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

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: July 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.

Language: Английский

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Mapping the landscape and roadmap of geospatial artificial intelligence (GeoAI) in quantitative human geography: An extensive systematic review

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2024, Volume and Issue: 128, P. 103734 - 103734

Published: March 11, 2024

This paper brings a comprehensive systematic review of the application geospatial artificial intelligence (GeoAI) in quantitative human geography studies, including subdomains cultural, economic, political, historical, urban, population, social, health, rural, regional, tourism, behavioural, environmental and transport geography. In this extensive review, we obtain 14,537 papers from Web Science relevant fields select 1516 that identify as studies using GeoAI via scanning conducted by several research groups around world. We outline applications systematically summarising number publications over years, empirical across countries, categories data sources used applications, their modelling tasks different subdomains. find out existing have limited capacity to monitor complex behaviour examine non-linear relationship between its potential drivers—such limits can be overcome models with handle complexity. elaborate on current progress status within each subdomain geography, point issues challenges, well propose directions opportunities for future context sustainable open science, generative AI, quantum revolution.

Language: Английский

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Global Streetscapes — A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2024, Volume and Issue: 215, P. 216 - 238

Published: July 16, 2024

Language: Английский

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Sensitivity of measuring the urban form and greenery using street-level imagery: A comparative study of approaches and visual perspectives

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2023, Volume and Issue: 122, P. 103385 - 103385

Published: June 17, 2023

Street View Imagery (SVI) is crucial in estimating indicators such as Sky Factor (SVF) and Green Index (GVI), but (1) approaches terminology differ across fields planning, transportation climate, potentially causing inconsistencies; (2) it unknown whether the regularly used panoramic imagery actually essential for tasks, or we can use only a portion of imagery, simplifying process; (3) do not know if non-panoramic (single-frame) photos typical crowdsourced platforms serve same purposes ones from services Google Baidu Maps their limited perspectives. This study first to examine comprehensively built form metrics, influence different practices on computing them multiple fields, usability normal (from consumer cameras). We overview run experiments 70 million images 5 cities analyse impact multitude variants SVI characterising physical environment mapping street canyons: few (e.g. fisheye) 96 scenarios perspective with variable directions, view, aspect ratios mirroring diverse smartphones dashcams. demonstrate that disparate give mostly comparable results metric R=0.82 R=0.98 metrics); often when using front-facing ultrawide camera), single-frame derive commercial counterparts. finding may simplify processes data also unlock value billions images, which are overlooked, benefit scores locations worldwide yet covered by services. Further, aggregated city-scale analyses, correspond closely.

Language: Английский

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Enhancing rooftop solar energy potential evaluation in high-density cities: A Deep Learning and GIS based approach

Energy and Buildings, Journal Year: 2023, Volume and Issue: 309, P. 113743 - 113743

Published: Nov. 11, 2023

Language: Английский

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Microclimate spatio-temporal prediction using deep learning and land use data

Building and Environment, Journal Year: 2024, Volume and Issue: 253, P. 111358 - 111358

Published: Feb. 28, 2024

Language: Английский

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Machine learning-based characterisation of urban morphology with the street pattern

Computers Environment and Urban Systems, Journal Year: 2024, Volume and Issue: 109, P. 102078 - 102078

Published: Feb. 15, 2024

Streets are a crucial part of the built environment, and their layouts, street patterns, widely researched contribute to quantitative understanding urban morphology. However, traditional pattern analysis only considers few broadly defined characteristics. It uses administrative boundaries grids as units that fail encompass diversity complexity networks. To address these challenges, this research proposes machine learning-based approach automatically recognise patterns employs an adaptive unit based on street-based local areas (SLAs). SLAs use network partitioning technique can adapt distinct networks, making it particularly suitable for different contexts. By calculating several streets' metrics performing hierarchical clustering method, streets with similar characters grouped under same pattern. A case study is carried out in six cities worldwide. The results show types rather diverse hierarchical, categorising them into clearly demarcated taxonomy challenging. derives set new morphometrics-based four major resemble conventional eleven sub-types significantly increase broader coverage capture structural differences across cities, such urban-suburban division number centres present. In conclusion, proposed morphometric characterise morphology has enhanced ability more information from environment while maintaining intuitiveness using patterns.

Language: Английский

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Learning visual features from figure-ground maps for urban morphology discovery

Computers Environment and Urban Systems, Journal Year: 2024, Volume and Issue: 109, P. 102076 - 102076

Published: Feb. 3, 2024

Language: Английский

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Predicting building characteristics at urban scale using graph neural networks and street-level context

Computers Environment and Urban Systems, Journal Year: 2024, Volume and Issue: 111, P. 102129 - 102129

Published: May 18, 2024

Language: Английский

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Building footprint data for countries in Africa: To what extent are existing data products comparable?

Computers Environment and Urban Systems, Journal Year: 2024, Volume and Issue: 110, P. 102104 - 102104

Published: March 22, 2024

Growth and developments in computing power, machine-learning algorithms satellite imagery spatiotemporal resolution have led to rapid automated feature-extraction. These methods been applied create geospatial datasets of features such as roads, trees building footprints, at a range spatial scales, with national multi-country now available open data from multiple sources. Building footprint is particularly useful applications including mapping population distributions, planning resource distribution campaigns humanitarian response. In settings well-developed systems, may complement existing authoritative sources, but data-scarce settings, they be the only source data. However, knowledge on degree which products are comparable can used interchangeably, impact selecting particular dataset subsequent analyses remains limited. For all countries Africa, we review analyse their similarities differences terms area count metrics. We explore variation between across sub-national administrative units different settlement types. Our results show that not interchangeable. There clear counts total footprints assessed products, well considerable heterogeneity coverage completeness.

Language: Английский

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