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A Methodological Approach for Data Collection and Geospatial Information of Healthy public Spaces in Peripheral Neighborhoods. Case Studies: La Bota and Toctiuco, Quito-Ecuador
Medina, A.; Mosquera, D.; Gallegos, F.A. A Methodological Approach for Data Collection and Geospatial Information of Healthy Public Spaces in Peripheral Neighborhoods—Case Studies: La Bota and Toctiuco, Quito, Ecuador. Sustainability2023, 15, 15553.
Medina, A.; Mosquera, D.; Gallegos, F.A. A Methodological Approach for Data Collection and Geospatial Information of Healthy Public Spaces in Peripheral Neighborhoods—Case Studies: La Bota and Toctiuco, Quito, Ecuador. Sustainability 2023, 15, 15553.
Medina, A.; Mosquera, D.; Gallegos, F.A. A Methodological Approach for Data Collection and Geospatial Information of Healthy Public Spaces in Peripheral Neighborhoods—Case Studies: La Bota and Toctiuco, Quito, Ecuador. Sustainability2023, 15, 15553.
Medina, A.; Mosquera, D.; Gallegos, F.A. A Methodological Approach for Data Collection and Geospatial Information of Healthy Public Spaces in Peripheral Neighborhoods—Case Studies: La Bota and Toctiuco, Quito, Ecuador. Sustainability 2023, 15, 15553.
Abstract
Adequate public spaces and urban green areas are key criteria for urban development and infrastructure implementation of healthy cities. Latterly, there has been an increasing number of research methods using artificial intelligence (AI) to monitor, quantify, and control the state of these spaces with an aim towards 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 of 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 on potential healthy spaces, and information to urban planners and policymakers in decision-making for healthy urban infrastructure.
Keywords
peripheral neighborhoods; public space assessment tools; co-location network; open access data; geospatial data science; network analysis; cartography.
Subject
Social Sciences, Urban Studies and Planning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
