Worldwide Detection of Informal Settlements via Topological Analysis of Crowdsourced Digital Maps
Datos Bibliográficos
| ID | 22031991 |
|---|---|
| Autores | Satej Soman (0000-0001-8450-7025, University of Chicago, autor de correspondencia), Anni Beukes (0000-0002-7502-4125, University of Chicago), Cooper Nederhood (0000-0001-5400-3272, University of Chicago), Nicholas Marchio (0000-0002-0677-1864, University of Chicago), Luís Bettencourt (0000-0001-6176-5160, University of Chicago) |
| Año | 2020 |
| Volumen | 9 |
| Número | 11 |
| Páginas | 685 |
| Fecha de publicación | 2020-11-16 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | ISPRS International Journal of Geo-Information (JOURNAL) |
| Identificadores de la revista | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Editorial | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi9110685 |
| OpenAlex | W3089232044 |
| Idioma | EN |
| Citas recibidas | 7 |
| Referencias citadas | 27 |
The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion through informal settlements (slums). These neighborhoods are too often characterized by a lack of connections, both physical and socioeconomic, with detrimental effects to residents and their cities. Here, we show how a scalable computational approach based on the topological properties of digital maps can identify local infrastructural deficits and propose context-appropriate minimal solutions. We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120 Low and Middle Income Countries (LMICs) in the Global South. We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated. We discuss how these diagnostics and solutions provide a multiscalar set of new capabilities—from individual neighborhoods to global regions—that can coordinate local community knowledge with political agency, technical capability, and further research
Cadastre · Cartography · Data science · Database · Geography · Geospatial analysis · Human settlement · Regional science · Scalability · Sociology · Automated Road and Building Extraction · Computer Science · Land Use and Ecosystem Services · Urban Design and Spatial Analysis
Spatial Information Gaps on Deprived Urban Areas (Slums) in Low-and-Middle-Income-Countries
Analysis of OpenStreetMap Data Quality at Different Stages of a Participatory Mapping Process
Methodological foundation of a numerical taxonomy of urban form
Slum and urban deprivation in compacted and peri-urban neighborhoods in sub-Saharan Africa
Towards a configurational typology of informal settlements
An analysis of morphological pattern variations in street networks within and surrounding slums in São Paulo, Brazil
Mapping the margins
Deep Learning in Remote Sensing
Heterogeneity and scale of sustainable development in cities
The Challenge of Slums
The world’s user-generated road map is more than 80% complete
An ontology of slums for image-based classification
Slums from Space—15 Years of Slum Mapping Using Remote Sensing
Combining satellite imagery and machine learning to predict poverty
Optimal reblocking as a practical tool for neighborhood development
A Critical Review of High and Very High-Resolution Remote Sensing Approaches for Detecting and Mapping Slums
Informal settlement upgrading and safety
Rhetoric of the ‘slum’
Where there is no local government
The five-city enumeration
If in doubt, count”
Urban transformations, migration and residential mobility patterns in African secondary cities
The Economics of Slums in the Developing World
| Obras citantes distintas | 7 |
|---|---|
| Citas por año | 1,4 |
| Intervalo de citas | 2021 - 2026 (6) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 6 |