Take a break and dive into the basics of map algebra with GRASS! 
#grass #geospatial #tutorial #modelling #foss #osgeo #raster #processing
https://grass-tutorials.osgeo.org/content/tutorials/map_algebra/basic_map_algebra.html
MVT, MBT, PMTiles: Everything to know about vector tiles: Daniel-J-H offers a comprehensive overview of #vectortiles technology, including #Mapbox Vector Tiles (#MVT), #MBTiles, and #Protomaps’s #PMTiles. The post explains the evolution from #raster to #vector #maps, compares key formats and technologies,...
https://spatialists.ch/posts/2025/05/19-mvt-mbt-pmtiles-everything-to-know-about-vector-tiles/ #GIS #GISchat #geospatial #SwissGIS
Thinking of proposing a workshop at FOSS4G UK 2025 (Oct, Leeds, UK) on on-the-fly tile generation for webmaps.
Could cover MVT generation using PostGIS and pg_tileserv, raster tile generation using Titiler etc, or both (in a longer workshop). I'm not sure how much I can fit into one workshop...
Any thoughts as to which you'd prefer? Or particular things I should cover?
Have an excellent long weekend everyone (if you are in the US), we all deserve it!
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H/T Simon Ilyushchenko for the brilliant image!
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#GIS #spatial #mapping #raster #mapnerds #mapgeeks #fridayfeeling #fridayfun #raster #projection #connected #gettingyourbearings #coordinates
MVT, MBT, PMTiles: Everything to know about vector tiles: @djh offers a comprehensive overview of #vectortiles technology, including #Mapbox Vector Tiles (#MVT), #MBTiles, and #Protomaps’s #PMTiles. The post explains the evolution from #raster to #vector #maps, compares key formats and technologies,...
https://spatialists.ch/posts/2025/05-19-mvt-mbt-pmtiles-everything-to-know-about-vector-tiles/ #GIS #GISchat #geospatial #SwissGIS
The previous demo made me dig deeper into dithering algorithms. It's something I should have done years ago, as I've been using simple random dithering now and then, and I hadn't even thought of gamma correction. One algorithm in particular caught my eye: Riemersma dithering, which uses the Hilbert curve. Compared to the usual matrices for error diffusion, the curve approach seemed easier to implement in some ways, as it has fewer edge issues.
More interestingly, it struck a chord with my earlier experiments with space-filling curves in image processing. So it was a kind of familiar territory, but it also seemed esoteric enough that I could imagine making some new discoveries. For example, play with other plane-filling curves besides the Hilbert.
The first image uses the boustrophedon curve, which makes the vertical wave patterns I recall from a number of non-dithering demos. The second curve is what I call the diagstrophedon, a diagonal zig-zag starting from the top left corner, and I think its wavy artefacts make a nice match for Venus's hair.
Then in image 3 we have Hilbert, which doesn't seem to make any particular artefacts, and I guess that's a good thing for dithering. Finally 4 uses the Peano curve, which makes some fun wiggles in light areas.
Yet another optimized Voronoi tiling. This was supposed to be a simpler alternative to the previous tiling approach, but I ended up going down a rabbit hole of various dithering algorithms.
Instead of the equal-sum partitions, this uses regular dithering to find the Voronoi seed points, and the tile areas are inversely proportional to the colour values. My simple random dithering didn't work as well as expected, so I started to look into alternatives. I was of course aware of Floyd-Steinberg, and as I grew a bit tired of this demo, I ended up cheating a little by using a ready-made library. Since I was using PIL for image handling anyway, I could simply use its format conversion functions to get a 1-bit image, which uses F-S by default.
As before, I planned to use edge detection to get smaller tiles at the contrast edges. However, it didn't work so well with dithering, as it would concentrate basically all seed points at the edges. So here I used a mix of edge detection and the original. I think it worked out nicely here, as the bright colours often coincide with areas of small detail, while the dark background doesn't need much resolution.
Día 8 | Distribuciones – Histograma | #30DayChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr, #ggscale y #scales.
Another visual refinement to a recent demo: adding seams to the optimized tiling scheme. While it breaks the mosaic illusion to some extent, I think it makes the tile sizing idea much clearer. As before, there's a uniform variant with the same number of tiles for comparison.
Source photo: Mary of Egypt by José de Ribera, in public domain.
Día 9 | Distribuciones – Divergente | #30DatChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr and #SPEI.
RiverREM - Generating River Relative Elevation Model (REM) Visualisations
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https://github.com/OpenTopography/RiverREM <-- shared GitHub repository
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https://opentopography.github.io/RiverREM/ <-- shared documentation
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https://opentopography.org/blog/new-package-automates-river-relative-elevation-model-rem-generation <-- shared Open Topography blog post about RiverREM
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H/T Heidi Luchsinger / Open Topography
[this post should not be considered as an endorsement of this product aka caveat emptor]
#GIS #spatial #mapping #remotesensing #earthobservation #Python #LiDAR #RiverREM #visualisation #hydrology #water #river #rivervalley #floodplain #terraces #GitHub #opensource #opendata #DEM #REM #model #modeling #RiverRelativeModel #documentation #tutorial #learning #tool #elevation #raster #sinuosity #drainage
Day 10 | Distributions / Multi – Modal | #30DayChartChallenge. Visualization made with R using #ggplot2, #tidyverse, #cowplot, #stars, #raster, #ggspatial and #sf. Data source: Sentinel-2 MSI (2024)
This is a TLDR of the presentation I did at #foss4g in Belém, last year.
Check it out: https://george-silva.hashnode.dev/efficient-methods-for-generating-zonal-statistics-in-gis
New Map Of Landscape Beneath Antarctica Unveiled
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https://phys.org/news/2025-03-landscape-beneath-antarctica-unveiled.html <-- shared technical article
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https://doi.org/10.1038/s41597-025-04672-y <-- shared paper
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#GIS #spatial #mapping #Bedmap3 #icebed #surface #thickness #gridded #datasets #Antarctica #raster #model #modeling #landscape #elevation #icesheet #survey #remotesensing #earthobservation #climatechange #warming #climate #melt #melting #seafloor #subglacial #geophysical #survey #topography #geology #bathymetry #topobathy #BritishAntarcticSurvey
@BritishAntarcticSurvey
Ever needed to reuse the same raster extent & resolution across multiple QGIS tasks? My latest blog post shows how the Raster Layer Properties function can automatically grab all those details from a reference layer. A good way to make your workflows more consistent and error-proof. https://ecodiv.earth/post/rasterlayerproperties/ #QGIS #GIS #FOSS #Raster #OpenSource
Better raster speed & size randomness, color selection ...
I'm working a on "Loading Screen Raster Generator" which creates raster lines gif animations from the web
Colors accurate, variable frames (4 to 32), size accurate (403x284 because borders)
Totally useless but fun
Introduction To Remote Sensing And Geographical Information Systems [GIS]
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https://www.nateko.lu.se/sites/nateko.lu.se.sv/files/remote_sensing_and_gis_20111212.pdf <-- shared link to paper/publication
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[I have yet to dig into this myself, but it looks very promising]
#GIS #spatial #mapping #remotesensing #earthobservation #learning #onlinelearning #tutorial #education #learning #elearning #onlineclasses #distancelearning #school #virtuallearning #learn #edtech #digitallearning #students #remotelearning #student #onlinetraining #training #technology #spatialdata #spatialanalysis #spatiotemporal #concepts #satellite #imagery #aerialimagery #raster #vector #introduction #101
Does anyone remember that equation that makes lines in pixel art look straight and not jagged?
Greg Cocks 
