.- 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.
