bayesian models”

It covers the design principles behind ArviZ and the motivation for the refactoring in 1.0. joss.theoj.org/papers/10.21...

How to Estimate a Mean, and What It Means for Science | Computational Psychology Introduction If I asked you to estimate 30 means, you would probably compute 30 sample means. And you would be provably wrong (well.. maybe not wrong, but at least provably inefficient).

New blog just dropped!

This one is all about estimators—we cover James-Stein, classical test theory, empirical Bayes, penalized regression, and hierarchical models, showing how they all can be used to do a better job than sample stats alone 🤓

haines-lab.com/post/how-to-...

A screenshot from X from Ollie Ballinger talking about a tool to detect building damage in Iran using open source radar images.

Ollie Ballinger (not on Bluesky) has created a method to detect building damage in Iran using open source radar imagery, in light of satellite image companies restricting access to images from the country.

The method is described in this peer-reviewed paper: t.co/OAXynsosnt

A worldmap of the spatial distribution of extracted flood events in the Groundsource dataset. The map displays the total number of flood events extracted by the LLM-based pipeline aggregated per grid cell. The data are visualized using a Robinson projection, with event counts represented by a logarithmic color scale. Red points indicate the spatial centroids of reference flood events from the GDACS database.

Excited to announce Groundsource - an open-source dataset of historic flood events! This has easily been one of the coolest projects I've worked on recently!

Thread 🧵 for details and all relevant links. 1/n

The aftermath of the Iranian strike on the oil tankers at the Basra oil terminal shows an oil slick near the burned out tanker, March 14. It's likely fuel oil as the cargo, oil condensates / naphtha, seemed to have burned of in the fire after the explosion

Mapas de distribución de especies forestales europeas Mapas de distribución de las principales especies forestales europeas

¿Te gustan los mapas de distribución de especies? 🗺️🌲

He recopilado los mapas de las principales especies forestales europeas, desde el Pinus sylvestris hasta el Quercus robur.

¡Espero que los disfrutes tanto como yo creándolos! 👇

edu.forestry.es/2017/09/mapa...

#forestry #botany

¿Te gustaría crear vectores hidrológicos de flujo a partir de un MDT como los que se ven aquí?

En el vídeo tutorial que comparto a continuación se explica: edu.forestry.es/2026/03/dire...

Muy útil para ver la dirección y sentido de las escorrentías que se produzcan sobre tu territorio.

Flooded dunes of Lake Chad visualized with synthetic aperture radar (Sentinel 1 GRD). Seasonal composite (red = spring, dry season, green = summer, wet season, blue = fall, dry season). The colors result from change in vegetation cover and water level, dark areas are flooded all year.

The COPERNICUS/DEM/GLO30 Digital Surface Model (DSM) now has a much more detailed example script in Earth Engine. Give it a try!

developers.google.com/earth-engine...

code.earthengine.google.com?scriptPath=E...

#earthengine

The next scikit-learn release will allow inspecting the type and values of attributes of fitted estimators in Jupyter notebooks & example code rendered as HTML in sphinx-gallery powered project websites.

scikit-learn.org/dev/auto_exa...

A black and white declassified KH-7 GAMBIT spy satellite photograph of Ashgabat, Turkmenistan on July 16, 1966.

A black and white declassified KH-7 GAMBIT spy satellite photograph of Ashgabat, Turkmenistan on July 16, 1966.

A black and white declassified KH-7 GAMBIT spy satellite photograph of Ashgabat, Turkmenistan on July 16, 1966.

KH-7 images have the ability to scratch itches I didn't know existed.

This image of Ashgabat, Turkmenistan for example is incredible.

Downscaling daily solar radiation in the Canary Islands with GAM Researcher in climate science at MBG-CSIC

🆕 BLOG POST
There’s so much more to spatial downscaling today than classic LM or kriging. In my new blog post, I show how flexible and powerful GAMs can be for this task. #rstats #dataviz

➡️ dominicroye.github.io/blog/canary-...

1/ I'm starting to see more and more parallels between MOOCs and AI.

MOOCs worked in computer science because the end result of problems are either right or wrong. But they really ONLY worked in CS. They didn't work in any other field because there was no way to make assessment work at scale.

2. Install the diagram extension in a Quarto project. Create a new Quarto project. From the terminal, run this to install the diagram extension: quarto install extension pandoc-ext/diagram 3. Tell your document to use the extension. Add this to the YAML header of a Quarto document: filters: - diagram 4. Add a .tikz block to your document. Add a tikz code block to your document like this: ```{.tikz} \begin{tikzpicture}[>={stealth}] \node (x) at (0,0) {$X_{t}$}; \node (y) at (2,0) {$Y_{t + 1}$}; \node (z) at (1,1) {$Z$}; \path[->] (z) edge (x); \path[->] (z) edge (y); \path[->] (x) edge (y); \end{tikzpicture} ``` 5. Render! Render the document to PDF and you should see a diagram. Render it to HTML or .docx or Typst and it should use inkscape to convert it to SVG. Magic.

New blog post! After years of annoying shenanigans, I discovered that nowadays it's *really* straightforward to get tikz diagrams in #QuartoPub to automatically turn into SVGs in HTML, docx, and Typst! Install Inkscape, install a Quarto extension, and you're done. www.andrewheiss.com/blog/2026/02...

The next two days I will be using our "Happy Days" at @wheregroup to work on something new:

The *Project Checker*, a #QGIS plugin to check QGIS projects for potential issues

https://github.com/kannes/qgis_project_checker

It will detect e.g.
- Layers without […]

[Original post on norden.social]