International Journal of Geographical Information Science

The special issue relates to a GIScience’23 workshop titled: ‘Disruptive Movement Analysis’ (https://somayehdodge.info/amd-giscience/dma-2023/).

The call is not limited to the workshop and we invite anyone interested to submit a paper. We are interested in work dealing with any type of moving object (e.g., people, animals, vehicles, virus, goods etc.), with application in any domain (e.g., health, transportation, wildlife ecology, sports, marine, outdoor recreation, fitness, epidemiology). We invite submissions of both empirical and vision research papers that describe new research ideas that fit the general theme of data-driven movement analysis, including, but not limited to, the following topics:

• Bias, representativeness, and uncertainty
• Privacy and ethics
• Open science and reproducible research
• Data fusion / data integration
• Big data / big models
• Deep learning
• GeoAI
• Inter- or multi-disciplinary problems (e.g., human-wildlife interaction)
• Simulation and prediction
• Visualization

Guidelines for submission of full manuscripts can be found at: http://www.tandfonline.com/action/authorSubmission?journalCode=tgis20&page=instructions/.

The International Journal of Geographical Information Science (IJGIS) considers all manuscripts on the strict condition that they have been submitted only to the International Journal of Geographical Information Science, that they have not been published already (including in conference proceedings), nor are they under consideration for publication or in press elsewhere. Manuscripts that significantly extend conference papers should (1) paraphrase original text with proper citations, and (2) clarify novel ideas or methods beyond what has been reported in the conference papers.

IJGIS exercises double-blinded peer reviews, so manuscripts for the peer reviews cannot disclose authors, affiliations, and funding agencies in the text. IJGIS requires sharing data and codes to support research reproducibility and replicability.  If research data cannot be shared due to privacy or licensing issues, mock data or simulated data should be provided to show how the codes work. Detailed information is available in the submission guideline under data and codes availability statement.

Instructions for AuthorsSubmit an Article