Publications
Urban Geo Analytics is grounded in peer-reviewed research. This page gathers the main scientific publications of Joan Perez, founder of UGA — journal articles, software papers, book chapters, and conference contributions spanning urban morphology, spatial analysis, geospatial AI, and open-source tool development. It includes work published under the Urban Geo Analytics affiliation as well as earlier research conducted at various affiliations.
UVLM: A Modular Python Package for Unified Vision–Language Model Loading, Inference and Comparison
Perez, J. & Fusco, G. (2026)
Abstract: Vision–Language Models (VLMs) have emerged as powerful tools for image understanding tasks, yet their practical deployment remains hindered by significant architectural heterogeneity across model families. This paper introduces UVLM (Unified Vision–Language Model), a pip-installable Python (v3.9+) package that provides a unified interface for loading, configuring, and running multiple VLM architectures on custom image analysis tasks. UVLM currently supports two major model families which differ fundamentally in their vision encoding, tokenization, and decoding strategies: LLaVA-NeXT and Qwen2.5-VL. The package abstracts these differences behind a single inference function and eliminates all architecture-specific code from the user’s workflow. UVLM is organized as eight modular Python components (model loading, dual-backend inference, response parsing, consensus validation, batch processing, prompt assembly, model registry, and utilities) and can be deployed in three modes: Google Colab for zero-install cloud access, local Jupyter notebooks for on-premises GPU use, and as a programmatic API for integration into automated pipelines. Key features include a multi-task prompt builder supporting four response types (numeric, category, boolean, text), a consensus validation mechanism based on majority voting, a flexible token budget (up to 1500 tokens) for custom reasoning strategies, and built-in truncation detection. The package is designed for extensibility: adding a new VLM family requires implementing one backend-specific inference section and adding entries to the model registry, without modifying any other module. An illustrative example on 120 street-view images across 16 model configurations is provided to demonstrate the software’s evaluation workflow.
Streetscape Analysis with Generative AI (SAGAI): Vision-language assessment and mapping of urban scenes
Perez, J. & Fusco, G. (2025)
Abstract: Streetscapes are an essential component of urban space. Their assessment is presently either limited to morphometric properties of their mass skeleton or requires labor-intensive qualitative evaluations of visually perceived qualities. This paper introduces SAGAI: Streetscape Analysis with Generative Artificial Intelligence, a modular workflow for scoring street-level urban scenes using open-access data and vision-language models. SAGAI integrates OpenStreetMap geometries, Google Street View imagery, and a lightweight version of the LLaVA model to generate structured spatial indicators from images via customizable natural language prompts. The pipeline includes an automated mapping module that aggregates visual scores at both the point and street levels, enabling direct cartographic interpretation. It operates without task-specific training or proprietary software dependencies, supporting scalable and interpretable analysis of urban environments. Two exploratory case studies in Nice and Vienna illustrate SAGAI’s capacity to produce geospatial outputs from vision-language inference. The initial results show strong performance for binary urban–rural scene classification, moderate precision in commercial feature detection, and lower estimates, but still informative, of sidewalk width. Fully deployable by any user, SAGAI can be easily adapted to a wide range of urban research themes, such as walkability, safety, or urban design, through prompt modification alone.
Population potential on catchment area (PPCA): A Python-based tool for worldwide geospatial population analysis
Perez, J. & Fusco, G. (2025)
Abstract: The Population Potential in Catchment Area (PPCA) protocol is a Python-based methodology designed to evaluate and analyze population distributions within specified pedestrian catchment areas globally. PPCA utilizes OpenStreetMap (OSM) and Global Human Settlement (GHS) data and employs Google Earth Engine for data acquisition and morphometric analysis. Through a series of four automated steps, the protocol cleans, processes, and classifies geospatial data, ultimately yielding refined population estimations within defined catchment regions. This protocol enables researchers and urban planners to assess the population that can be potentially accessed on foot using the street network, within given distances. The protocol allows this assessment globally with minimal input requirements, focusing mostly on bounding box coordinates.
Population and Morphological Change: A Study of Building Type Replacements in the Osaka-Kobe City-Region in Japan
Perez, J. et al., (2024)
Abstract: As cities adapt to new needs and challenges, their forms change in close relation to population dynamics. This article focuses on the link between population dynamics and the evolution of building hull types. The case study is the Osaka-Kobe city-region in Japan, a country globally witnessing an intense population decline. Morphometric indicators are coupled with a tree-like classificatory model in order to label buildings into consistent classes between two different periods (2003–2004 and 2013–2014). The building class distributions and their evolutions are studied in conjunction with population censuses. Urban adaptation processes are particularly accounted for through the study of the replacement of building types. Results show that, among other things, townhouses in traditional neighborhoods are gradually being replaced by small-size collective complexes. In far outlying areas, people are still eager to move and live in detached single-family homes despite a global context of population decline. Finally, central places are increasingly filled by narrow almost-adjoining towers. Relations between building types and population dynamics, detailed through maps and statistics, show that peoples are increasingly concentrating in central locations associated with specific building types, while some other peripheral locations are concerned by both a disappearance of specific building types and a population decline.
An Urban World
Moriconi-Ebrard, F and Perez, J (2024)
Abstract: The urban world arises from an inclination toward consolidation in a mineralized environment crafted by humans. It embodies the material manifestation of the species’ gregarious tendency. The geographical landscape of the 21st century directs our attention not toward the autonomy of the urban world in relation to the rural world but, on the contrary, to the map of the ancient rural world. The dynamics of rural densification and its colonization through urban dispersal are reshaping a historical and classical paradigm of urban dynamics based on a view that urbanization is primarily driven by migrant flows, notably rural exodus. The studies on metropolization present a reductionist and elitist perspective of urbanization. Development and urban planning projects, such as new neighborhoods and eco-districts, are proliferating and contribute to the development, and even redevelopment, of urban areas. Nations benefitting from industrial relocations are experiencing a phase of intense urban concentration.
Potential of the 15-Minute Peripheral City: Identifying Main Streets and Population Within Walking Distance
Perez, J & Fusco, G. (2024)
Abstract: The concept of the 15-minute city presents challenges for pedestrian accessibility, particularly in peripheral areas with less pedestrian-friendly street networks. This paper explores the angular continuity of main streets and the population potential around them as crucial elements for the development of the 15-minute peripheral city. By utilizing geoprocessing algorithms, the study aims to identify main streets and verify their demographic potential in two distinct geographic contexts near Lille and Nice, France. The protocol is divided into four steps, as follows: (1) main streets identification through continuity, (2) calculation of morphological indicators on buildings, (3) machine learning to estimate the number of dwellings per building, and (4) population potential estimate within different walking distances from main streets. The findings reveal a network of interconnected main streets with significant population potentials in the outskirts of both test areas. These streets could serve as the development corridors for enhancing commercial activities and services, supporting the vision of the 15-minute city in peripheral areas.
Sustainable Aging in Aix-Marseille-Provence Metropolis: Assessment Indicators and Interactive Visualizations for Policy Making
Perez, J et al., (2023)
Abstract: As the world’s population continues to age and urbanization accelerates, the focus of urban sustainability has evolved towards promoting the needs and well-being of older adults in addition to environmental concerns. Urban environments have a significant impact on the experiences of city dwellers, particularly of older adults, and from this perspective certain neighborhoods present greater challenges than others. To address issues related to aging, cities around the world have launched initiatives to improve urban sustainability for older adults, ranging from redesigning public spaces to providing opportunities for social interaction. However, to design effective interventions, open-access data related to urban environments must be collected and analyzed to identify neighborhoods with the greatest need for improvement. This paper presents a case study of the Aix-Marseille-Provence metropolis in France, showing that a range of assessment indicators focused on walkability and urban form can be calculated using open-access data. Through the presentation of these indicators and exploratory analysis results in a visual and interactive format (HTML-based platform), planners and policymakers can quickly identify patterns and trends, thereby helping them identify neighborhoods with the most significant needs and create more effective policies.
Classification and clustering of buildings for understanding urban dynamics – A framework for processing spatiotemporal data
Perez, J et al., (2022)
Abstract: This paper presents different methods implemented with the aim of studying urban dynamics at the building level. Building types are identified within a comprehensive vector-based building inventory, spanning over at least two time points. First, basic morphometric indicators are computed for each building: area, floor-area, number of neighbors, elongation, and convexity. Based on the availability of expert knowledge, different types of classification and clustering are performed: supervised tree-like classificatory model, expert-constrained k-means and combined SOM-HCA. A grid is superimposed on the test region of Osaka (Japan) and the number of building types per cell and for each period is computed, as well as the differences between each period. Mappings are then performed, showing that building types have specific locations and dynamics. In some extreme cases, a specific building type can even gradually replace a type on a declining dynamic. Questions of data preparation, and clustering validation are also dealt with, underlining the interest of assessing the spatial distribution of clusters.
Ageing and Urban Form in Aix-Marseille-Provence Metropolis
Perez, J et al., (2021)
Abstract: The world population is ageing. In France, this phenomenon is particularly pronounced with 19.6% of the population being over 65-year-old in 2018. While it has been recognized that urban form plays an important role in ensuring a sustainable future for urban areas, ageing dynamics are challenging the core concept of urban sustainability. Maintaining or improving the quality of life of an ageing population through urban built form will become as much important, and as much recognized, as ensuring urban environmental sustainability in the future. Today, the well-being of the elderly is still reduced to the economic aspects of the silver economy or to ergonomic aspects in building design. While socio-demographic micro-data on the elderly are available, a comprehensive metropolitan-wide and fine-scale description of the urban forms where seniors live must rely on the latest developments of urban morphometrics. From historic city centres to suburban residential areas, passing through modernist apartment blocks, none of these typical forms seems particularly suited to the needs posed by ageing, which must accommodate accessibility to housing itself and to local shops, health care and services in general. The question of the role of different urban forms over the spatial distribution of the seniors thus arises, as well as the capacity of spatial arrangements to suit the needs and specificities of an ageing population. The case study is a metropolitan area that offers a great heterogeneity of urban forms: AixMarseille-Provence, in Southern France. Some areas show over or under-representation of seniors, while others are better at ensuring a generational mix. In most cases, the spatial distribution of the seniors can be linked to specific building hull forms. The spatial distribution of these hull types, and their close relationships to ageing and accessibility are presented in this paper.
Are patterns of vacant lots random? Evidence from empirical spatiotemporal analysis in Chiba prefecture, east of Tokyo
Usui, H & Perez, J (2021)
Abstract: According to the Japanese government, vacant lots are randomly generated and accumulated (without being rebuilt after demolition) in the process of increasing vacant lots, a phenomenon called urban perforation. Urban perforation in urban areas may trigger a high degree of inefficiency in public infrastructure management. However, this observation lacks theoretical and empirical foundations, a lacuna to which this paper will focus on. Consequently, our research objectives are to confirm: (1) whether or not vacant lots are randomly generated and (2) whether or not vacant lots are randomly accumulated as a result of random generation. The methodology includes a consistent and bottom-up approach to delineate urban areas (alongside statistical spatial analysis). Through theoretical and empirical analyses in Chiba Prefecture (situated in the eastern part of the Tokyo metropolitan region), we find that the random generation of vacant lots does not tend to continue in the same urban areas. Rather, in most urban areas, this process is a temporary phenomenon. Subsequently, phase transition generally shifts from random to clustered generation or vice versa. Nevertheless, once vacant lots are randomly accumulated in an urban area, this process tends to continue. The contributions of this article are not only to provide important spatiotemporal findings regarding the generation and accumulation patterns of vacant lots, but also to discuss how to apply policy for urban perforation where phenomena are significantly pronounced.









