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Li W, Sun R, He H, Yan M, Chen L. Perceptible landscape patterns reveal invisible socioeconomic profiles of cities. Sci Bull (Beijing) 2024:S2095-9273(24)00447-X. [PMID: 38969538 DOI: 10.1016/j.scib.2024.06.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 04/29/2024] [Accepted: 04/30/2024] [Indexed: 07/07/2024]
Abstract
Urban landscape is directly perceived by residents and is a significant symbol of urbanization development. A comprehensive assessment of urban landscapes is crucial for guiding the development of inclusive, resilient, and sustainable cities and human settlements. Previous studies have primarily analyzed two-dimensional landscape indicators derived from satellite remote sensing, potentially overlooking the valuable insights provided by the three-dimensional configuration of landscapes. This limitation arises from the high cost of acquiring large-area three-dimensional data and the lack of effective assessment indicators. Here, we propose four urban landscapes indicators in three dimensions (UL3D): greenness, grayness, openness, and crowding. We construct the UL3D using 4.03 million street view images from 303 major cities in China, employing a deep learning approach. We combine urban background and two-dimensional urban landscape indicators with UL3D to predict the socioeconomic profiles of cities. The results show that UL3D indicators differs from two-dimensional landscape indicators, with a low average correlation coefficient of 0.31 between them. Urban landscapes had a changing point in 2018-2019 due to new urbanization initiatives, with grayness and crowding rates slowing, while openness increased. The incorporation of UL3D indicators significantly enhances the explanatory power of the regression model for predicting socioeconomic profiles. Specifically, GDP per capita, urban population rate, built-up area per capita, and hospital count correspond to improvements of 25.0%, 19.8%, 35.5%, and 19.2%, respectively. These findings indicate that UL3D indicators have the potential to reflect the socioeconomic profiles of cities.
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Affiliation(s)
- Wenning Li
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Ranhao Sun
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Hongbin He
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ming Yan
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liding Chen
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
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Yang L, Li Q, Li Q, Zhao L, Luo Z, Liu Y. Different explanations for surface and canopy urban heat island effects in relation to background climate. iScience 2024; 27:108863. [PMID: 38361609 PMCID: PMC10867416 DOI: 10.1016/j.isci.2024.108863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/28/2023] [Accepted: 01/08/2024] [Indexed: 02/17/2024] Open
Abstract
The background climatic conditions and urban morphology greatly influence urban heat island effects (UHIs), but one-size-fits-all solutions are frequently employed to mitigate UHIs. Here, attribution models for surface UHIs (SUHIs) and canopy UHIs (CUHIs) were developed to describe UHI formation. The contribution of factors to SUHIs and CUHIs shows similar dependencies on background climate and urban morphology. Furthermore, the factors that mainly contributed to CUHIs were more complex, and anthropogenic heat was the more critical factor. Influence from urban morphology also highlights that there is no one-size-fit-all solution for heat mitigation at the neighborhood. In particular, maintaining a low building density should be prioritized, especially mitigating CUHIs. Moreover, it is more effective to prioritize urban irrigation maintenance over increasing green cover in arid regions but the opposite in humid regions. The work can provide scientific evidence to support developing general and regional guidelines for urban heat mitigation.
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Affiliation(s)
- Liu Yang
- State Key Laboratory of Green Building, Department of Architecture, Xi’an University of Architecture and Technology, Xi’an, Shaanxi 710055, P.R. China
| | - Qi Li
- State Key Laboratory of Green Building, Department of Architecture, Xi’an University of Architecture and Technology, Xi’an, Shaanxi 710055, P.R. China
- State Key Laboratory of Subtropical Building and Urban Science, School of Architecture, South China University of Technology, Guangzhou 510640, P.R. China
| | - Qiong Li
- State Key Laboratory of Subtropical Building and Urban Science, School of Architecture, South China University of Technology, Guangzhou 510640, P.R. China
| | - Lei Zhao
- Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Zhiwen Luo
- Welsh School of Architecture, Cardiff University, Cardiff, UK
| | - Yan Liu
- State Key Laboratory of Green Building, Department of Architecture, Xi’an University of Architecture and Technology, Xi’an, Shaanxi 710055, P.R. China
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Ren Y, Lafortezza R, Giannico V, Sanesi G, Zhang X, Xu C. The unrelenting global expansion of the urban heat island over the last century. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:163276. [PMID: 37019234 DOI: 10.1016/j.scitotenv.2023.163276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 05/27/2023]
Abstract
The past century has seen dramatic increases in global temperatures and mounting urbanization. As a result of these events, the urban heat island (UHI) effect has received growing attention in scientific research worldwide. A global search was initially conducted using a scientific literature database to collect all available relevant publications to understand how the UHI has been expanding worldwide and affecting more cities across different latitudes and altitudes. Subsequently, a semantic analysis was performed to extract city names. The literature search and analysis combined resulted in 6078 publications in which UHI was investigated in 1726 cities worldwide in the 1901 to 2022 time period. The cities were grouped into 'first appearance' and 'recurrent appearance'. Results show that UHI was studied in only 134 cities during the 90-year period from 1901 to 1992, with a remarkable growth over time in the number of cities where interest in UHI increased. Interestingly, the number of first appearances was always notably higher than the number of recurrent appearances. The Shannon evenness index was employed to identify the spatial locations (hotspots) across the globe where UHI-related research has been concentrated in multiple cities over the last 120 years. Finally, Europe was selected as a testbed for conducting an analysis to shed light on how economic, demographic, and environmental factors can impact UHI. Our study is unique for having demonstrated not only the rapid growth of cities affected by UHI globally but also the increasing and unrelenting expansion of UHI occurrences across different latitudes and altitudes over time. These novel findings will undoubtedly be of interest to scientists investigating the UHI phenomenon and its trends. Stakeholders will acquire a broader perspective and deeper understanding of UHI in order to engage in more effective urban planning to offset and mitigate the phenomenon's adverse effects in the context of increasing climate change and urbanization.
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Affiliation(s)
- Yaxue Ren
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via Amendola 165/A, 70126 Bari, Italy
| | - Raffaele Lafortezza
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via Amendola 165/A, 70126 Bari, Italy; The Key Laboratory for Silviculture and Conservation of Ministry of Education, Key Laboratory for Silviculture and Forest Ecosystem of State Forestry Grassland Administration, Research Center for Urban Forestry, Beijing Forestry University, Beijing 100083, China.
| | - Vincenzo Giannico
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via Amendola 165/A, 70126 Bari, Italy
| | - Giovanni Sanesi
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via Amendola 165/A, 70126 Bari, Italy
| | - Xinna Zhang
- The Key Laboratory for Silviculture and Conservation of Ministry of Education, Key Laboratory for Silviculture and Forest Ecosystem of State Forestry Grassland Administration, Research Center for Urban Forestry, Beijing Forestry University, Beijing 100083, China
| | - Chengyang Xu
- The Key Laboratory for Silviculture and Conservation of Ministry of Education, Key Laboratory for Silviculture and Forest Ecosystem of State Forestry Grassland Administration, Research Center for Urban Forestry, Beijing Forestry University, Beijing 100083, China
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He T, Wang K, Xiao W, Xu S, Li M, Yang R, Yue W. Global 30 meters spatiotemporal 3D urban expansion dataset from 1990 to 2010. Sci Data 2023; 10:321. [PMID: 37236983 DOI: 10.1038/s41597-023-02240-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/15/2023] [Indexed: 05/28/2023] Open
Abstract
Understanding the spatiotemporal dynamics of global 3D urban expansion over time is becoming increasingly crucial for achieving long-term development goals. In this study, we generated a global dataset of annual urban 3D expansion (1990-2010) using World Settlement Footprint 2015 data, GAIA data, and ALOS AW3D30 data with a three-step technical framework: (1) extracting the global constructed land to generate the research area, (2) neighborhood analysis to calculate the original normalized DSM and slope height of each pixel in the study area, and (3) slope correction for areas with a slope greater than 10° to improve the accuracy of estimated building heights. The cross-validation results indicate that our dataset is reliable in the United States(R2 = 0.821), Europe(R2 = 0.863), China(R2 = 0.796), and across the world(R2 = 0.811). As we know, this is the first 30-meter 3D urban expansion dataset across the globe, which can give unique information to understand and address the implications of urbanization on food security, biodiversity, climate change, and public well-being and health.
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Affiliation(s)
- Tingting He
- Department of Land Management, Zhejiang University, Hangzhou, 310058, China
| | - Kechao Wang
- Department of Land Management, Zhejiang University, Hangzhou, 310058, China
| | - Wu Xiao
- Department of Land Management, Zhejiang University, Hangzhou, 310058, China.
| | - Suchen Xu
- Department of Land Management, Zhejiang University, Hangzhou, 310058, China
| | - Mengmeng Li
- Department of Land Management, Zhejiang University, Hangzhou, 310058, China
- Swiss Federal Research Institute WSL, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
| | - Runjia Yang
- Department of Land Management, Zhejiang University, Hangzhou, 310058, China
| | - Wenze Yue
- Department of Land Management, Zhejiang University, Hangzhou, 310058, China
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Yang C, Zhao S. Scaling of Chinese urban CO 2 emissions and multiple dimensions of city size. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159502. [PMID: 36265639 DOI: 10.1016/j.scitotenv.2022.159502] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/11/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023]
Abstract
Cities are both the primary cause of global climate change and the key to the mitigation agenda. China's unprecedented urbanization has paralleled a growth in energy demand and urban areas have emerged as the crux of CO2 emissions reduction in China. There is a crucial need for policymakers to understand how CO2 emissions scale with city size and adopt economies of scale (cost savings) for mitigation, particularly through a multidimensional lens of city size. This study reveals a set of scaling relations between urban scope 1 CO2 emissions and five dimensions of city size in 340 Chinese cities, including population (POP), built-up area (BA), building height (BH), specific built-up area (SBA), and built-up volume (BV). The findings show that CO2 emissions in Chinese cities scale linearly with POP and BA but sublinearly with BA, SBA, and BV, and more diverse regimes exist across various geographic zones, population hierarchies, administrative hierarchies, and governance contexts. The prevalent sublinear scaling regime between CO2 emissions and SBA and BV demonstrates the potential importance of optimizing the vertical built-up landscapes for establishing a zero‑carbon society. Furthermore, the top 10 % and bottom 10 % performance of individual cities in emissions identified by the Scale-Adjusted Metropolitan Indicator (SAMI) (the smaller the better) highlights the imprints of the socioeconomic context (e.g., Low Carbon City Initiative) on the scaling of CO2 emissions in Chinese cities, which is critical for developing decarbonization strategies. Our multidimensional analysis can assist in the local-tailored low-carbon development of Chinese cities.
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Affiliation(s)
- Chen Yang
- College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China
| | - Shuqing Zhao
- College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China.
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