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Nick Bearman

@nickbearman.bsky.social
95 followers 93 following 73 posts

GIS Trainer & Consultant; now also at fosstodon.org/@nickbearman, Cartographic Editor @carto-giscience.bsky.social‬; cartography, open data, QGIS, R, linktr.ee/nickbearman

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Nick Bearman @nickbearman.bsky.social · 18/09/2026
OSGeo:UK do some great work, including the FOSS4G:UK conference series, and will be supporting FOSS4G 2027 in Bristol next year! Get involved!
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 17/09/2026
CaGIS Volume 53 Issue 5, including a special section on AsiaCarto 2024 is now available online and the printed copy is on its way to our subscribers! www.tandfonline.com/toc/tcag20/5... #GISchat We have 8 great papers, check out the thread below:
Front cover, for Cartography and Geographic Information Science, Volume 53, No 5, September 2026, The Journal of the Cartography and Geographic Information Society. Includes Figure 1 by Yang et al. A sample of map layout graph construction, which is a research diagram illustrating map layout graph construction. Part a) shows a world map of seismic activity with 6 colored markers representing different elements on the map. Part b) transforms these into a graph theory representation where elements become vertices (v1-v6) connected by edges showing relationships.
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Nick Bearman @nickbearman.bsky.social · 16/09/2026
Want to learn how to visualise and analyze spatial data in the social sciences? My GIS seminars are coming up in Oct & Nov 2026: - Intro to QGIS and Advanced QGIS - Intro to R and Advanced R Perfect for PhD students, researchers & academics! More details nickbearman.com/training-cou...
Students working on laptops creating maps.A screenshot of QGIS showing a world map in green.A screenshot of a map created in R, showing Percentage population Ages 10 to 14 for Liverpool, UK. Screenshot of a Zoom window with participants.
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Nick Bearman @nickbearman.bsky.social · 11/09/2026
Great to have you sponsoring, GeoDa. Looking forward to catching up at FOSS4G:UK and seeing what you're up to.
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Nick Bearman @nickbearman.bsky.social · 01/09/2026
Should be great, looking forward to it!
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Nick Bearman @nickbearman.bsky.social · 24/08/2026
Already know a bit of R and GIS but want to extend your knowledge? My Advanced R for Spatial Analysis course is coming up starting *tomorrow*: For those ready to dive deeper, who want to learn about spatial statistics and overlays nickbearman.com/training-cou...
Screenshot of a Zoom window with participants. Map showing overlapping circular buffer zones around tram stations (marked with red and black dots) with areas coloured by IMD Decile values ranging from 1-10, displayed in graduated blue shades from light to dark.
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Nick Bearman @nickbearman.bsky.social · 21/08/2026
Just sending out my welcome email for my Advanced R for Spatial Analysis course starting Tues - but don't worry, there is still space! Know R and GIS but want to extend your knowledge? For those ready to dive deeper, to learn about spatial statistics and overlays nickbearman.com/training-cou...
Screenshot of a course announcement creation dialog for 'Advanced R for Spatial Analysis 2.0', containing a welcome message with software installation instructions and course prerequisites.Map showing overlapping circular buffer zones around tram stations (marked with red and black dots) with areas coloured by IMD Decile values ranging from 1-10, displayed in graduated blue shades from light to dark.
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Nick Bearman @nickbearman.bsky.social · 17/08/2026
Want to learn how to visualise and analyze spatial data using #R? My #R #GIS courses are coming up in the next few weeks: Intro to using R as a GIS - tomorrow & 19 Aug No prior knowledge needed! Advanced R as a GIS - 25 & 26 Aug For those ready to dive deeper nickbearman.com/training-cou...
A screenshot of a map created in R, showing Percentage population Ages 10 to 14 for Liverpool, UK. Map showing overlapping circular buffer zones around tram stations (marked with red and black dots) with areas coloured by IMD Decile values ranging from 1-10, displayed in graduated blue shades from light to dark.
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Nick Bearman @nickbearman.bsky.social · 12/08/2026
Want to learn how to visualise and analyze spatial data using #R? My #R #GIS courses are coming up in the next few weeks: Intro to using R as a GIS - 18 & 19 Aug No prior knowledge needed! Advanced R as a GIS - 25 & 26 Aug For those ready to dive deeper nickbearman.com/training-cou...
A screenshot of a map created in R, showing Percentage population Ages 10 to 14 for Liverpool, UK. Map showing overlapping circular buffer zones around tram stations (marked with red and black dots) with areas coloured by IMD Decile values ranging from 1-10, displayed in graduated blue shades from light to dark.
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Nick Bearman @nickbearman.bsky.social · 10/08/2026
Know QGIS a bit already but want to dive deeper? Want to learn how to visualise and analyze spatial data in the social sciences and build your #GIS skills? LAST FEW PLACES for Advanced QGIS Spatial Analysis course starting TOMORROW 11th August instats.org/seminar/adva... #GISchat
A image of a point in polygon analysis - a series of hexagons with different coloured points in - and of a map showing local authorities (orange) overlaid with green space (green).
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OSGeo:UK @uk.osgeo.org · 04/08/2026
Early Bird tickets for FOSS4G:UK 2026 are now sold out! 🎉 A huge thank you to everyone who secured an Early Bird ticket. The Call for Presentations (CFP) is now closed too. Thank you to everyone who submitted talks and workshops.
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Nick Bearman @nickbearman.bsky.social · 03/08/2026
Want to learn how to visualise and analyze spatial data in the social sciences? My #Intro #QGIS course starts TOMORROW: Intro to QGIS & Spatial Data - No prior knowledge needed! More details at: nickbearman.com/training-cou... Any questions, please ask!
A screenshot of QGIS showing a world map in green.Screenshot of a Zoom window with participants.
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 03/08/2026
New article! Fascinating article from Lu Cheng, Taisheng Chen and colleagues exploring differences of spatial visual attention and spatial confidence during spatial orientation in unfamiliar environments doi.org/10.1080/1523... #GISchat
Figure 3: Representative composite heat maps of visual attention during map-based navigation tasks 2-4, comparing a) a poor-SD (spatial disorientation) participant and b) a good-SD participant. Both maps show the same urban area with streets, parks (green), water (blue), and numbered points of interest (1-10 and A-D). Starting and end points are labeled. Heat map colors indicate visual attention intensity: orange/red shows high concentration, blue shows low or no attention. The poor-SD participant's map displays concentrated orange/red clusters throughout, suggesting scattered attention. The good-SD participant's map shows dispersed blue tones with subtle patterns, suggesting more systematic scanning. Each map includes a north arrow and 1:20m scale bar. The comparison demonstrates differences in visual attention patterns related to spatial disorientation abilities during map-based wayfinding.
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Nick Bearman @nickbearman.bsky.social · 30/07/2026
Want to learn how to visualise and analyze spatial data in the social sciences and build your #GIS skills? My GIS seminars are coming up over in August 2026: Intro to Spatial Data & R as a GIS Advanced R for Spatial Analysis nickbearman.com/training-cou... #GISchat #R #GIS
A screenshot of a map created in R, showing Percentage population Ages 10 to 14 for Liverpool, UK. A map showing tram stations (red and black points) with a 600m buffer (circles) around each, on top of IMD data (shades of blue).
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Nick Bearman @nickbearman.bsky.social · 30/07/2026
Starting on Tuesday, 2pm (UK/London) or sign up and watch the recording. Want to learn how to visualise and analyze spatial data in the social sciences? Check out my #QGIS courses Not sure? Check out my FREE What is GIS? seminar at instats.org/seminar/what... to find out more.
instats.org
What is GIS? 2.0 (Free Seminar) - Livestreamed Research Training | Instats
PhD-level seminar on What is GIS? 2.0 (Free Seminar) with Nick Bearman . Live Q&A plus on‑demand access. Join via your university’s Instats membership or enroll directly.
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Nick Bearman @nickbearman.bsky.social · 28/07/2026
Want to learn how to visualise and analyze spatial data in the social sciences and build your #GIS skills? My Intro QGIS and Advanced QGIS courses are starting next week, with @instats.bsky.social instats.org/seminar/intr... instats.org/seminar/adva... nickbearman.com/training-cou... #GISchat
A image of a point in polygon analysis - a series of hexagons with different coloured points in - and of a map showing local authorities (orange) overlaid with green space (green). A screenshot of QGIS showing a world map in green.
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Nick Bearman @nickbearman.bsky.social · 24/07/2026
Less than 1 week to go. Make sure you get to #FOSS4GUK in Leeds this year - it will be amazing!
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 14/07/2026
New article! Federico De Angelis & Paolo Beria @beriapaolo.bsky.social present some new ways of mapping origin-destination matrices with national-scale commuting data doi.org/10.1080/1523... #GISchat
 Mobility resultants for Italy, work commuting, year 2011. Labels refer to places mentioned in the text. The map displays Italy with terrain shown in light gray and major cities labeled including Milan, Turin, Venice, Bologna, Rome, Naples, Palermo, and others. Orange flow lines represent commuting patterns between locations, with line thickness indicating volume of movement. The legend shows two classification systems: 'Monodirectionality index' (0-0.33, 0.33-0.50, 0.50-0.66, 0.66-1.00) and 'Total movements [pax]' (1-257, 257-614, 614-1577, >1577). Strong commuting corridors appear around major urban centers like Milan and Rome, shown by prominent orange flow patterns radiating outward. Regional annotations identify areas like Rimini, Ancona, Cagliari, and Bari. The visualization demonstrates uneven geographic distribution of work commuting, with concentrated patterns in northern industrial regions and more dispersed patterns in southern Italy.
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Nick Bearman @nickbearman.bsky.social · 09/07/2026
Really looking forward to hearing from Abi!
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Nick Bearman @nickbearman.bsky.social · 09/07/2026
All finished, and the recording is now available via instats.org/seminar/what... and please do post any questions you have!
instats.org
What is GIS? 2.0 (Free Seminar) - Livestreamed Research Training | Instats
PhD-level seminar on What is GIS? 2.0 (Free Seminar) with Nick Bearman . Live Q&A plus on‑demand access. Join via your university’s Instats membership or enroll directly.
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Nick Bearman @nickbearman.bsky.social · 07/07/2026
🗺️ FREE GIS seminar for researchers TOMORROW! Learn about GIS, spatial data analysis, visualization & software tools with Dr. Nick Bearman. Perfect for PhD students, researchers & academics looking to add a spatial dimension to their work! instats.org/seminar/what... @instats.bsky.social #GIS
Screenshot of Posit Cloud (formerly RStudio Cloud) interface for a project titled 'intro-r-spatial-analysis' by user Nick Bearman. The interface is divided into several sections: 1) Left side shows an R script editor with code visible on lines 231-250, including commands for calculating crime rates, joining population data to LSOA crimes, and creating a map using the tmap package with tm_shape() and tm_polygons() functions using a 'brewer.greens' color scale; 2) Upper right shows the Environment panel listing data objects including 'breaks', 'crimes', 'crimes_sf'; 3) Lower right displays a Plots panel showing a choropleth map with geographic boundaries filled in varying shades of green representing 'Rate of Crimes per 10,000 population' with a legend showing five categories ranging from 6-87 to 884-2,624; 4) Bottom shows Console/Terminal tabs with R console output. The interface includes standard RStudio menus (File, Edit, Code, View, Plots, Session, Build, Debug, Profile, Tools, Help) and toolbar buttons.A screenshot of QGIS showing a world map in green.
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Nick Bearman @nickbearman.bsky.social · 06/07/2026
Want to learn how to visualise and analyze spatial data? My #R #GIS courses are coming up in Aug 2026: Intro to using R as a GIS - No prior knowledge needed! Advanced R as a GIS - For those ready to dive deeper nickbearman.com/training-cou...
Screenshot of Posit Cloud (formerly RStudio Cloud) interface for a project titled 'intro-r-spatial-analysis' by user Nick Bearman. The interface is divided into several sections: 1) Left side shows an R script editor with code visible on lines 231-250, including commands for calculating crime rates, joining population data to LSOA crimes, and creating a map using the tmap package with tm_shape() and tm_polygons() functions using a 'brewer.greens' color scale; 2) Upper right shows the Environment panel listing data objects including 'breaks', 'crimes', 'crimes_sf'; 3) Lower right displays a Plots panel showing a choropleth map with geographic boundaries filled in varying shades of green representing 'Rate of Crimes per 10,000 population' with a legend showing five categories ranging from 6-87 to 884-2,624; 4) Bottom shows Console/Terminal tabs with R console output. The interface includes standard RStudio menus (File, Edit, Code, View, Plots, Session, Build, Debug, Profile, Tools, Help) and toolbar buttons.Screenshot of a Zoom window with participants.
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Nick Bearman @nickbearman.bsky.social · 01/07/2026
Want to learn how to visualise and analyze spatial data in the social sciences? My #GIS courses are coming up in Aug 2026: Intro to QGIS & Spatial Data - No prior knowledge needed! Advanced QGIS Spatial Analysis - For those ready to dive deeper nickbearman.com/training-cou...
A image of a point in polygon analysis - a series of hexagons with different coloured points in - and of a map showing local authorities (orange) overlaid with green space (green). Screenshot of a Zoom window with participants.
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Nick Bearman @nickbearman.bsky.social · 30/06/2026
Lots of exciting content to check out here, including a CaGIS interview with Valentin Meo and yours truly on Deepfake Geography :-)
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 29/06/2026
New article from Kurtis Danluk, Bernhard Jenny and colleagues presenting Ring maps: a new view for augmented reality navigation doi.org/10.1080/1523... #GISchat Source code at github.com/berniejenny/...
Figure 1: A ring map with an inner and an outer ring created by the prototype for the Apple Vision Pro augmented-reality headset, as seen from the viewer's perspective. The photograph shows an outdoor plaza area with trees, buildings, and people in winter/early spring conditions. A hand holding the device is visible in the foreground pointing toward an augmented reality overlay. The AR visualization displays concentric rings labeled 'Inner ring' (Closest landmark distance 10 m) and 'Outer ring' (Farthest landmark distance 500 m). A 3D landmark model of McKinney Tower is overlaid on the real-world landmark building in the center distance. White text labels identify the real-world landmark, the 3D landmark representation, and the ring boundaries. A pink/magenta colored rectangular shape appears on a nearby tree trunk, labeled 'Location & Heading +15'. The visualization demonstrates spatial awareness and proximity measurement in augmented reality.
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 25/06/2026
New article! Atsushi Masuyama explores execution-level variability for geographic masking: a new way to help improve privacy without compromising analytical utility doi.org/10.1080/1523... #GISchat Check out the data at doi.org/10.6084/m9.f...
Figure 3: Comparison of crime locations before and after masking using donut masking with different parameter settings. Panel a) shows results with r = 100 m and panel b) with r = 500 m. Both maps display the same urban area with underlying street network visible as thin gray lines, census blocks (solid gray polygons labeled 'Households ≥ 0'), and Chôme boundaries (white/unfilled polygons). Pre-masking Hypothetical Crime Locations are marked with filled black circles, representing original crime positions. Post-masking Crime Locations are shown as hollow/open circles, indicating the displaced positions after applying the donut masking algorithm. Each map includes a north arrow and 1 km scale bar. The larger radius in panel b) (500m) produces greater displacement of crime locations compared to the smaller radius in panel a) (100m), demonstrating how the radius parameter controls the privacy protection level in crime data masking.
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AGI Geocommunity @geocommunity.bsky.social · 24/06/2026
Registration for GeoCom 2026 is Open! Our flagship event for the UK geospatial sector will be held on the 12th November 2026, returning once again to the Royal Geographical Society (with IBG), in London Register🔗https://www.agi.org.uk/agi-flagship-geocom/
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Nick Bearman @nickbearman.bsky.social · 25/06/2026
Great to see Astun Technology support FOSS4G:UK 2026! Thank you!
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Nick Bearman @nickbearman.bsky.social · 24/06/2026
I've just launched gitRmap — a semi-automated map of locations you can add your own points to. Designed for people new to GIS, but who know a little bit of Git. Fork → edit a CSV → get a map. No coordinates needed! Blog post: nickbearman.com/blog/2026-06... Try it out: nickbearman.com/gitRmap/
A screenshot of gitRmap, a Leaflet web map with a series of points on the map.
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Nick Bearman @nickbearman.bsky.social · 23/06/2026
Great to be adding to my GeoAI slides for my upcoming What is GIS? FREE Seminar with @instats.bsky.social Come along on 8th July and find out What is GIS? #GISchat instats.org/seminar/what...
A screenshot of slides and video of Dr Nick Bearman's InStats course What is GIS?
A series of six Russian Dolls with labels Data Analytics, Artificial Intelligence, Machine Learning, Neural Networks, Deep Learning and Generative AI. GIS: GeoAI

    Geographical Analysis
        Some improvements from existing statistical methods
        Interesting QGIS GeoAI Plugin Jan 2026 and Review
    LLM / ChatGPT / assistant
        Kue Plugin: An AI Chatbot for QGIS, Feb 2025
        Using (any) chatbot for coding
        Posit AI in RStudio - subscription
        Generative AI Tools for Quantitative Research: A Practical Guide, David Bann and Liam Wright - PAYG Positron ClaudeGeoAI: But

    What are we using AI for?
    AI is a tool - how we use it is important
        To assist is great
        To help us learn is great
        To do boring work for is great
        To do complex work for us ?
        To learn for us?
    “Using AI to do learning for us is like someone helping you lift dumbbells in the gym - it’s not the way to build strength”
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Nick Bearman @nickbearman.bsky.social · 22/06/2026
Fantastic to hear Addresscloud is back as a sponsor again for FOSS4G:UK 2026!
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 22/06/2026
New article! Shreya Shukla & Tina Pujara complete a systematic review of how we cartographically represent emotions in urban design and planning doi.org/10.1080/1523... #GISchat
Figure 3: Link between the methods of emotion data collection and visualization techniques. The diagram displays three columns connected by arrows showing data flow. Left column 'Methods of Emotion Data Collection' is divided into three categories: Subjective (Map-based survey, Mental map/Sketch Map, Questionnaire), Crowdsourcing Subjective (Crowdsourcing Social media data), and Objective (Physiological sensors). Center column 'Data Type' shows intermediate processing stages: Data lines/segments, Sketches/Annotations, Geolocated Data points (with note 'Combined with GPS data'), and Continuous data values. Right column 'Visualization Techniques in Emotion Mapping' displays output maps: Line Map, Sketch Map, Emoji Map, Point Map, Pie-chart Map, and Peak Map. Additional processing step shows 'Data Aggregation' connecting Point Map and Pie-chart Map to Heat Map and Grid Map respectively. Dashed and solid arrows indicate direct and conditional connections between collection methods, data types, and visualization outputs.
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 18/06/2026
New article! Christos Kastrisios proposed a new side selective line simplification algorithm for use with nautical chart generalization doi.org/10.1080/1523... #GISchat #OpenAccess See the data at doi.org/10.6084/m9.f...
Figure 14: Representative sections from testbeds a) 6 (left), b) 4 (center), and c) 2 (right) showing removal of source-line intricacies and preservation of overall contour form by the side-selective algorithm. Each panel displays red contour lines on a white background, representing different results of line simplification processing. Panel a) shows contours with parallel linear features and some detailed intricacies. Panel b) displays a more centralized pattern with less peripheral detail. Panel c) exhibits scattered, dispersed contour segments. The three examples demonstrate varying degrees of how the algorithm handles the removal of fine-scale variations and noise from source contour data while maintaining the essential shape and spatial organization of the overall landform representation, making note of which side can be simplified.
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Nick Bearman @nickbearman.bsky.social · 16/06/2026
Great to hear Ordnance Survey are supporting #FOSS4G:UK 2026!
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Nick Bearman @nickbearman.bsky.social · 11/06/2026
What is GIS? Check out my free seminar on @instats.bsky.social What is GIS? on 8th July, 4pm UK time instats.org/seminar/what... Want to learn more? My #R #GIS courses coming up in Aug 2026: Intro to QGIS Advanced QGIS Intro to using R as a GIS Advanced R as a GIS nickbearman.com/training-cou...
A screenshot of a map created in R, showing Percentage population Ages 10 to 14 for Liverpool, UK.
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OSGeo:UK @uk.osgeo.org · 11/06/2026
FOSS4G:UK 2026’s AMA session starts in 24 hours! 🎉 Join OSGeo:UK team tomorrow (June 12th) at 12 PM for an open conversation about the conference, the programme, sponsorship, community involvement, and more. Bring your questions and chat with the team behind FOSS4G:UK 2026.
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OSGeo:UK @uk.osgeo.org · 10/06/2026
Learn more about them here: agi.org.uk Join us at FOSS4G:UK 2026 in Leeds on 12–13 October 2026: uk.osgeo.org/foss4guk2026 P.S. Learn more about the event at our upcoming AMA on June 12, afternoon: uk.osgeo.org/foss4guk2026/ama #FOSS4GUK #OSGeoUK #FOSS4G #AGI #Geospatial #GIS #OpenSource
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Nick Bearman @nickbearman.bsky.social · 10/06/2026
Looking forward to hearing more about what the AGI have been up to at #FOSS4GUK
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 09/06/2026
Check out the CaGIS Interview with Mahdi Nazari Ashani to hear all about running a SLM in a browser youtu.be/YZ-BFNHtwMo and checkout the full demo of AWebGIS at youtu.be/7-QYALy4F2E plus the CaGIS article for #free at doi.org/10.1080/1523... #GISchat
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Nick Bearman @nickbearman.bsky.social · 08/06/2026
Come and ask anything at our AMA on Friday! #FOSS4GUK
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OSGeo:UK @uk.osgeo.org · 08/06/2026
Learn more about them here: www.hotosm.org/en/ Join us at FOSS4G:UK 2026 in Leeds on 12–13 October 2026: uk.osgeo.org/foss4guk2026
hotosm.org
Home - HOT Website
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OSGeo:UK @uk.osgeo.org · 08/06/2026
...response, and resilience building around the world. Their mission is to ensure that open map data is available and used for impact, especially in places facing disaster, emergency, and multidimensional poverty.
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OSGeo:UK @uk.osgeo.org · 08/06/2026
We’re delighted to announce that Humanitarian OpenStreetMap Team (HOTOSM) is a Community Sponsor of FOSS4G:UK 2026! 🎉 HOTOSM is an international non-profit dedicated to improving lives through accurate, accessible geographic data and open mapping, supporting humanitarian action, disaster...
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 04/06/2026
New article! Fascinating article from Rui Xin and colleagues, looking at using AIS data to identify occupied anchor positions in ports, using a case study of Port of Los Angeles - Long Beach #GISchat doi.org/10.1080/1523... See their code at doi.org/10.6084/m9.f...
Variation of the average offset (movement due to weather and tides) at various time points for Long Beach. Darker red = more offset. 
Figure 18: Visualization of the average offset degree of occupied anchor positions from 2019 to 2023. Six maps of the Long Beach area arranged in a 2x3 grid show: a) combined five-year data (2019-2023), and b) 2019, c) 2020, d) 2021, e) 2022, f) 2023 individually. Anchor positions are displayed as circles colored on a heat scale from light pink/white (0, no offset) to dark red (1, maximum offset), indicating the average displacement of occupied anchors. Spatial clustering patterns are visible, with higher offset degrees (darker red) in southern zones during earlier years, decreasing toward 2023. Each map includes a north arrow and scale bar (0-2-4 km). Light blue/teal represents water and beige represents land.
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OSGeo:UK @uk.osgeo.org · 02/06/2026
We’re excited to announce an Ask Me Anything (AMA) session for FOSS4G:UK 2026! 🎉 Join us on 12th June at 12 PM for an open conversation about the conference, the programme, sponsorship, community involvement, and more. Bring your questions and come chat with the team behind FOSS4G:UK 2026.
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OSGeo:UK @uk.osgeo.org · 26/05/2026
Proud to announce CGI as a Bronze Sponsor of FOSS4G:UK 2026 in Leeds! CGI brings global expertise in geospatial, AI, cloud, data, and secure digital transformation. Join us 12–13 Oct 2026 at Horizon Leeds. More: cgi.com/uk/en-gb #FOSS4GUK #Geospatial #OpenSource
Bronze Sponsor graphic for CGI on a dark map-style background, with large “CGI” text in the center, a Foss4G UK Leeds 2026 logo at bottom left, the dates 12th–13th October at the bottom, and a QR code at bottom right.
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Nick Bearman @nickbearman.bsky.social · 21/05/2026
Want to learn how to use QGIS to visualise and analyze spatial data? My #Intro to #QGIS course is running on Tue 26th May *next week* and Mon 1st June - No prior knowledge needed! More details and sign-up: nickbearman.com/training-cou...
Students working on laptops creating maps.A screenshot of QGIS showing a world map in green.
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 20/05/2026
New article! Xini Hu and colleagues look at how we can create a map color style design to enhance the emotional expressiveness of maps #GISchat doi.org/10.1080/1523...
Figure 7: Sample cases of emotional color style design results for ordinary maps. Six panels labeled a) through f) display partial Chengdu city vector maps styled with different emotional color palettes. Each panel shows a small reference image (left) with an arrow pointing to the resulting styled map (right). Panel a) 'original' shows the standard map with typical cartographic colors. Panel b) 'calm' uses muted beiges and soft colors. Panel c) 'happy' features bright teals, greens, and warm tones. Panel d) 'nostalgic' employs sepia and brown tones. Panel e) 'fear' uses dark blues and purples creating an ominous atmosphere. Panel f) 'depressed' applies desaturated grays and muted colors. Each map includes a legend identifying features: river, forest, residential, industrial, commercial, main road, subsidiary road, ordinary road, railway, and background. The maps show the same geographic area with consistent road networks and blue river running through, demonstrating how color choices alone can evoke different emotional responses.
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Nick Bearman @nickbearman.bsky.social · 19/05/2026
Want to learn how to use QGIS to visualise and analyze spatial data? My #Intro to #QGIS course is running 26th May and 1st June *New Dates!* No prior knowledge needed! nickbearman.com/training-cou...
A screenshot of QGIS showing a world map in green.Screenshot of a Zoom window with participants.
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The Cartography and Geographic Information Society @carto-giscience.bsky.social · 18/05/2026
New article! How can we calculate off-road trafficability? Renan Fabres Dalmonech and colleagues use multicriteria decision analysis to develop a robust spatial model #GISchat doi.org/10.1080/1523...
Figure 6: Vehicle trafficability map for a conventional vehicle with tires, showing a) a continuous scale ranging from 0 to 10 and b) a categorical scale with classes from adequate to impeditive, according to Jenks natural breaks. Both maps display the same geographic area with coordinate labels (27.92°S to 28.06°S latitude, 49.44°W to 49.36°W longitude). Map a) uses a continuous color gradient from light orange/beige (low trafficability, 0) to dark brown/red (high trafficability, 10) as shown in the Index of Trafficability (IT) legend. Map b) applies five distinct color categories: green (Adequate), light green (Slightly restrictive), yellow (Restrictive), orange (Very restrictive), and red (Impeditive). The right panel includes a legend with both classification systems, a north arrow, scale bar showing 0-5-10 km at 1:10,000 scale, and datum information (Horizontal Datum SIRGAS2000 Epoch 2000.4, UTM Zone 22S). The terrain appears highly variable with complex patterns of trafficability throughout.
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