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Favelas 4D

Scalable methods for morphology analysis of informal settlements using terrestrial laser scanning data

Bibliographic Data

ID21247757
AuthorsArianna Salazar-Miranda (0000-0003-4093-9250, Massachusetts Institute of Technology, corresponding author), Arianna Salazar Miranda (Massachusetts Institute of Technology), Guangyu Du (0009-0008-8335-3333, Massachusetts Institute of Technology), Claire Gorman (Massachusetts Institute of Technology), Fábio Duarte (0000-0003-0909-5379, Pontifícia Universidade Católica do Paraná), Washington Fajardo (Massachusetts Institute of Technology), Carlo Ratti (0000-0002-1065-2972, Massachusetts Institute of Technology)
Year2022
Volume49
Issue9
Pages2345-2362
Publication date2022-11-01
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning B Urban Analytics and City Science (JOURNAL)
Journal identifiersISSN: 2399-8083 • E-ISSN: 2399-8091
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/23998083221080174
OpenAlexW3161364175
LanguageEN
Citations received2
References cited38

One billion people live in informal settlements worldwide. The complex and multilayered spaces that characterize this unplanned form of urbanization pose a challenge to traditional approaches to mapping and morphological analysis. This study proposes a methodology to study the morphological properties of informal settlements based on terrestrial LiDAR (Light Detection and Ranging) data collected in Rocinha, the largest favela in Rio de Janeiro, Brazil. To measure the morphology of the informal settlement, we propose a series of five metrics related to the geometric characteristics of streets: street width, street elevation, facade heterogeneity, facade density, and street canyon. Our analysis operates at two resolutions, including a global analysis focused on comparing different favela streets to one another and a local analysis unpacking the variation of morphological metrics within streets. We show that our methodology reveals meaningful differences and commonalities in terms of the global morphological characteristics across streets and their local variations, which align with the historical evidence of the favela’s development. Finally, we create morphological maps at high spatial resolution from LiDAR data to inform urban planning assessments of concerns related to crowding, structural safety, air quality, and accessibility in the favela. The methods for this study are automated and can be easily scaled to analyze entire informal settlements, leveraging the increasing availability of inexpensive LiDAR scanners on portable devices such as cellphones

Archaeology · Built environment · Cartography · Civil engineering · Facade · Geography · Human settlement · Informal settlements · Lidar · Remote sensing · Urban Morphology · Urban planning · Urbanization · Computer Science · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Remote Sensing and LiDAR Applications

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Citations per year1
Citation span2024 - 2025 (2)
Highly citedNo

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Open DOIOpen Access
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