Web and Wireless Geographical Information Systems (eBook, PDF)

22nd International Symposium, W2GIS 2025, Mexico City, Mexico, September 8-9, 2025, Proceedings
Redaktion: Mata-Rivera, Miguel Félix; Siabato, Willington; Zagal-Flores, Roberto

• Format: PDF

Produktbeschreibung

This LNCS conference volume constitutes the proceedings of the 22nd International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2025, in Mexico City, Mexico, held during September 8-9, 2025.

The 11 full papers presented in this volume were carefully reviewed and selected from 22 submissions.

They are grouped into the following topics: Advances in Geospatial Artificial Intelligence: From Pixel-level Vision to Large-Language Models; Data-driven Urban Health & Safety: Environmental Exposure, Crime, and Disease Dynamics; Location Intelligence for Urban Resources, Mobility, and Commerce.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 172
• Erscheinungstermin: 16. August 2025
• Englisch
• ISBN-13: 9783032017239
• Artikelnr.: 75213178

Inhaltsangabe

.- Advances in Geospatial Artificial Intelligence: From Pixel-level Vision to Large-Language Models.

.- Enhancing Urban Image Segmentation with Color Range Mask Layer: A Deep Learning Approach Using Airborne Data.

.- AIGC Image Features for GIS: A Preliminary Test of Elements, Colors, and Spatial Structure in Recommendation Tasks.

.- Quality Assessment of Tourist Generated Contents: A Large Language Model Approach.

.- Integrating ChatGPT and Geospatial Resources: A Virtual Assistant for Enhanced Decision-Making in Disaster Response.

.- Data-driven Urban Health & Safety: Environmental Exposure, Crime, and Disease Dynamics.

.- Discovering Urban Insights of Air Pollution in Mexico City Using
Social Networks.

.- An Urban Data Analytics Approach to Explore the Relations Between Trends of Air Pollution and Crime in Mexico City.

.- Diabetes Disparities in Mexico: A Spatio-Temporal and Marginalization Index Analysis.

.- Predictive Model for Identifying High-Risk Areas in the Public Transport Network of Mexico City.

.- Location Intelligence for Urban Resources, Mobility, and Commerce.

.- Analyzing Water Consumption Patterns in Mexico City: A GIS and Data Science Approach.

.- Geospatially-Informed Recommendations for Automobile Purchases: Integrating Spatial Analysis for Enhanced Decision-Making.

.- Predicting the Spatial Longevity of Small and Medium-Sized Enterprises in Mexico City: A Location Intelligence Analysis of Veterinary Clinics.