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

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

SUBMITTER: Herfort B

PROVIDER: S-EPMC10326063 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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

Herfort Benjamin B Lautenbach Sven S Porto de Albuquerque João J Anderson Jennings J Zipf Alexander A

Nature communications 20230706 1

OpenStreetMap (OSM) has evolved as a popular dataset for global urban analyses, such as assessing progress towards the Sustainable Development Goals. However, many analyses do not account for the uneven spatial coverage of existing data. We employ a machine-learning model to infer the completeness of OSM building stock data for 13,189 urban agglomerations worldwide. For 1,848 urban centres (16% of the urban population), OSM building footprint data exceeds 80% completeness, but completeness remai ...[more]

PMID: 37414776

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Project description:Urbanization has become one of the hot issues of global sustainable development, and is mainly characterized by urban population growth and construction land expansion. However, the inharmonious development of urban expansion and population migration has brought serious challenges to urban planning and management. China is the largest developing country in the world, and the urbanization process has accelerated over the past decades. In this paper, decoupling analysis was used to demonstrate the spatio-temporal relationship between urban expansion and population growth in 321 prefecture-level cities in China, providing a reference basis for sustainable development. The results showed that China's population, total GDP, and construction land area increased from 1990 to 2018. The rate of construction land expansion was larger in the eastern coastal and western regions than in the northeastern and central regions, but the population growth rate was not significantly different among these regions. According to the decoupling analysis, the relationships of population-GDP, construction land-GDP, and population-construction land were mainly weak decoupling, indicating that both the population growth and the construction land expansion lagged behind the economic development, and the population growth lagged behind construction land expansion. In addition, the results were analyzed based on China's four economic regions. Population and construction land area changes in the northeastern provinces experienced a shift from weak decoupling to expansive negative decoupling, then presented a strong decoupling. The decoupling state of population-construction land in the west region was relatively stable. The relationship between population and construction land in the central regions was mainly weak decoupling, and some cities developed into strong decoupling. The relationship between population and construction land in the east region experienced a shift from strong decoupling to weak decoupling, then demonstrated expansive negative decoupling, mainly manifested in the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations. Therefore, the northeast region should take measures to promote regional population growth while reasonably controlling the expansion of construction land, the west region should focus on ecological protection and moderately attract population, the central region should control their population development and reasonably allocate land, and the east region should pay attention to and solve the citizenship problem of migrant workers in second-tier and third-tier cities when promoting new urbanization.

Dataset Information

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

Publications

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

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