This study evaluates the spatial behavior of an intermodal transportation hub in Carapungo, one of the densest neighborhoods in Quito, Ecuador. This public infrastructure is deficient and lacks adequate equipment for the people who use, occupy, and transit within and around it, as well as for the numerous activities that occur, particularly at Carapungo’s Entry Park. Traditional methods for analyzing urban dynamics and land use are typically rigid and fail to grasp the complex and nonlinear nature of public spaces, especially in informal Global South cities. However, recent advancements in Artificial Intelligence and Machine Learning, combined with aerial drone videos, have enabled the modeling and prediction of urban dynamics beyond state regulations and formal planning. In this context, we developed a model using Computer Vision Technology and the YOLOv5 algorithm, incorporating Deep Learning training. The objective is twofold: firstly, to detect people, their movement and speed; and secondly, to produce “Occupancy” and “Count & Speed” cartographies that highlight commuters’ spatial patterns. These situated cartographies provide valuable insights into urban design, mobility, and interaction within a conflicted public space’s-built environment. The generated data offer planners and policymakers quantitative spatial information to consider local practices and dynamics in urban planning, particularly in situations of informality and insufficient urban infrastructure.

Through the understanding of cartography as an alternative representation tool, this paper researches the existing and usually invisible relationships between informal micro-activities and formal public spaces. For this purpose, Carapungo Entry Park located in the north of Quito (Ecuador), is taken as a case study, being a paradigmatic case of the complexity and multiplicity that constitutes informality in Latin American cities. After a first analysis based on the formal planning of this park, we will focus on dissident spatial practices carried out by inhabitants who occupy and appropriate a formal space. These situations of conflict originate spatial constructions based on spontaneity, fluidity, adaptability, movement, and temporality, which include local culture, economy, and social interaction. With the production of cartographies, the processes and activities generated by formal and informal vendors, passers-by, and public transport passengers, are made visible and analyzed. The expected results based on cartography as an alternative representation, are the presentation of relations of tensions, forces, conflicts, and negotiations that allow us to identify patterns, trends and behaviors that have no place in the supposed precision and rigor of the regulations in the formal planning of public space.

Adequate public spaces and urban green areas are key criteria for urban development and infrastructure implementation in healthy cities. Latterly, there have been an increasing number of research methods using artificial intelligence (AI) to monitor, quantify, and control the state of these spaces with an aim toward pioneering research in urban studies. However, in informal areas, open-data access tends to lack adequate and updated information, making it difficult to use AI methods. Hence, we propose a methodology for restricted open data collection and preparation for future use in machine learning or spatial data science models for similar areas. To that extent, we examine two peripheral and low-income neighborhoods in Quito, Ecuador—La Bota and Toctiuco—to analyze their public spaces, urban green areas, points of interest, and road networks, and how they address healthy cities criteria. We develop an original methodological approach that combines an index of proximity, accessibility, quantity, and quality for these spaces with geospatial and network analysis techniques. Results indicate that the connectivity and structure of these spaces are centralized and nodal, representing exclusion and segregation. This work provides insights into potential healthy spaces and information to urban planners and policymakers in decision-making for healthy urban infrastructure.