Publications

Select publications

Wagner, C., Dodge, S., & Alizadeh, D., (2025) Identifying Resilient Communities in Road Networks: A Path-Based Embedding Approach. The proceedings of the 13th International Conference on Geographic Information Science, Christchurch, New Zealand.

Noi, E., Dodge, S., & Murray, A. T. (2025). Exploring the effects of wildfire events on movement patterns. Applied Geography, 179, 103602. https://doi.org/10.1016/j.apgeog.2025.103602

Long, J. A., Demšar, U., Dodge, S., & Weibel, R. (2025). Data-driven movement analysis. International Journal of Geographical Information Science, 39(5), 945–950. https://doi.org/10.1080/13658816.2025.2481096

Cho, S., Murray, A. T. , Dodge, S. &  Church, R. L., (2025) Locational Decision-Making and Representational Impacts, The Professional Geographer, 77(2), 121-135, DOI: 10.1080/00330124.2025.2455180

Wan, Z., & Dodge, S. (2024). Medark: a map-matching error detection and rectification framework for vehicle trajectories. International Journal of Geographical Information Science, 39(4), 872–899. https://doi.org/10.1080/13658816.2024.2436482.

Su, R., Newsham, N., & Dodge, S. (2024). Spatiotemporal dynamics of ethnoracial diversity and segregation in Los Angeles County: Insights from mobile phone data. Computers, Environment and Urban Systems, 114, 102203.

Alizadeh, D., & Dodge, S. (2024). Disaster vulnerability in road networks: a data-driven approach through analyzing network topology and movement activity. International Journal of Geographical Information Science, 1-22.

Liu, Y., Battersby, S., & Dodge, S. (2024). Scaling up time–geographic computation for movement interaction analysis. Transactions in GIS, 28(6), 1577-1593.

Park, J., Tsou, M. H., Nara, A., Dodge, S., & Cassels, S. (2024). Examining human mobility changes during COVID-19 across socioeconomic groups: a comparative analysis of San Diego County and New York City. Computational Urban Science, 4(1), 21.

Su, R., Liu Y., Dodge, S., (2024). ORTEGA v1.0: an open-source Python package for context-aware interaction analysis using movement data. Movement Ecology, 12(20). https://doi.org/10.1186/s40462-024-00460-2.

Liu Y., Dodge, S., Simcharoen, A., Ahearn, S.C., Smith, J.L.D, (2024) Analyzing tiger interaction and home range shifts using a time-geographic approach. Movement Ecology. 12 (1), 13. https://doi.org/10.1186/s40462-024-00454-0

Park, J., Tsou, MH., Nara, A. Cassels, S., Dodge, S.(2024)  Developing a social sensing index for monitoring place-oriented mental health issues using social media (twitter) data. Urban Info 3, 2 (2024). https://doi.org/10.1007/s44212-023-00033-5

Wan Z., and Dodge, S. (2023). A Generative Trajectory Interpolation Method for Imputing Gaps in Wildlife Movement Data. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on AI-driven Spatio-temporal Data Analysis for Wildlife Conservation (GeoWildLife ’23). Association for Computing Machinery, New York, NY, USA, 1–8. https://doi.org/10.1145/3615893.3628759

Wan, Z., Dodge, S., & Bohrer, G. (2023). Leveraging similarity analysis to understand variability in movement behavior. Transactions in GIS, 27(5), 1441-1466. https://doi.org/10.1111/tgis.13082

Bae, C. J., & Dodge, S. (2023). Assessing the cognition of movement trajectory visualizations: interpreting speed and direction. Cartography and Geographic Information Science, 50(2), 143-161. https://doi.org/10.1080/15230406.2022.2157879

Dodge, S., & Nelson, T. A. (2023). A framework for modern time geography: emphasizing diverse constraints on accessibility. Journal of Geographical Systems, 25, pages 357-375. https://doi.org/10.1007/s10109-023-00404-1

Franklin, R. S., Delmelle, E. C., Andris, C., Cheng, T., Dodge, S., Franklin, J., … & Wentz, E. A. (2023). Making space in geographical analysis. Geographical Analysis, 55(2), 325-341. https://doi.org/10.1111/gean.12325

Noi, E., Rudolph, A. & Dodge, S. (2023), VASA: An Exploratory Visualization Tool for Mapping Spatio-temporal Structure of Mobility – A COVID-19 Case Study. Cartography and Geographic Information Science (CaGIS). 51(2), pages 275-296. https://doi.org/10.1080/15230406.2022.2156388

Su, R., Dodge, S., Goulias, K., (2022) A classification framework and computational methods for human interaction analysis using movement data, Transactions in GIS, 26(4), Pages 1665-1682, https://doi.org/10.1111/tgis.12960

Su, R., Dodge, S., Goulias, K., (2022) Understanding the impact of temporal scale on human movement analytics, Journal of Geographical Systems, 24, pages 353–388, DOI: 10.1007/s10109-021-00370-6. (Selected as the JGS Editor’s Choice Article).

Noi, E., Rudolph, A. & Dodge, S. (2022) Assessing COVID- induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi- source analytical framework, International Journal of Geographical Information Science, 36(3), Pages 585-616. DOI: 10.1080/13658816.2021.2005796

Dodge, S., Toka, M. & Bae, C.J. (2021) DynamoVis 1.0: an exploratory data visualization software for mapping movement in relation to internal and external factors. Movement Ecology 9, 55 (2021). https://doi.org/10.1186/s40462-021-00291-5

Dodge, S., Noi, E. (2021) Mapping trajectories and flows: Facilitating a human-centered approach to data-driven movement analytics. Cartography and Geographic Information Science (CaGIS). 48 (4), pp. 353-375, DOI: 10.1080/15230406.2021.1913763

Dodge, S., Su, R., Johnson, J., Simcharoen, A., Goulias, K., Smith J.L.D., Ahearn, S.C. (2021) ORTEGA: an object-oriented time-geographic analytical approach to trace space-time contact patterns in movement data, Computer Environment and Urban Systems. Vol 88, 101630. https://doi.org/10.1016/j.compenvurbsys.2021.101630

Dodge, S., (2021) A Data Science Framework for Movement. Geographical Analysis, the GA 50th Anniversary Special Issue, 53 (1), pp. 92 –112. https://doi.org/10.1111/gean.12212.

Adams, B., Dodge, S., Purves, R., (2020) JOSIS’s 10th anniversary special feature: part two, Journal of Spatial Information Science. No. 21, pp. 1–4. Editorial. doi:10.5311/JOSIS.2020.21.729

Adams, B., Dodge, S., Purves, R., (2020) JOSIS’s 10th anniversary special feature, Journal of Spatial Information Science. No. 20, pp. 1–4. Editorial. doi:10.5311/JOSIS.2019.19.670

Dodge, S.,Gao, S., Tomko, M., Weibel, R., (2020) Progress in computational movement analysis – towards movement data science, International Journal of Geographical Information Science. 34 (12), pp. 2395–2400. doi:10.1080/13658816.2020.1784425

Miller, H., Dodge, S., Miller, J., and Bohrer, G., (2019) Towards an integrated science of movement: converging research on animal movement ecology and human mobility, International Journal of Geographical Information Science, 33(5), pp. 855 – 876, doi:10.1080/13658816.2018.1564317

Long, J. A ., Weibel, R., Dodge, S. & Laube P. (2018), Moving ahead with computational movement analysis, International Journal of Geographical Information Science, Volume 32, Issue 7, pp. 1275 – 1281, doi: 10.1080/13658816.2018.1442974.

Ahearn, S.C., Dodge, S. (2018), Recursive Multi-frequency Segmentation of Movement Trajectories (ReMuS), Methods in Ecology and Evolution, 9(4), 1075 –1087.

Obringer, R., Bohrer, G., Weinzierl, R., Dodge, S., Deppe, J., Ward, M., Brandes, D., Kays, R., Flack, A., and Wikelski, M., (2018) Track Annotation: Determining the Environmental Context of Movement Through the Air. In Chilson, P.B., Frick, W.F., Kelly, J.F., Liechti., F., (Eds.), Aeroecology. Chapter 4, pp. 71 – 76, Springer. doi:10.1007/978-3-319-68576-2_4.

Soleymani, A., Pennekamp, F., Dodge, S., and Weibel, R., (2017). Characterizing change points and continuous transitions in movement behaviors using wavelet decomposition. Methods in Ecology and Evolution. Volume 8, Issue 9, September 2017, pp. 1113 – 1123. doi: 10.1111/2041-210X.12755

Ahearn, S.C., Dodge, S., Simcharoen, A., Xavier., G., Smith, J.L.D., (2017), A context-sensitive correlated random walk: A new simulation model for movement. International Journal of Geographical Information Science,31:5, pp 867 –883, doi:10.1080/13658816.2016.1224887. [pdf]

Dodge, S., (2016). From Observation to Prediction: The Trajectory of Movement Research in GIScience. In Onsrud, H. and Kuhn, W., (Eds.), Advancing Geographic Information Science: The Past and Next Twenty Years.  Chapter 9. pp. 123 – 136. GSDI Association Press. [pdf]

Dodge, S., Weibel, R., Ahearn, SC., Buchin, M., Miller, J. (2016). Analysis of movement data, International Journal of Geographical Information Science, Volume 30, Issue 5, pages 825–834, doi:10.1080/13658816.2015.1132424. [pdf]

Buchin, M., Dodge, S., and Speckmann, B. (2014). Similarity of Trajectories Taking into Account Geographic Context. Journal of Spatial Information Science (JOSIS). No. 9, pp. 101–124, doi:10.5311/JOSIS.2014.9.179.

Soleymani, A., Cachat, J., Robinson, K., Dodge, S., Kalueff, A., and Weibel, R., (2014). Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement. Journal of Spatial Information Science (JOSIS). No. 8, pp. 1–25, doi:10.5311/JOSIS.2014.8.162.

Dodge, S., Bohrer, G., Bildstein, K., Davidson, S.C., Weinzierl, R., Bechard, M.J., Barber, D., Kays, R., Brandes, D., Han, J., and Wikelski, M., (2014). Environmental effects on multi-year variability in movement ecology of turkey vultures (Cathartes aura) in North and South America. Philosophical Transactions B. Special issue: Satellite Remote Sensing for Biodiversity Research and Conservation Applications. May 2014, 369: 20130195. doi:10.1098/rstb.2013.0195.

Dodge, S., Bohrer, G., Weinzierl, R., Davidson, S.C., Kays, R., Douglas, D., Cruz, S., Han, J., Brandes, D., and Wikelski, M., (2013). The Environmental-Data Automated Track Annotation (Env-DATA) System: Linking Animal Tracks with Environmental Data. Movement Ecology, July 2013, 1:3, BioMed Central Ltd. doi:10.1186/2051-3933-1-3.

Dodge, S., Laube, P., and Weibel, R. (2012). Movement Similarity Assessment Using Symbolic Representation of Trajectories. International Journal of Geographical Information Science. Volume 26, Issue 9, pages 1563–1588, Taylor & Francis.

Dodge, S., Weibel, R. and Forootan, E. (2009). Revealing the Physics of Movement: Comparing the Similarity of Movement Characteristics of Different Types of Moving Objects. Computers, Environment and Urban Systems, Volume 33, Issue 6, November 2009, pages 419–434.

Dodge, S., Weibel, R. and Lautenschutz, A-K. (2008). Towards a Taxonomy of Movement Patterns. Information Visualization, Vol. 7, pages 240–252.

Peer-reviewed Conference Papers

Noi, E., & Dodge, S. (2023). A Data Fusion Framework for Exploring Mobility Around Disruptive Events (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Schloss Dagstuhl-Leibniz-Zentrum für Informatik.

Noi, E., Rudolph, R. & Dodge, S. (2021) A novel method for mapping spatiotemporal structure of mobility patterns during the COVID-19 pandemic. GIScience Conference 2021 Short Paper Proceedings, UC Santa Barbara: Center for Spatial Studies.

Su, R., Dodge, S., Goulias, K., (2021) A time-geographic approach to quantify the duration of interaction in movement data, the 1st ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility, 2021 ACM SIGSPATIAL Conference. ~~Received Best Paper Award~~

Dodge, S., (2020), Towards a cartographic framework for movement, In proceedings of AutoCarto 2020: the 23rd International Research Symposium on cartography and GIScience. November 18-20, 2020, Esri Campus, Redlands, CA.

Dodge, S., (2018), Embracing visualization as a key element in computational movement analytics, In Freundschuh, S.M., Sinton, D., (Eds.) AutoCarto / UCGIS 2018, The 22nd International Research Symposium on Computer-based Cartography and GIScience, Pages 52–57, 22 – 24 May, Madison, WI.

Dodge, S., (2016), Context-sensitive spatiotemporal simulation model for movement, GIScience 2016, 27-30 September, Montreal, Canada.

Bohrer, G., Kays, R., Davidson, S., Weinzierl, R., Dodge, S., McClain, K.M., Wikelski, M., (2015). Remote Sensing in Support of Endangered Species Management and Animal Movement Research — The Env-DATA tool pack. The 66th International Astronautical Congress. pp. 2-7, 12-16 October, Jerusalem, Israel, IAC-15-B5,2,8,x30258.

Xavier, G. and Dodge, S., (2014). An Exploratory Visualization Tool for Mapping the Relationships between Animal Movement and the Environment. In Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Interacting with Maps. pp. 36–42, doi:10.1145/2677068.2677071

Buchin, M., Dodge, S., and Speckmann, B. (2012). Context-Aware Similarity of Trajectories. In Xiao, N., Kwan, M.P., Goodchild, M.F. & Shekhar, S. (Eds.): Geographic Information Science, Lecture Notes in computer Science (LNCS): 7478, pages 43-56, Springer-Verlag Berlin Heidelberg, GIScience 2012. 18-21 September 2012, Columbus, Ohio. USA.

Dodge, S., Weibel, R., and Laube, P. (2011). Trajectory Similarity Analysis in Movement Parameter Space. GISRUK 2011, pages 270-279. Short paper. April 27-29, 2011, University of Portsmouth, UK.

Dodge, S., Weibel, R. and Laube, P. (2009). Exploring Movement – Similarity Analysis of Moving Objects. The SIGSPATIAL Special, Volume 1, Issue 3, pages 11-16. The 17th ACM International Conference on Advances in Geographic Information Systems. 4-6 November 2009. PhD Showcase.

Edited Volumes

Long, J., Weibel., R., Dodge, S., and Laube, P., (2018), Special Issue in Memoriam of Professor Rein Ahas on Computational Movement Analysis, International Journal of Geographical Information Science, Volume 32, Issue 7–8, July–August 2018, pages 1275 — 1698, ISSN 1365-8816. Taylor & Francis.

Birkin, M., Dodge, S., Fasy B.T., and Mann, R.P. (2018), From Observations to Prediction of Movement (Dagstuhl Seminar 18282). Dagstuhl Reports, Volume 7, Issue 7, pages 54 — 71. doi:10.4230/DagRep.7.7.54

Weibel., R., Dodge, S., Ahearn, SC, Buchin, M., Miller, J. (2016), Special Issue on Analysis of Movement Data, International Journal of Geographical Information Science, Volume 30, Issue 5-6, May–June 2016, pages 825 — 1253, ISSN 1365–8816, Taylor & Francis.