A spatio-temporal analysis investigating completeness and inequalities of global urban building data in OpenStreetMap

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Июль 6, 2023

Abstract OpenStreetMap (OSM) has evolved as a popular dataset for global urban analyses, such assessing progress towards the Sustainable Development Goals. However, many analyses do not account uneven spatial coverage of existing data. We employ machine-learning model to infer completeness OSM building stock data 13,189 agglomerations worldwide. For 1,848 centres (16% population), footprint exceeds 80% completeness, but remains lower than 20% 9,163 cities (48% population). Although inequalities have recently receded, partially result humanitarian mapping efforts, complex unequal pattern biases remains, which vary across various human development index groups, population sizes and geographic regions. Based on these results, we provide recommendations producers analysts manage data, well framework support assessment biases.

Язык: Английский

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Unsupervised machine learning in urban studies: A systematic review of applications

Cities, Год журнала: 2022, Номер 129, С. 103925 - 103925

Опубликована: Авг. 15, 2022

Язык: Английский

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Challenges of urban digital twins: A systematic review and a Delphi expert survey

Automation in Construction, Год журнала: 2023, Номер 147, С. 104716 - 104716

Опубликована: Янв. 5, 2023

Many challenges to operate digital twins remain, hindering their design and implementation, are rarely discussed. Furthermore, issues of social legal nature often overlooked. We identify the operating in urban context through a bifurcated multi-dimensional approach: systematic literature review an expert survey. The organises identified across technical non-technical dimensions. As topic is novel, corpus rather small lacking contextualisation challenges. Thus, we complement it with survey based on Delphi method, involving diverse panel domain experts covering academia, industry government organisations. Combining results, 14 9 map them phases twin's life cycle. most severe appear be related interoperability (e.g. disparate semantic standards) practical value lack business models).

Язык: Английский

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Quality of crowdsourced geospatial building information: A global assessment of OpenStreetMap attributes

Building and Environment, Год журнала: 2023, Номер 237, С. 110295 - 110295

Опубликована: Апрель 18, 2023

Geospatial data of the building stock is essential in many domains pertaining to built environment. These datasets are often provided by governments, but crowdsourcing them has surged last decade. Nowadays, OpenStreetMap (OSM) – most popular Volunteered Geographic Information (VGI) platform contains geospatial and descriptive on more than 500 million buildings worldwide collected millions contributors, it increasingly used studies ranging from energy microclimate urban planning life cycle assessment. However, large-scale understanding their quality remains limited, which may hinder use management. In this paper, we seek understand state information OSM whether a reliable source such data. We provide comprehensive study assess attribute (descriptive) mapped globally, e.g. function, key ingredients analyses simulations examine three aspects: completeness, consistency, accuracy. assessment, first at scale available hitherto, find that continues be highly heterogeneous — poor some, very high completeness other areas, potentially benefiting range application domains, estimate 3D models 443 administrative units (mostly cities municipalities) around world can generated OSM, underpinning generation digital twins. The number floors type frequent properties contributors record, cases accurate, while mapping interior did not gain momentum.

Язык: Английский

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Revealing spatio-temporal evolution of urban visual environments with street view imagery

Landscape and Urban Planning, Год журнала: 2023, Номер 237, С. 104802 - 104802

Опубликована: Май 17, 2023

Язык: Английский

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EUBUCCO v0.1: European building stock characteristics in a common and open database for 200+ million individual buildings

Scientific Data, Год журнала: 2023, Номер 10(1)

Опубликована: Март 20, 2023

Building stock management is becoming a global societal and political issue, inter alia because of growing sustainability concerns. Comprehensive openly accessible building data can enable impactful research exploring the most effective policy options. In Europe, efforts from citizen governments generated numerous relevant datasets but these are fragmented heterogeneous, thus hindering their usability. Here, we present EUBUCCO v0.1, database individual footprints for ~202 million buildings across 27 European Union countries Switzerland. Three main attributes - height, construction year type included respectively 73%, 24% 46% buildings. We identify, collect harmonize 50 open government OpenStreetMap, perform extensive validation analyses to assess quality, consistency completeness in every country. v0.1 provides basis high-resolution urban studies scales continental, comparative or local using centralized source variety use cases, e.g., energy system analysis natural hazard risk assessments.

Язык: Английский

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Knowledge and topology: A two layer spatially dependent graph neural networks to identify urban functions with time-series street view image

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2023, Номер 198, С. 153 - 168

Опубликована: Март 16, 2023

Язык: Английский

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Automatic assessment of public open spaces using street view imagery

Cities, Год журнала: 2023, Номер 137, С. 104329 - 104329

Опубликована: Апрель 22, 2023

Язык: Английский

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A graph-based neural network approach to integrate multi-source data for urban building function classification

Computers Environment and Urban Systems, Год журнала: 2024, Номер 110, С. 102094 - 102094

Опубликована: Март 15, 2024

Язык: Английский

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Assessing the differential impact of vegetated and built-up areas on heat exposure environment: A case study of Los Angeles

Building and Environment, Год журнала: 2025, Номер unknown, С. 112538 - 112538

Опубликована: Янв. 1, 2025

Язык: Английский

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