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This book constitutes the refereed proceedings of the 21st International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2024, held in Yverdon-les-Bains, Switzerland, during June 18-19, 2024.
The 8 full papers and 7 short papers included in this book were carefully reviewed and selected from 20 submissions. The book also contains one invited talk. They were organized in topical sections as follows: Spatiotemporal Data Analysis, Open Data and Reproducible Research, Geospatial Technologies and Tools, Advanced Computing and GIS Applications, Transportation Applications, and Doctoral Symposium.
List of contents
.- Spatiotemporal Data Analysis.
.- A Novel Framework for Spatiotemporal POI Analysis.
.- Exploring Spatiotemporal Dynamics: A Historical Analysis of Missing Persons Data in Mexico, Revealing Patterns and Trends.
.- Assessing and Managing Soil Quality with Geodata: the IQS Project.
.- Open Data and Reproducible Research.
.- Publication of satellite Earth observations in the Linked Open Data Cloud: Experiment through the TRACES project.
.- Geospatial Webservices and Reproducibility of Research: Challenges and Needs.
.- Geospatial Technologies and Tools.
.- TAME II: A Modern Geographic Text Annotation Tool.
.- Towards OGC API - Features centric GIS applications controlled by Object Relational Mapping.
.- Advanced Computing and GIS Applications.
.- Smooth Building Footprint Aggregation with Alpha Shapes.
.- In Situ Visualization of 6DoF Georeferenced Historical Photographs in Location-Based Augmented Reality.
.- Can Large Language Models Automatically Generate GIS Reports?.
.- Transportation Applications.
.- A Digital Twin Architecture for Intelligent Public Transportation Systems: a FIWARE-based Solution.
.- An analysis of container transportation multiple networks from the perspective of shipping company.
.- Doctoral Symposium.
.- A Spatial Interaction Model for the Identification of Urban Functional Regions.
.- Enhancing Efficiency and Privacy of Intelligent Public Transportation Systems through Federated Learning and EdgeAI.
.- Towards a Framework for Personalising Leisure Walking Route Recommendations.
