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Nick Bearman

@nickbearman.bsky.social

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

59 Followers  |  53 Following  |  15 Posts  |  Joined: 16.04.2025  |  1.9108

Latest posts by nickbearman.bsky.social on Bluesky

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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!

#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.

30.10.2025 18:00 — 👍 1    🔁 1    💬 0    📌 0
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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...

20.10.2025 15:54 — 👍 1    🔁 1    💬 0    📌 0
Heat map of travel efficiency, updated

Heat map of travel efficiency, updated

“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.

17.10.2025 12:51 — 👍 659    🔁 204    💬 28    📌 34

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.

17.10.2025 07:54 — 👍 608    🔁 40    💬 18    📌 1

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

17.10.2025 07:43 — 👍 1151    🔁 99    💬 31    📌 16
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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

17.10.2025 08:56 — 👍 0    🔁 1    💬 0    📌 0
Welcome to FOSS4G:UK 2025
YouTube video by FOSS4G:UK Welcome to FOSS4G:UK 2025

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...

17.10.2025 16:05 — 👍 3    🔁 5    💬 0    📌 0
Heatmap dendrograms visualizing the pairwise distance matrices and hierarchical clustering results for the dynamic time warping (DTW) distance.

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.

Maps for the different cluster scenarios (2 to 7) based on the dynamic time warping (DTW) distance.

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...

16.10.2025 16:33 — 👍 3    🔁 1    💬 0    📌 0
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 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.

A screenshot of QGIS showing a world map in green.

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

14.10.2025 14:04 — 👍 2    🔁 0    💬 0    📌 0
Different maps that show life expectancy by county in the U.S., where the data is divided using different data binning methods.

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.

Box plot style graphics show data points for adult percent obesity by county in the U.S.

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

13.10.2025 16:00 — 👍 5    🔁 3    💬 1    📌 1
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).

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).

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...

13.10.2025 16:08 — 👍 12    🔁 4    💬 0    📌 1

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.

10.10.2025 15:09 — 👍 5    🔁 2    💬 0    📌 0
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.

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.

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...

09.10.2025 14:36 — 👍 2    🔁 1    💬 0    📌 0
Figure 10 (left) showing ship channels for cargo, within the Great Lakes and Figure 11 (right) showing routes within those channels.

Figure 10 (left) showing ship channels for cargo, within the Great Lakes and Figure 11 (right) showing routes within those channels.

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...

08.10.2025 14:49 — 👍 3    🔁 1    💬 0    📌 0
Students working on laptops creating maps.

Students working on laptops creating maps.

Screenshot of a Zoom window with participants.

Screenshot of a Zoom window with participants.

🗺️ 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...

06.10.2025 11:08 — 👍 0    🔁 0    💬 0    📌 0
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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...

06.10.2025 10:50 — 👍 4    🔁 1    💬 0    📌 0

Wishing all my friends at @uk.osgeo.org #foss4guk in Leeds a great conference

30.09.2025 17:14 — 👍 6    🔁 3    💬 1    📌 0
Alternative options in the survey, including low or high narrative text, and the addition of maps and photos.

Alternative options in the survey, including low or high narrative text, and the addition of maps and photos.

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

29.09.2025 15:28 — 👍 4    🔁 1    💬 0    📌 0
A map showing the current footprint of Huaqiangbei (left) along with a breakdown of the categories of shops from 2018 to 2020.

A map showing the current footprint of Huaqiangbei (left) along with a breakdown of the categories of shops from 2018 to 2020.

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

29.09.2025 13:45 — 👍 4    🔁 1    💬 0    📌 0
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🗺️ 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

29.09.2025 12:29 — 👍 0    🔁 0    💬 0    📌 0
Students working on laptops creating maps.

Students working on laptops creating maps.

A screenshot of QGIS showing a world map in green.

A screenshot of QGIS showing a world map in green.

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 Oct-Nov 2025:
What is GIS? A FREE GIS seminar for researchers!
Intro to QGIS & Advanced QGIS
Intro to R & Advanced R
nickbearman.github.io/training-cou...

24.09.2025 15:18 — 👍 2    🔁 0    💬 0    📌 0
An example of the spatial interaction model, with interactions between two regions (origin area and destination area) and within each area.

An example of the spatial interaction model, with interactions between two regions (origin area and destination area) and within each area.

New paper! Marjan Ghanbari, Mohammad Karimi and colleagues analyse intra-city function regions using spatial analysis interaction, using a case study of Chicago, doi.org/10.1080/1523... #GISchat

24.09.2025 14:10 — 👍 2    🔁 1    💬 0    📌 0
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This is the final regsitration call for #FOSS4GUK in Leeds on 1st and 2nd October. 🚨🚨

We have about 20 tickets left. Day tickets are also available. 🎟️🎟️🎟️

uk.osgeo.org/foss4guk2025...

We close registration 21st Sept and we really would like you to meet all of our amazing sponsors in Leeds.

19.09.2025 13:41 — 👍 3    🔁 2    💬 0    📌 0
This map shows spatiotemporal risk values for two villages (Xiaoguo village and Liujia Zuo village) as of January 6, 2021. The risk values are displayed using a color-coded legend ranging from 0 (white) to 6-24 (red), with intermediate categories of 0-2 (light gray), 2-4 (light blue), and 4-6 (orange).

The map displays various geometric shapes and structures scattered across the area, with the highest risk concentrations (shown in red and orange) appearing to be concentrated around the central area between the two villages. Lower risk areas are shown in lighter colors.

This map shows spatiotemporal risk values for two villages (Xiaoguo village and Liujia Zuo village) as of January 6, 2021. The risk values are displayed using a color-coded legend ranging from 0 (white) to 6-24 (red), with intermediate categories of 0-2 (light gray), 2-4 (light blue), and 4-6 (orange). The map displays various geometric shapes and structures scattered across the area, with the highest risk concentrations (shown in red and orange) appearing to be concentrated around the central area between the two villages. Lower risk areas are shown in lighter colors.

New Paper! Yuanfang Chen and colleagues present a new way of contact-tracing, the PSTP-STRA method doi.org/10.1080/1523... #GISchat

18.09.2025 14:05 — 👍 3    🔁 1    💬 0    📌 0
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Great discussions at #SDSL2025 about integrating #SpatialDataScience libraries in desktop and cloud environments, featuring @movingpandas , @qgis #Trajectools and the @carto Trajectory Analytics extension from the @emeraldseu project

18.09.2025 12:45 — 👍 7    🔁 4    💬 0    📌 0
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PostGIS Day | November 20 Learn how others are making use of PostGIS, pick up some tips and tricks, and share stories about bringing this excellent tool into your organizations.

@pwramsey.bsky.social and I are hosting PostGIS Day again this year! The call for papers and registration is open now. Join us!

www.snowflake.com/postgis-day-...

17.09.2025 14:07 — 👍 7    🔁 5    💬 0    📌 0
Students working on laptops creating maps.

Students working on laptops creating maps.

A screenshot of QGIS showing a world map in green.

A screenshot of QGIS showing a world map in green.

🗺️ FREE GIS seminar for researchers! 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! 7th Oct, 1pm (UK/London) Sign up at instats.org/seminar/what...

17.09.2025 13:18 — 👍 0    🔁 0    💬 0    📌 0
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A World of Tides The most recent issue of ArcUser, a magazine for Esri GIS software users spotlights cartographer Dave Taylor’s striking Oceanic Oscillations map.

A lovely ocean tides map using the Spilhaus projection for some Wednesday mappy goodness #MapoftheWeek mapoftheweek.substack.com/p/a-world-of...

17.09.2025 10:46 — 👍 62    🔁 17    💬 0    📌 0
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Helping to make standards fun and useful join Jo Cook at FOSS4G:UK 2025 in Leeds on the 1-2 October

Read more and register your place🔗https://bit.ly/3SWe9PI

11.09.2025 09:15 — 👍 3    🔁 1    💬 0    📌 0
A goat wearing a GPS collar

A goat wearing a GPS collar

A map showing goat ranges, overlaid on a 250 buffer of mining sites

A map showing goat ranges, overlaid on a 250 buffer of mining sites

Fantastic paper from Yan Lin and colleagues, Practicing community-based research in GIScience, using GIS with an Indigenous community, presenting a case study on environmental health concerns related to mining legacies in the U.S., using goats wearing GPS collars #GISchat doi.org/10.1080/1523...

04.09.2025 15:43 — 👍 1    🔁 1    💬 0    📌 0

@nickbearman is following 20 prominent accounts