GABLE: A first fine-grained 3D building model of China on a national scale from very high resolution satellite imagery DOI Creative Commons
Xian Sun, Xingliang Huang, Yongqiang Mao

et al.

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 305, P. 114057 - 114057

Published: Feb. 27, 2024

Three-dimensional (3D) building models provide horizontal and vertical information of urban development patterns, which are significant to urbanization analysis, solar energy planning, carbon reduction sustainability. Despite that many popular products on a global or national scale proposed, these usually focus extraction height estimation at fairly coarse resolutions while categories not taken into consideration. In this study, we extend the previous work in two aspects involving introduction semantically fine-grained (i.e., 12 rooftop classes) spatially representations individual buildings with compact polygons. Specifically, develop novel framework for generation 3D models, including developing network joint classification, another parallel estimation, post-processing algorithm fusion results from independent networks. To train networks improve generalization, construct custom large-scale datasets addition existing Urban Building Classification (UBC) dataset 2023 IEEE Data Fusion Contest (DFC 2023) dataset. Finally, nation-scale fine-GrAined BuiLding modEl (GABLE) product is derived based Beijing-3 satellite images (0.5–0.8 m) our proposed framework. GABLE provides polygon, category value each instance. Further analyses conducted uncover distribution terms diversity, density. These demonstrate significance values GALBE, potentials far beyond these.

Language: Английский

A global map of local climate zones to support earth system modelling and urban-scale environmental science DOI Creative Commons
Matthias Demuzere, Jonas Kittner, Alberto Martilli

et al.

Earth system science data, Journal Year: 2022, Volume and Issue: 14(8), P. 3835 - 3873

Published: Aug. 29, 2022

Abstract. There is a scientific consensus on the need for spatially detailed information urban landscapes at global scale. These data can support range of environmental services, since cities are places intense resource consumption and waste generation concentrated infrastructure human settlement exposed to multiple hazards natural anthropogenic origin. In face climate change, also required explore future urbanization pathways design strategies in order lock long-term resilience sustainability, protecting from decisions that could undermine their adaptability mitigation role. To serve this purpose, we present 100 m-resolution map local zones (LCZs), universal typology distinguish areas holistic basis, accounting typical combination micro-scale land covers associated physical properties. The LCZ map, composed 10 built 7 cover types, generated by feeding an unprecedented number labelled training earth observation images into lightweight random forest models. Its quality assessed using bootstrap cross-validation alongside thematic benchmark 150 selected functional independent open-source surface cover, imperviousness, building height, heat. As each type with generic numerical descriptions key canopy parameters regulate atmospheric responses urbanization, availability globally consistent climate-relevant description important prerequisite supporting model development creating evidence-based climate-sensitive planning policies. This dataset be downloaded https://doi.org/10.5281/zenodo.6364594 (Demuzere et al., 2022a).

Language: Английский

Citations

168

A spatio-temporal analysis investigating completeness and inequalities of global urban building data in OpenStreetMap DOI Creative Commons
Benjamin Herfort, Sven Lautenbach, João Porto de Albuquerque

et al.

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

Citations

121

Global Building Morphology Indicators DOI Creative Commons
Filip Biljecki, Yoong Shin Chow

Computers Environment and Urban Systems, Journal Year: 2022, Volume and Issue: 95, P. 101809 - 101809

Published: May 4, 2022

Characterising and analysing urban morphology is a continuous task in data science, environmental analyses, many other domains. As the availability quality of on them have been increasing, buildings gained more attention. However, tools facilitating large-scale studies, together with an interdisciplinary consensus metrics, remain scarce often inadequate. We present Global Building Morphology Indicators (GBMI) — three-pronged contribution addressing such shortcomings: (i) comprehensive list hundreds building form multi-scale measures derived through systematic literature review; (ii) methodology tool for computation these metrics database suited big comparative release code freely open-source; (iii) we carry out computations using high performance computing, generating public repository quantifying selected areas around world, demonstrate their value novel analyses comparing morphological parameters across cities. GBMI introduces formalised, structured, modular, extensible method to compute, manage, disseminate indicators at large scale resolution, while precomputed dataset facilitates studies. The theory implementation traverse multiple scales: level, both individual contextual ones based encircling by buffers, aggregations several hierarchical administrative levels grids. Our open dataset, comprising billions records growing scope worldwide, most instance parametrising stock, supporting studies analytics range disciplines.

Language: Английский

Citations

84

Satellite mapping of urban built-up heights reveals extreme infrastructure gaps and inequalities in the Global South DOI Creative Commons
Yuyu Zhou, Xuecao Li, Wei Chen

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2022, Volume and Issue: 119(46)

Published: Nov. 7, 2022

Information on urban built-up infrastructure is essential to understand the role of cities in shaping environmental, economic, and social outcomes. The lack data heights over large areas has limited our ability characterize its spatial variations across world. Here, we developed a global atlas circa 2015 at 500-m resolution from Sentinel-1 Ground Range Detected satellite data. Results show extreme gaps per capita Global South compared with average, even larger average levels North. Per infrastructures some countries North are more than 30 times higher those South. results also that 45 combined, ∼16% population, roughly equivalent 114 South, ∼74% population. inequality infrastructure, as measured by an index, most countries, but largest Our analysis reveals scale demand required order meet sustainable development goals.

Language: Английский

Citations

81

Global urban structural growth shows a profound shift from spreading out to building up DOI Creative Commons
Steve Frolking, Richa Mahtta, Tom Milliman

et al.

Nature Cities, Journal Year: 2024, Volume and Issue: 1(9), P. 555 - 566

Published: Aug. 5, 2024

Abstract We present a new study examining the dynamics of global urban building growth rates over past three decades. By combining datasets for 1,550+ cities from several space-borne sensors—data scatterometers and settlement-built fraction based on Landsat-derived data—we find profound shifts in how expanded 1990s to 2010s. Cities had both increasing fractional cover microwave backscatter (correlating with volume), but decades, decreased most regions large cities, while increased essentially all cities. The divergence increase these metrics indicates shift lateral expansion more vertical development. This transition has happened different decades extents across world’s Growth rate increases were largest Asian toward development consequences material energy use, local climate living.

Language: Английский

Citations

24

Global Mapping of Three-Dimensional (3D) Urban Structures Reveals Escalating Utilization in the Vertical Dimension and Pronounced Building Space Inequality DOI Creative Commons

Xiaoping Liu,

Xinxin Wu, Xuecao Li

et al.

Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: March 1, 2024

Three-dimensional (3D) urban structures play a critical role in informing climate mitigation strategies aimed at the built environment and facilitating sustainable development. Regrettably, there exists significant gap detailed consistent data on 3D building space with global coverage due to challenges inherent collection model calibration processes. In this study, we constructed structure dataset (GUS-3D), including volume, height, footprint information, 500 m spatial resolution using extensive satellite observation products numerous reference samples. Our analysis indicated that total volume of buildings worldwide 2015 exceeded 1 × 1012 m3. Over 1985 period, observed slight increase magnitude growth (i.e., it increased from 166.02 km3 during 1985–2000 period 175.08 2000–2015 period), while expansion magnitudes two-dimensional (2D) (22.51 103 km2 vs. 13.29 km2) extent (157 133.8 notably decreased. This trend highlights intensive vertical utilization land. Furthermore, identified heterogeneity provision inequality across cities worldwide. is particularly pronounced many populous Asian cities, which has been overlooked previous studies economic inequality. The GUS-3D shows great potential deepen our understanding creates new horizons for studies.

Language: Английский

Citations

19

The Last Puzzle of Global Building Footprints—Mapping 280 Million Buildings in East Asia Based on VHR Images DOI Creative Commons
Qian Shi, Jiajun Zhu, Zhengyu Liu

et al.

Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: 4

Published: Jan. 1, 2024

Building, as an integral aspect of human life, is vital in the domains urban management and analysis. To facilitate large-scale planning applications, acquisition complete reliable building data becomes imperative. There are a few publicly available products that provide lot data, such Microsoft Open Street Map. However, East Asia, due to more complex distribution buildings scarcity auxiliary there lack these regions, hindering application Asia. Some studies attempt simulate information using incomplete local footprints through regression. reliance on inaccurate introduces cumulative errors, rendering this simulation highly unreliable, leading limitations achieving precise research Asian region. Therefore, we proposed comprehensive mapping framework view complexity conducted extraction 2,897 cities across 5 countries Asia yielded substantial dataset 281,093,433 buildings. The evaluation shows validity our product, with average overall accuracy 89.63% F1 score 82.55%. In addition, comparison existing further high quality completeness data. Finally, conduct spatial analysis revealing its value supporting urban-related research. for article can be downloaded from https://doi.org/10.5281/zenodo.8174931 .

Language: Английский

Citations

18

3D building reconstruction from single street view images using deep learning DOI Creative Commons

Hui En Pang,

Filip Biljecki

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2022, Volume and Issue: 112, P. 102859 - 102859

Published: June 17, 2022

3D building models are an established instance of geospatial information in the built environment, but their acquisition remains complex and topical. Approaches to reconstruct often require existing (e.g. footprints) data such as point clouds, which scarce laborious acquire, limiting expansion. In parallel, street view imagery (SVI) has been gaining currency, driven by rapid expansion coverage advances computer vision (CV), it not used much for generating city models. Traditional approaches that can use SVI reconstruction multiple images, while practice, only few street-level images provide unobstructed a building. We develop from single image using image-to-mesh techniques modified CV domain. regard three scenarios: (1) standalone single-view reconstruction; (2) aided top delineating footprint; (3) refinement models, i.e. we examine enhance level detail block (LoD1) common. The results suggest trained supporting able overall geometry building, first scenario may derive approximate mass useful infer urban form cities. evaluate demonstrating usefulness volume estimation, with mean errors less than 10% last two scenarios. As is now available most countries worldwide, including many regions do have footprint and/or data, our method rapidly cost-effectively without requiring any information. Obtaining hitherto did any, enable number analyses locally time.

Language: Английский

Citations

69

Measuring the coupling of built-up land intensity and use efficiency: An example of the Yangtze River Delta urban agglomeration DOI
Linlin Ruan, Tingting He, Wu Xiao

et al.

Sustainable Cities and Society, Journal Year: 2022, Volume and Issue: 87, P. 104224 - 104224

Published: Oct. 3, 2022

Language: Английский

Citations

59

3D building metrics for urban morphology DOI Creative Commons
Anna Labetski, Stelios Vitalis, Filip Biljecki

et al.

International Journal of Geographical Information Science, Journal Year: 2022, Volume and Issue: 37(1), P. 36 - 67

Published: Aug. 1, 2022

Urban morphology is important in a broad range of investigations across the fields city planning, transportation, climate, energy, and urban data science. Characterising buildings with set numerical metrics fundamental to studying form. Despite rapid developments 3D geoinformation science, growing availability, most studies simplify their 2D footprint, when taking height into account, they at assume one value per building, i.e. simple 3D. We take first step elevating building full/true 3D, uncovering use higher levels detail, account detailed shape building. foundation new research line on by providing comprehensive metrics, implementing them openly released software, generating an open dataset containing for 823,000 Netherlands, demonstrating case where clusters architectural patterns are analysed through time. Our experiments suggest added complement existing counterparts, reducing ambiguity, advanced insights. Furthermore, we provide comparative analysis using different detail models.

Language: Английский

Citations

48