The 1st ACM SIGSPATIAL International Workshop on Human-Centered Geospatial Computing (GeoHCC)

Logo

About

Rapid advances in geospatial computing technologies, including GeoAI, large-scale data infrastructures, multimodal sensing, and large models, are reshaping how we model, visualize, and engage with geographic phenomena. While these innovations are powerful, the role of humans remains pivotal—they set the goals, implement and steer these technologies, make critical decisions, and are themselves the very subjects these systems are designed to serve.

Human-Centered Geospatial Computing seeks to ensure that such technologies align with human needs and values as well as amplify and augment human abilities while preserving their control in order to make the system more productive, enjoyable, and fair. Specifically, it focuses on fostering interactive collaboration through human feedback, boosting human abilities in spatial reasoning, creative expression, and decision-making, and supporting a deeper understanding of human experiences in space. At the same time, it demands careful attention to ethical concerns, including privacy, bias, transparency, and trustworthiness, to ensure that the developed system is both powerful and responsible.

Program


Monday, November 3rd | Location: Room Think 2
Start End Session / Presentation
14:00 15:00 Keynote Talk by Prof. Ying Song "Modeling Movement, Understanding People: Toward Human-Centered Geospatial Computing for Sustainable Mobility and Accessibility"

Prof. Ying Song

Prof. Ying Song is an Associate Professor in Geography, Environment & Society at the University of Minnesota. Her research and teaching focus on Geographical Information Science (GIScience), with an emphasis on integrating space and time in geospatial analysis and modeling. Her empirical work centers on human mobility and accessibility in urban environments, and she is also interested in multi-modal transportation planning, public health, and ecological applications.
15:00 15:18 Max Gadomski and Auriol Degbelo. MEC: Towards Semi-Automated Map Experiment Creation
15:18 15:36 Jiyoon Pyo, Yuankun Jiao, Yao-Yi Chiang and Michael Corey. Augmenting Human-Centered Racial Covenant Detection and Georeferencing with Plug-and-Play NLP Pipelines
15:36 16:00 Coffee Break
16:00 16:18 Jina Kim, Leeje Jang, Yao-Yi Chiang, Guanyu Wang and Michelle Pasco. StreetLens: Enabling Human-Centered AI Agents for Neighborhood Assessment from Street View Imagery
16:18 16:36 Tarlan Bahadori, Alvin Chiu, Ahmed Eldawy and Michael Goodrich. Circle Quasi-Cartograms: Dorling Cartograms with Edge Connections and Relaxed Overlap Conditions
16:36 16:54 Ziyi Liu, Sidi Wu and Lorenz Hurni. Geospatial Question Answering on Historical Maps Using Spatio-Temporal Knowledge Graphs and Large Language Models
16:54 17:12 Hilman Prakoso and Ed Manley. A Cloud-Native Architecture for Web Mapping Visualisation While Protecting Sensitive Geospatial Data: A Case Study on Adherence Rate to Speed Limits in British Cities

Call For Papers

The workshop seeks high-quality short papers of up to 4 pages (not including references) that have not been published in other academic outlets and are not concurrently under peer review. Once accepted, at least one author is required to register for the workshop and the ACM SIGSPATIAL conference, as well as attend the workshop to present the accepted work which will then appear in the ACM Digital Library. As GeoHCC papers appear in the ACM SIGSPATIAL proceedings we follow the same submission process.

Topics (but not limited to)
  • Building computing systems to support spatial understanding, reasoning, and decision-making
  • Designing human-in-the-loop computing system to incorporate human knowledge and feedback in the workflow
  • Designing creative and participatory systems that foster human creativity in map-making, spatial design, and geovisualization
  • Modeling and understanding human perceptions of built and natural environments
  • Measuring emotions, sentiments, and experiences across places and spatial scales
  • Investigating human spatial cognition and place-based reasoning across different geographic contexts
  • Identifying and mitigating biases and risks in human-centered geospatial computing models and workflows
  • Protecting human privacy in the geospatial computing workflows
  • Developing interpretable and trustworthy models for users and decision-makers
  • Applying geospatial computing to address societal challenges in public health, disaster response, climate resilience, housing, transportation, etc.

Paper Format
Accepted GeoHCC'25 papers will appear in the ACM SIGSPATIAL'25 Proceedings. Therefore, we follow the same formatting requirements as ACM SIGSPATIAL'25 which can be found at https://sigspatial2025.sigspatial.org/ Manuscripts should be submitted in PDF format and formatted using the ACM camera-ready templates available at https://www.acm.org/publications/proceedings-template SIGSPATIAL uses the Conference Proceedings Primary Article template with two-column format. Alterations to the template, especially to gain more space, will be grounds for administrative rejection without further technical review. Submissions to ACM SIGSPATIAL are single-blind -- i.e., the names and affiliations of the authors should be listed in the submitted version. The author list is considered to be final after the submission deadline and no changes to the author list are allowed for accepted papers.

Important Dates

Organizers

Workshop Chairs

Sidi Wu, Institute of Cartography and Geoinformation, ETH Zurich

Yizi Chen, Institute of Cartography and Geoinformation, ETH Zurich

Jiaxin Feng, Department of Geography, Dartmouth College

Jina Kim, Department of Computer Science and Engineering, University of Minnesota

Yao-Yi Chiang, Department of Computer Science and Engineering, University of Minnesota


Program Committee Co-Chairs

Yizi Chen, Institute of Cartography and Geoinformation, ETH Zurich

Yijun Lin, Department of Computer Science and Engineering, University of Minnesota


Program Committee

Peter Kiefer, Institute of Cartography and Geoinformation, ETH Zurich

Yuhao Kang, Department of Geography & the Environment, The University of Texas at Austin

Haosheng Huang, GeoAI and Cartography, University of Ghent

Ross Purves, Department of Geography, University of Zurich

Yanan Xin, Department of Transport and Planning, TU Delft

Pei-Yu Wu, Interactive Visualization & Intelligence Augmentation Lab, ETH Zurich

Hongyu Zhang, University of Massachusetts Amherst

Kee Moon Jang, Sensable City Lab, MIT

Jinmeng Rao, Google DeepMind

Shi-Lung Shaw, Geography and Sustainability Department, University of Tennessee

Grant McKenzie, Department of Geography, McGill University

Junghwan Kim, Department of Geography, Virginia Tech

Ben Adams, Computer Science and Software Engineering, University of Canterbury


Acknowledgment of Additional Reviewers
Zekun Li, Min Namgung, Yuankun Jiao, Theresa Chen, Zhiyong Zhou, Yiwei Wang, Jiakun Xu