ArticleNature communications2023
A spatio-temporal analysis investigating completeness and inequalities of global urban building data in OpenStreetMap.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
30 citing papers in PubMed.
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- Global data-water symbiosis reduces AI infrastructure's carbon and water footprint.Environmental science and ecotechnology · 2026Article
- Quantifying roadless areas and fragmentation in the context of wildlife-vehicle collision risk in Great Britain.Scientific reports · 2026Article
- Satellite mapping of every building's function in urban China reveals deep built environment disparities.Nature communications · 2026Article
- Global impacts of transportation infrastructure on forest degradation and loss.Nature communications · 2026Article
- GlobalBuildingMap - Unveiling the mystery of global buildings.Scientific data · 2026Article
- High Spatial Resolution Building Characteristics for the Global South: Insights from the Google Open Buildings Temporal Dataset (2016-2023).Gates open research · 2026Article
- Predicting human mobility flows in cities using deep learning on satellite imagery.Nature communications · 2025Article
- From Footprints to Functions: A Comprehensive Global and Semantic Building Footprint Dataset.Scientific data · 2025Article
- Narrowing the gap for city building height predictions.Scientific reports · 2025Article
- Inequality in infrastructure access and its association with health disparities.Nature human behaviour · 2025Article
- Water outage predictions for natural hazards using synthetic water distribution systems.Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- Satellite-based analysis uncovers uneven solar PV distribution across Japan and its consumption of forest and agricultural lands.Scientific reports · 2025Article
- Mapping and quantifying travel time to define health facility catchment areas in Blantyre city in Malawi.Communications medicine · 2025Article
- Mapping the Completeness and Positional Accuracy of OpenStreetMap Road Data at the County Level in the Contiguous United States.Transactions in GIS : TG · 2025Article
- OSMlanduse a dataset of European Union land use at 10 m resolution derived from OpenStreetMap and Sentinel-2.Scientific data · 2025Article
- The first urban open space product of global 169 megacities using remote sensing and geospatial data.Scientific data · 2025Article
- Monitoring individual rice field flooding dynamics over a large scale to improve mosquito surveillance and control.Malaria journal · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.