Thinking in spatial patterns

Spatial machine learning has become a standard tool for producing environmental and geographic prediction maps.

At useR!

Title slide of the talk Keynote slides: https://jakubnowosad.com/ml4eo2026/ Workshop materials: https://jakubnowosad.com/ml4eo2026workshop/ Machine learning is now deeply embedded1 in Earth observation workflows, from mapping current environmental conditi…

Time flies, and I am now much closer to the end of the PRISM (PReservation and RecognItion of Spatial patterns using Machine learning) project than to its beginning.1.

Slides: https://jakubnowosad.com/agforum2025 This presentation covered three interconnected deep learning concepts appearing in spatial data science work.

Title slide Slides: https://jakubnowosad.com/rome2025 Video recording: https://youtu.be/uZe7thh80MI Reproducible code: https://jakubnowosad.com/rome2025/index.R Geospatial predictive mapping is a common task across many domains, aiming to produce continuo…

Last year, I received a grant from the Marie Skłodowska-Curie Actions Postdoctoral Fellowships (MSCA-PF) program for a project called PRISM: PReservation and RecognItion of Spatial patterns using Machine learning.

NoteMethods for comparing spatial patterns in raster data This is the sixth part of a blog post series on comparing spatial patterns in raster data.

NoteMethods for comparing spatial patterns in raster data This is the fifth part of a blog post series on comparing spatial patterns in raster data.

NoteMethods for comparing spatial patterns in raster data This is the fourth part of a blog post series on comparing spatial patterns in raster data.

NoteMethods for comparing spatial patterns in raster data This is the third part of a blog post series on comparing spatial patterns in raster data.

NoteMethods for comparing spatial patterns in raster data This is the second part of a blog post series on comparing spatial patterns in raster data.

NoteMethods for comparing spatial patterns in raster data This is the first part of a blog post series on comparing spatial patterns in raster data.

I received a grant from the Marie Skłodowska-Curie Actions Postdoctoral Fellowships (MSCA-PF) program: between August 2024 and August of 2026, I will be at the University of Muenster, Germany, working on a project named PRISM: PReservation and RecognItion…

The spatial kinetic Ising model is a simple model of spatial patterns that can be used to simulate the evolution of spatial patterns over time.

A two-dimensional Ising model is an idealized physical system that consists of a lattice of binary variables (magnetic spins) that can be in one of two states: up or down.

Spatial signatures represent spatial patterns of land cover in a given area.

The spatial signatures of categorical rasters are a set of numbers that describe the spatial patterns of the provided variables.

This is a second blog post in a series about the supercells package.

Segmentation is a process of partitioning space into smaller segments.

In the past, I wrote a post on how to calculate landscape-level metrics for local landscapes.

TLTR: This is a last blog post in a series about motif - an R package aimed for pattern-based spatial analysis.

TLTR: Clustering similar spatial patterns requires one or more raster datasets for the same area.

TLTR: Quantifying changes of spatial patterns requires two datasets for the same variable in the same area.

TLTR: Finding similar spatial patterns requires data for a query region and a search space.

TLTR: Spatial signatures are multi-value representations of the patterns that compress information about spatial composition and configuration.

I gave the overview of what is the pattern-based spatial analysis and how it can be applied for the RGS-IBG GIScience Webinar Series.

TLTR: motif is an R package aimed for pattern-based spatial analysis.

Bivariate color palettes are products of combining two separate color palettes.

The raceland package implements a computational framework for a pattern-based, zoneless analysis and visualization of (ethno)racial topography.

Maximilian H.K.

In the last few weeks, I was asked a similar question several times - how to calculate landscape metrics for local landscapes?

R version 4.0 is just around the corner.

Quantitative assessment of spatial patterns has been a keen interest of generations of spatial scientists and practitioners using spatial data.

A few months ago I have made an attempt to visualize the world population changes from 1800 to 2100: {{% tweet "1049685831475187712" %}} This way of visualization is good to show the ever-changing distribution of the population on a global scale.

Landscape metrics are algorithms that quantify physical characteristics of landscape mosaics (aka categorical raster) in order to connect them to some ecological processes.

Introduction GeoPAT 2 is an open-source software written in C and dedicated to pattern-based spatial and temporal analysis.

I am extremely proud to announce that Geocomputation with R is complete.

Last week Neil Kaye tweeted: Animating the Mercator projection to the true size of each country in relation to all the others.

Last month, Max Roser presented a cartogram of the Earth’s population in 2018.

Creating or determination of regions is a useful way to describe the world.

This is the sixth and the last blog post in the series introducing GeoPAT 2 - a software for pattern-based spatial and temporal analysis.

Blog posts in the series introducing GeoPAT 2 - a software for pattern-based spatial and temporal analysis: GeoPAT 2: Software for Pattern-Based Spatial and Temporal Analysis Pattern-based Spatial Analysis - core ideas Finding similar local landscapes Qua…

Blog posts in the series introducing GeoPAT 2 - a software for pattern-based spatial and temporal analysis: GeoPAT 2: Software for Pattern-Based Spatial and Temporal Analysis Pattern-based Spatial Analysis - core ideas Finding similar local landscapes Qua…

Blog posts in the series introducing GeoPAT 2 - a software for pattern-based spatial and temporal analysis: GeoPAT 2: Software for Pattern-Based Spatial and Temporal Analysis Pattern-based Spatial Analysis - core ideas Finding similar local landscapes Qua…

Blog posts in the series introducing GeoPAT 2 - a software for pattern-based spatial and temporal analysis: GeoPAT 2: Software for Pattern-Based Spatial and Temporal Analysis Pattern-based Spatial Analysis - core ideas Finding similar local landscapes Qua…

Global socio-economic data is easily accessible nowadays.

Blog posts in the series introducing GeoPAT 2 - a software for pattern-based spatial and temporal analysis: GeoPAT 2: Software for Pattern-Based Spatial and Temporal Analysis Pattern-based Spatial Analysis - core ideas Finding similar local landscapes Qua…

Update (2018-12-12): Alternative approach to this problem can be found at https://github.com/Nowosad/us-map-alternative-layout.

Foo Hello everybody!