the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Monitoring Arctic Permafrost – Examining the Contribution of Volunteered Geographic Information to Mapping Ice-Wedge Polygons
Abstract. This study evaluates the potential of Volunteered Geographic Information (VGI) for mapping and monitoring ice-wedge polygons in Arctic permafrost regions through two case studies in Alaska and Canada. We developed and tested a web-based mapping application that enables volunteers to identify polygon centroids in high-resolution aerial imagery, with data collected from 105 contributors in the frame of organized mapping events. The volunteer-contributed data achieved completeness scores of 88.74 % and 70.81 % compared to expert mapping for the Cape Blossom (Alaska) and Blueberry Hills (Canada) study regions respectively, with median positional accuracies of 1.29 m and 1.38 m. Analysis shows that contributions from approximately five volunteers per polygon are sufficient to achieve reliable results. Using Voronoi diagrams derived from the crowd-sourced centroids, we successfully reconstructed ice-wedge polygon networks and extracted key geomorphological and hydrological parameters including polygon area, perimeter, and network topology. The results demonstrate that VGI can effectively support permafrost monitoring by enabling efficient mapping of ice-wedge polygons across large areas while maintaining high data quality standards.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-1778', Anonymous Referee #1, 01 Jul 2025
- AC1: 'Reply on RC1', Oliver Fritz, 28 Aug 2025
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RC2: 'Comment on egusphere-2025-1778', Lingcao Huang, 14 Jul 2025
General comments:
Thanks to Walz et al. for the manuscript on evaluating the contributions from non-expert volunteers for the task of mapping ice-wedge polygons in two typical regions in the Arctic. The manuscript is well written and clearly presents the results with tables and figures, demonstrating the potential of using volunteered geographic information to monitor permafrost-thaw features from remote sensing imagery. I have a few comments and suggestions for the authors to consider.
Although technical details of the crow-sourced mapping application are available in Appendix A, however, if some details and potential issues could be mentioned or discussed in the manuscript, it would benefit other crow-sourced applications. A fundamental assumption of using a crow-sourced system is that it allows many people to contribute to a task that cannot be completed by a few experts. If the task does attract many people, how many concurrent users are allowed in the system? How to synchronize data? In fact, it’s not easy to recruit volunteers for mapping specific features (e.g., permafrost-thaw features) that most people are not familiar with, as demonstrated by Huang et al. 2023 (Huang, L., et al. Identifying active retrogressive thaw slumps from ArcticDEM. ISPRS Journal of Photogrammetry and Remote Sensing, 205, 301–316), how are you going to recruit contributors for a continuous monitoring task besides mapping events? How to manage large datasets if you use the crow-sourced system for much larger areas?
Specific comments:
L6: “positional accuracies”, validated against what data?
L13: “the largest non-seasonal component of the cryosphere”? largest in area?
A screenshot of the web-based crow-sourced mapping application would be helpful for readers to understand its functions and capabilities.
L146: “crowd-validated”? I am a little confused, as these results will still need to be validated by the experts?
Figure 3 would be good to show a zoom-in region, like Figure 4.
Figure 7, please show a zoom-in Figure, like Figure 8.
L239: Where is the difference between “manually digitized reference polygons” and “expert-derived polygons”?
L286: “betweenness” a sentence to explain betweenness and its importance would be helpful for readers without a hydrological background.
L324: “the overall time available for the crowd-sourced mapping process”, What’s the time referring to? The event duration?
L369: “especially when high-resolution elevation data is unavailable”? This is confusing. This manuscript still requires high-resolution imagery. From my understanding, the need for spatial resolution is determined by the observing objects, that is, smaller features require higher spatial resolution.
technical corrections:
L169: “()rettel-bach2021quantitative”?
L309: change “inSAR” to “InSAR”.
Citation: https://doi.org/10.5194/egusphere-2025-1778-RC2 - AC2: 'Reply on RC2', Oliver Fritz, 28 Aug 2025
Data sets
Monitoring Arctic Permafrost - Crowd- sourced Ice-wedge Polygon Center Points P. Walz et al. https://doi.org/10.5281/zenodo.14756139
Model code and software
Workflow python code P. Walz et al. https://gitlab.heigit.org/giscience/disaster-tools/heigit-crowdmap/monitoring-arctic-permafrost
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General comments:
I very much enjoyed reading the preprint ‘Monitoring Arctic Permafrost – Examining the Contribution of Volunteered Geographic Information to Mapping Ice-Wedge Polygons’ by Walz et al. (2025). In the study the authors evaluate the potential of Volunteered Geographic Information (VGI) for mapping and monitoring permafrost by conducting a case study of ice-wedge polygons in two study regions, located in Alaska and Canada.
In general, the manuscript is well prepared and in well the scope of The Cryosphere. The purpose of the manuscript is clearly articulated; the research process is in most parts described sufficiently and appropriate methods were utilized. Although the approach of this study is not totally novel, the manuscript has added value to the use of VGI in permafrost monitoring. However, the discussion remains a bit superficial at some points and should be revised, for example, the broader relevance of the findings should be discussed more thoroughly. In addition, the structure of the manuscript could benefit from small changes. I’ll point out these shortcomings and gaps in the discussion in the next section ‘Specific comments’ – so the authors can take actions on them more easily.
Overall, the manuscript is clear and easy to follow, written in good English, and provides interesting insights into the use of VGI in mapping and monitoring of ice wedge polygons.
Specific comments:
Technical corrections/suggestions: