Web and Wireless Geographical Information Systems

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 89, 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.

Inhalt

.- 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.