URBAN MOBILITY ANALYSIS WITH REAL-TIME GEOSPATIAL DATA AND THE GRAVITY MODEL

Urban mobility in the Metropolitan Area of Guatemala City is influenced by land use, congestion, and travel friction. The integration of real-time data through digital tools like Google Maps allowed for a more precise identification of travel patterns. Using the gravity model, it was found that travel time and congestion are more decisive factors than distance in kilometers. Regional models performed better than the general model, highlighting the need for a differentiated approach to mobility. The lack of structured databases hinders transportation planning, making it essential to combine real-time data and fieldwork to improve decision-making and optimize urban mobility.