Nick Bearman
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nickbearman.bsky.social
Nick Bearman
@nickbearman.bsky.social
61 followers 57 following 17 posts
GIS Trainer & Consultant; now also at http://fosstodon.org/@nickbearman, Cartographic Editor @carto-giscience.bsky.social‬; cartography, open data, QGIS, R, http://linktr.ee/nickbearman
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Reposted by Nick Bearman
uk.osgeo.org
Do you have an open source geo project that could make a difference in the UK? We’ve got £6,000 to share between £500–£1000 projects! Submit your idea by 30 Nov 2025 to osgeouk@gmail.com
💵🌍 #foss4guk #OpenSource #foss4g #gischat
November 7, 2025 at 7:16 PM
nickbearman.bsky.social
🗺️ Want to learn how to visualise and analyze spatial data in the social sciences and build your #GIS skills?
Unlock powerful new ways to understand our world
Courses start Next Week! Intro R, Advanced R, Spatial Stats R
nickbearman.com/training-cou...
#GIS #SocialScience #Research #DataViz
November 6, 2025 at 3:51 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
New article! Darlan Miranda Nunes & Silvana Philippi Camboim investigate Collaborative toponyms in OpenStreetMap evaluating the potential to complement and update National Mapping Agencies data, doi.org/10.1080/1523... also see their code and process at github.com/darlanmnunes...
#GISchat
A grid of six choropleth maps comparing OpenStreetMap toponym coverage across two Brazilian cities (Água Verde in Paraná and Passaré in Ceará) and three data categories (Leisure, Building, and Amenity). Each map uses equal interval classification showing the proportion of OSM toponyms in grid cells, with a legend indicating: 0-25% (cream/white), 25-50% (light green), 50-75% (medium green), and 75-100% (dark green). Água Verde shows more dispersed coverage with darker concentrations in the top row (Leisure) and bottom row (Amenity), while Passaré shows sparser overall coverage with notable clustering in the Amenity category. The Building row shows minimal to no coverage for both cities, appearing almost entirely cream-colored. Figure 5 caption reads: 'Choropleth maps based on the equal interval classification of OSM toponyms by tag in the study areas.'
November 5, 2025 at 3:03 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
New paper! Fascinating discussion of Optimizing electric vehicle supply equipment allocation using a range of local and global MCDA methods by Emily Zhou & Junyi Yang, #GISchat doi.org/10.1080/1523...
Figure showing four neighborhood clusters in Philadelphia derived from spectral clustering. Panel a displays a map with colored squares representing four clusters: Cluster 1 (dark blue) concentrated in center city and some northern areas, Cluster 2 (olive green) in northwest sections, Cluster 3 (light green) in northeast regions, and Cluster 4 (teal) spanning south and southwest Philadelphia. Panels b)-d) show density distribution curves for each cluster: panel b) shows driving age population with two peaks, panel c) displays EV registration levels with multiple peaks at lower values, and panel d) illustrates distance to nearest electric vehicle supply equipment (EVSE) with highest density at shorter distances tapering off toward 1.00.
November 4, 2025 at 3:06 PM
nickbearman.bsky.social
🗺️ Want to learn how to visualise and analyze spatial data in the social sciences and build your #GIS skills?
Unlock powerful new ways to understand our world
Courses in Nov 2025 @InstatsS Intro R, Advanced R, Spatial Stats R
nickbearman.com/training-cou...
#GIS #SocialScience #Research #DataViz
Student working on a tablet computer making a map. A screenshot of a map created in R, showing Percentage population Ages 10 to 14 for Liverpool, UK.
November 4, 2025 at 12:49 PM
Reposted by Nick Bearman
foss4gna.bsky.social
#FOSS4GNA isn’t just talks - don’t miss the B2B networking, the Geo-Career Expo + Ice Cream Social, and the Hootenanny. Come for the content, stay for the community.
FOSS4G North America
Join us at the FOSS4G NA Conference. Discover the latest in Free and Open Source Software for Geospatial communities. Network, learn, and innovate with industry leaders and enthusiasts. Don't miss out on shaping the future of geospatial technology!
www.foss4gna.org
October 30, 2025 at 6:00 PM
nickbearman.bsky.social
Want to learn how to visualise and analyze spatial data in the social sciences and build your #GIS skills? Last chance to sign up for my Intro QGIS course starting tomorrow with InStats instats.org/seminar/intr... Or check out my Advanced QGIS course starting next week: instats.org/seminar/adva...
October 20, 2025 at 3:55 PM
Reposted by Nick Bearman
brenttoderian.bsky.social
“Now Scientific American has updated and re-released what it calls the “classic graphic” that shows that a human on a bicycle—able to coast, or freewheel, without pedaling—remains the world’s most energy effecient traveler.” @carltonreid.com on the re-release of the iconic graph in @forbes.com.
Heat map of travel efficiency, updated
October 17, 2025 at 12:52 PM
Reposted by Nick Bearman
astrokatie.com
I feel like stuff like this is too often overlooked in discussions around technology-based mitigations of climate change. If we use tech innovations to make it easy and convenient for people to use the “greener” alternative that already exists, they’ll use it.
October 17, 2025 at 7:54 AM
Reposted by Nick Bearman
astrokatie.com
Living in the Future benefit: the combination of Google Maps public transit directions and phone-tap onboard payment makes it SO EASY to take public trams/buses/metros when traveling now. It’s fantastic not to have to resort to taxis just for lack of easy access to the local transit ticketing system
October 17, 2025 at 7:44 AM
Reposted by Nick Bearman
geocommunity.bsky.social
We are pleased to release the programme for our AGI Greater Manchester Network Event

📅Thursday 23 October
🕘 15:00-17:00
📍 Jacobs' offices Central Manchester
Read more and register🔗https://bit.ly/3IM4b20
October 17, 2025 at 8:56 AM
Reposted by Nick Bearman
uk.osgeo.org
We have now uploaded all the recorded sessions from #FOSS4GUK 2025 in Leeds. 📹🦉

We would now invite everyone else to our youtube channel if you would like to catch up on the 35 recorded session.

www.youtube.com/watch?v=qCKv...
Welcome to FOSS4G:UK 2025
YouTube video by FOSS4G:UK
www.youtube.com
October 17, 2025 at 4:05 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
Fantastic new article from Lars De Sloover and colleagues from Department of Ggeography Ugent comparing impacts of Euclidean distance and dynamic time warping with spatiotemporal analysis of COVID-19 dynamics across Europe #GISchat doi.org/10.1080/1523...
Heatmap dendrograms visualizing the pairwise distance matrices and hierarchical clustering results for the dynamic time warping (DTW) distance. Maps for the different cluster scenarios (2 to 7) based on the dynamic time warping (DTW) distance.
October 16, 2025 at 4:33 PM
nickbearman.bsky.social
Want to learn how to visualise and analyze spatial data in the social sciences and build your #GIS skills? My Intro QGIS and Advanced GIS courses are coming up, starting next week, with @instats instats.org/seminar/intr... instats.org/seminar/adva... nickbearman.github.io/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) overlayed with green space (green). A screenshot of QGIS showing a world map in green.
October 14, 2025 at 2:04 PM
Reposted by Nick Bearman
cl10.bsky.social
Hi data people, check out Exploropleth! exploropleth.github.io/exploropleth/. It's free, open source software that shows how binning methods affect maps. There's also a teaching worksheet and a journal article in CaGIS: exploropleth.github.io
@arpitnarechania.bsky.social &
@alexendert.bsky.social
Different maps that show life expectancy by county in the U.S., where the data is divided using different data binning methods. Box plot style graphics show data points for adult percent obesity by county in the U.S.
October 13, 2025 at 4:00 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
New article! A fantastic new tool Exploropleth: exploratory analysis of data binning methods in choropleth maps, from @arpitnarechania.bsky.social Alex Endert & Clio Andris doi.org/10.1080/1523... #GISchat website exploropleth.github.io video of the tool in action: www.youtube.com/watch?v=lNV8...
Figure 5. Combine View lets users analyze a) a combination of one or more binning methods by visualizing b) the most consistent Bin, c) the frequency of the most consistent Bin, and d) both together for each U.S. county in separate choropleths. The new, resiliency binning method then utilizes this information to g) determine “resilient” bins (counts, intervals) that are also visualized in a choropleth. Hovering any county on the map shows a tooltip with relevant information about the county, as shown in e) and f).
October 13, 2025 at 4:08 PM
Reposted by Nick Bearman
MapLayNet can learn a concept hierarchy of map layout via an unsupervised data similarity measure. The resulting layout embedding can be further explored for more cartographic tasks.
carto-giscience.bsky.social The Cartography and Geographic Information Society @carto-giscience.bsky.social · Aug 26
New paper from Jian Yang and colleagues, presenting MapLayNet, a way of understanding maps as a graph and classifying how they are laid out, with the aim of better map layout retrieval and design recommendation #GISchat #OpenAccess doi.org/10.1080/1523...
Figure 1 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. Figure 10 Machine learning visualization showing how AI clusters similar map elements together. Each dot represents a different map and are grouped together in 2D space according to their layout. The algorithm successfully identifies layout patterns across different map types! #MachineLearning #Cartography
October 10, 2025 at 3:09 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
Great new article! Victor Irekponor & Taylor M. Oshan
address reproducibility in spatially varying coefficient (SVC) models, and introduce svc-viz, a open source Python tool to-do this #GISchat doi.org/10.1080/1523... github.com/marquisvicto...
A three-panel visualization showing bandwidth selection and spatial analysis for local intercept estimation. The top panel displays an AICc curve starting around 2000 at spatial unit 0, dipping to a minimum near bandwidth 220 (marked by a green vertical line), with an orange dashed line indicating another reference point, then rising steadily to about 5000 at spatial unit 3000. The middle panel shows a choropleth map of the contiguous United States with counties colored on a diverging red-to-blue scale, where darker red regions (values around -2) appear concentrated in the Southwest, particularly Texas and surrounding areas, lighter colors (near 0) cover much of the central and eastern US, and blue regions (positive values up to 4) appear in the Pacific Northwest and parts of the Northeast. The bottom panel presents a caterpillar plot showing coefficient estimates with confidence intervals across approximately 3000 spatial units, displayed as vertical bars in gray and colored segments (red for negative, blue for positive values), with most estimates clustering near zero but showing notable variation and wider intervals toward the right side of the plot.
October 9, 2025 at 2:36 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
New article! Fascinating new method of reconstructing maritime route networks for nearshore waters, using step-by-step density-based clustering from Jiale Pan and colleagues doi.org/10.1080/1523...
Figure 10 (left) showing ship channels for cargo, within the Great Lakes and Figure 11 (right) showing routes within those channels.
October 8, 2025 at 2:49 PM
nickbearman.bsky.social
🗺️ 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! Tue 7th 1pm (UK/Ldn) Sign up at instats.org/seminar/what...
Students working on laptops creating maps. Screenshot of a Zoom window with participants.
October 6, 2025 at 11:08 AM
nickbearman.bsky.social
I’ve just returned from a fantastic 2 days in Leeds for FOSS4G:UK 2025. FOSS4G is an amazing group, and I am so proud to be part of the Local Organising Committee. We were in the great venue Horizon Leeds, with two days of workshops and talks.
nickbearman.com/blog/2025-10...
October 6, 2025 at 10:50 AM
Reposted by Nick Bearman
stevenfeldman.bsky.social
Wishing all my friends at @uk.osgeo.org #foss4guk in Leeds a great conference
September 30, 2025 at 5:14 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
Great new article from Michala A. Garrison, Schyler A. Reis, Shiyu Zhang and Carolyn S. Fish, evaluating “narrative transportation” – how engrossed one becomes in a story when used in storytelling maps, and the impact of including maps and photos doi.org/10.1080/1523... #GISchat
Alternative options in the survey, including low or high narrative text, and the addition of maps and photos.
September 29, 2025 at 3:28 PM
Reposted by Nick Bearman
carto-giscience.bsky.social
New paper from Yunfei Ma, Yuan Zhang and colleagues, Where is Huaqiangbei? looking at how Huaqiangbei, one of Shenzhen’s largest business districts, has evolved over time doi.org/10.1080/1523...
#GISchat
A map showing the current footprint of Huaqiangbei (left) along with a breakdown of the categories of shops from 2018 to 2020.
September 29, 2025 at 1:45 PM
nickbearman.bsky.social
🗺️ FREE GIS seminar for researchers! Learn about GIS, spatial data analysis, visualization & software tools. Perfect for PhD students, researchers & academics looking to add a spatial dimension to their work! 7th Oct, 1pm (UK/London) Sign up at instats.org/seminar/what... @instats.bsky.social
September 29, 2025 at 12:29 PM