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carto-giscience.bsky.social
The Cartography and Geographic Information Society
@carto-giscience.bsky.social
68 followers 68 following 77 posts
The Cartography and Geographic Information Society supports research, education, and practice to improve the understanding, creation, analysis, and use of maps and geographic information to support effective decision-making and improve the quality of life.
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carto-giscience.bsky.social
New article! Using storytelling and guided interactions to help users understand large spatial and temporal data sets. Oana Candit et al. provide an example representing active fires of 2023 Paper: doi.org/10.1080/1523... App: www.animation.oanacanditmaps.ro/app/ #GISchat
A screenshot from the app, showing a series of yellow and orange cones (each one representing fire intensity (colour) and fire frequency (width and height) along text saying "Fires are being fueled by dry conditions and strong winds".
December 8, 2025 at 4:30 PM
carto-giscience.bsky.social
New paper! Thomas Depian et al. investigate transitions in dynamic point labelling which are an issue in dynamic mapping systems. Weather data in Vienna - the labels change and it is not obvious which have changed doi.org/10.1080/1523... #GISchat #OpenAccess doi.org/10.17605/OSF...
Figure 1. Two labelings of the weather situation in Vienna at different timestamps: 23 labels appear, 26 disappear, and 11 change their position. The labelings are computed by our prototype that we describe in Section 4. Label-Icons: © GeoSphere Austria. Note that a full visual scan of the individual labels is necessary to identify all changes (Rensink et al., 1997).
December 3, 2025 at 3:59 PM
carto-giscience.bsky.social
New article! Timofey Samsonov explores animated transitions proportional symbol and choropleth representations on thematic maps #GISchat #ICC2023 doi.org/10.1080/1523... Check out the supplementary videos of each transition at zenodo.org/records/1717... and see it in practice at observablehq.com
Figure 2: A series of 6 maps, showing transition from proportional symbols (circles) for each area within the map to a choropleth map where the color shows the value. Labelled t=0 to t=1.
December 2, 2025 at 11:57 AM
carto-giscience.bsky.social
We all know color in maps is important. Shangjing Jiang and colleagues used crowdsourced photographs to create place-aware colored maps which help create a sense of place doi.org/10.1080/1523... #GISchat Figure 1 below shows their comparisons: Google Maps, Snazzy Maps "Hopper" and place-aware maps
Three of the maps used in the evaluation, on the left a Google Maps style map (relatively plain colouring, with green for parks, blue for water and shades of grey and light brown for everywhere else), in the middle a Snazzy Maps - Hopper style map, with darker colors across the board, dark green for parks, dark blue for water, light green for gardens/ greenspace and grey for buildings, and on the right, the Place-aware Map, with much more vibrant colours.
December 1, 2025 at 11:51 AM
carto-giscience.bsky.social
At a festival with events happening over a week and over a whole city? Dilara Bozkurt explores temporal navigation for festival maps on mobile devices, working out how to incorporate space and time on a small screen like a mobile phone doi.org/10.1080/1523... #GISchat #OpenAccess Check out the GIF:
November 27, 2025 at 3:02 PM
carto-giscience.bsky.social
New article! Where are GIScience faculty hired from? Yanbing Chen and colleagues, using data from GISphere, analyze faculty mobility and research themes through hiring networks #GISchat doi.org/10.1080/1523... Below: where current GIS faculty are (x-axis) and where they got their PhDs (y-axis).
Figure 7. Marimekko chart visualizing the distribution of GIS faculty placements across four continents (North America, Asia, Europe, and Oceania) and their PhD origins. The X-axis represents the total number of current GIS faculty in each continent, while the Y-axis shows the percentage of faculty based on where they obtained their Ph.Ds. The width of each segment on the X-axis corresponds to the number of GIS faculty in that continent, and the colored segments represent the proportion of faculty whose PhD origins are from different continents. For example, a total of 345 GIS faculty members are currently affiliated with institutions in North America. Of these, 89.0% obtained their PhDs in North America, 7.8% in Europe, 2.0% in Asia, 0.9% in Oceania, and 0.3% in Africa.
November 25, 2025 at 11:55 AM
carto-giscience.bsky.social
Fantastic article on Georeferencing historical maps using automated processes, including local feature matching and Delaunay consistency from Beatrice Vaienti, Isabella di Lenardo and Frédéric Kaplan doi.org/10.1080/1523... #GISchat #OpenAccess
Figure 1, a sample of the 113 maps of Jerusalem used in this study. Figure 19, a series of 113 rectangles plotted on top of an OpenStreetMap basemap, showing the coverage of historical maps of Jerusalem.
November 24, 2025 at 4:50 PM
carto-giscience.bsky.social
New paper from Hong Wang, Mingda Zhang and colleagues: Evaluating color preference in thematic maps, a case study from China doi.org/10.1080/1523... #GISchat See below, figure 12: The true and predicted values of a selection of maps, with higher values for better maps.
A series of 6 maps with different color selections, with scores ranging from 2.10 to 4.00 (out of 5) with true value (scored by a survey) and predicted value (predicted by a color preference evaluation model)
November 20, 2025 at 3:13 PM
carto-giscience.bsky.social
How to design a campus cultural landscape map? Tao Zou and colleagues designed a map and then explored the user experience of the map doi.org/10.1080/1523... #GISchat Check out their map below, and the full res version at figshare.com/articles/dat...
A map of a campus university in China, with interesting elements picked out.
November 19, 2025 at 4:37 PM
carto-giscience.bsky.social
Deepfake geography: A new paper from Valentin Meo looking at how we can detect manipulated satellite images doi.org/10.1080/1523... Also check out our interview on the paper with Valentin and @nickbearman.bsky.social: youtu.be/DklnevrHR1c #GISchat #FreeAccess
Figure 4. Examples of deepfakes generated with PatchMatch. Real image (left, small) and the deepfake (big, right) produced by PatchMatch for urban areas. The real image includes a red house, which is removed in the fake image, replaced by green lawn.
November 17, 2025 at 2:30 PM
carto-giscience.bsky.social
Lastly, Eric Delmelle is stepping down as Editor-in-Chief with Angela Yao stepping up to take his place - thank you Eric and Angela. And finally, thank you to our amazing 215 reviewers who help us make the journal what it is. doi.org/10.1080/1523...
November 12, 2025 at 11:07 AM
carto-giscience.bsky.social
Fantastic new article looking at whether schematic maps (e.g. the London Tube map) can help with pedestrian route planning, from Ruyu Dai and colleagues, #GISchat doi.org/10.1080/1523...
Fantastic new article looking at whether schematic maps (e.g. the London Tube map) can help with pedestrian route planning, from Ruyu Dai and colleagues, #GISchat https://doi.org/10.1080/15230406.2025.2478186
November 12, 2025 at 11:05 AM
carto-giscience.bsky.social
Taisheng Chen, Kun Hu et al. present a new way to automatically enhance qualitative color schemes for color vision deficiency, doi.org/10.1080/1523... #GISchat
Four maps (metro map above, land cover map below, original left and enhanced right) with fixation heatmaps overlaid on top. The fixations show consistent areas being observed.
November 12, 2025 at 11:04 AM
carto-giscience.bsky.social
Great new article from Julian Keil and colleagues, looking at the landmark attraction effect, where locations are memorized closer to prominent landmarks than they actually are. The symbol used also has an impact on this. doi.org/10.1080/1523... #GISchat #OpenAccess
The different impact of different types of symbols.
November 12, 2025 at 11:04 AM
carto-giscience.bsky.social
Issue 52-6 of Cartography and Geographic Information Science is now available!

We have 8 papers, inc. navigation, symbology, schematic representations of roads maps, labelling, Swiss style relief shading maps and a thank you to our reviewers!

www.tandfonline.com/toc/tcag20/5... #GISchat
Front cover of Cartography and Geographic Information Science journal, volume 52 no 6 from November 2025.
November 12, 2025 at 11:03 AM
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
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
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
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
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
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
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
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
carto-giscience.bsky.social
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
An example of the spatial interaction model, with interactions between two regions (origin area and destination area) and within each area.
September 24, 2025 at 2:10 PM
carto-giscience.bsky.social
New Paper! Yuanfang Chen and colleagues present a new way of contact-tracing, the PSTP-STRA method doi.org/10.1080/1523... #GISchat
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.
September 18, 2025 at 2:05 PM