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

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), pages 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.

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

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). 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, https://doi.org/10.1007/s10109-021-00370-6. (Selected as the JGS Editor’s Choice Article).

Noi, E., Rudolph, A., & Dodge, S. (2021). Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework. International Journal of Geographic Information Science, 36(3), Pages 585-616, https://doi.org/10.1080/13658816.2021.2005796

Dodge, S., Toka, M., Bae, C. (2021). DynamoVis 1.0: An Exploratory Data Visualization Software for Mapping Movement in Relation to Internal and External Factors, Movement Ecology, 9:55, https://doi.org/10.1186/s40462-021-00291-5

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).

Noi, E., Rudolph, A., & Dodge, S. (2021). A novel method for mapping spatiotemporal structure of mobility patterns during the COVID-19 pandemic. GIScience 2021 Short Paper Proceedings, UC Santa Barbara: Center for Spatial Studies. http://dx.doi.org/10.25436/E2WC7B [download link]

Dodge S., Noi, E. (2021) Mapping trajectories and flows: Facilitating a human-centered approach to data-driven movement analytics. Cartography and Geographic Information Science. 48:4, 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, Computers, Environment and Urban Systems, 88 (July 2021), 101630, pp. 1–14. doi: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. doi:10.1111/gean.12212

Dodge, S., (2020) WhereNext: Towards a Cartographic Framework for Movement, in AutoCarto 2020. [pdf]

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

Dodge, S., Ahearn, SC. (2020) Multi-scale Modeling of Movement. Scale and Spatial Analytics: A SPARC Workshop. February 10 – 11, 2020, Arizona State University, Tempe, AZ. Position paper.

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

Dodge, S., (2019) Towards Movement Data Science, Spatial Data Science Symposium: Setting the Spatial Data Science Agenda. December 9-11, 2019 – Santa Barbara, California. [pdf]

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 Geographic Information Science, 33(5), pp. 855 — 876. doi:10.1080/13658816.2018.1564317