Sustainable Cities and Society最新文献

Scenario forecasting of carbon neutrality by combining the LEAP model and future land-use simulation: An empirical study of Shenzhen, China

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-09 DOI: 10.1016/j.scs.2025.106367

Xinyan Zhao , Zhijie Rao , Jinyao Lin , Xinchang Zhang

{"title":"Scenario forecasting of carbon neutrality by combining the LEAP model and future land-use simulation: An empirical study of Shenzhen, China","authors":"Xinyan Zhao , Zhijie Rao , Jinyao Lin , Xinchang Zhang","doi":"10.1016/j.scs.2025.106367","DOIUrl":"10.1016/j.scs.2025.106367","url":null,"abstract":"<div><div>Forecasting future carbon emissions and carbon stocks under the influence of land-use changes will offer guidance for achieving urban carbon neutrality. However, a gap exists in the systematic combination of carbon emission forecasting and carbon stock forecasting to simulate the carbon neutrality path. Therefore, we introduced a novel method for scenario forecasting of carbon neutrality, which can integrate dynamic future land-use and NPP data to forecast carbon stocks. CCUS technology was also considered. Shenzhen, a Chinese city with high carbon emissions, was chosen as our case study area. First, the LEAP model was employed for forecasting future carbon emissions. Subsequently, the PLUS method was utilized for forecasting land-use evolution. Then, the carbon stocks were estimated on the basis of land-use forecasting and NPP. Finally, we explored the potential of CCUS for realizing carbon neutrality under integrated carbon emission and land-use scenarios. The results indicate that Shenzhen's future carbon emissions exhibit a tendency of an initial increase, followed by a decline. Due to the increase in ecological land, vegetation carbon stocks may increase slightly in farmland protection and ecological security scenarios. With the support of CCUS technology, the four scenarios are expected to achieve carbon neutrality before 2050. The scenarios presented in this study align more closely with future development trajectories and actual conditions, making them more informative for policy-making. In summary, the proposed framework would facilitate a comprehensive understanding of the pathways to achieving carbon neutrality goals.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106367"},"PeriodicalIF":10.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-resolution outdoor heat-risk modeling for city central areas with applications to Tokyo and Lyon 城市中心区高分辨率室外热风险建模在东京和里昂的应用

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-09 DOI: 10.1016/j.scs.2025.106344

Alvin C.G. Varquez , Janat Taerakul , Florent Renard , Lucille Alonso , Sunkyung Choi , Ryoga Hiroki , Yasunobu Ashie , Eiko Kumakura , Makoto Okumura , Shinya Hanaoka , Atsushi Inagaki , Manabu Kanda

{"title":"High-resolution outdoor heat-risk modeling for city central areas with applications to Tokyo and Lyon","authors":"Alvin C.G. Varquez , Janat Taerakul , Florent Renard , Lucille Alonso , Sunkyung Choi , Ryoga Hiroki , Yasunobu Ashie , Eiko Kumakura , Makoto Okumura , Shinya Hanaoka , Atsushi Inagaki , Manabu Kanda","doi":"10.1016/j.scs.2025.106344","DOIUrl":"10.1016/j.scs.2025.106344","url":null,"abstract":"<div><div>Owing to climate change, urbanization, and population shifts, heat risks in cities are projected to rise. This work aims to introduce a flexible approach for mapping outdoor heat risks by individually constructing, normalizing, and combining its four key components – hazard, exposure, vulnerability, and adaptive capacity – as recommended by the International Panel on Climate Change. The methodology was demonstrated by constructing 500-m hourly-varying outdoor heat risk maps of elderly population over two city-central areas (Tokyo and Lyon) of distinct geophysical features and demographic conditions during a summer day in 2022. The hazard component was described using a 2-m simulation of heat-stress index (wet-bulb globe temperature), which accounts for urban surface details. Vulnerability, exposure, and adaptive capacity were then defined as functions of hourly 500-m population changes, open-space ratios, and proximity to health centers, respectively. During the selected dates in Tokyo’s and Lyon’s central areas, significant spatiotemporal variations emerged in daytime elderly heat risk due to their unique urban landscapes, local climates, and senior population mobility patterns. Meanwhile, reductions in elderly population movement resulted in low outdoor vulnerability despite the peak heat hazard condition during the noontime. This work highlights the usefulness of the proposed approach, the prevailing complexities of detailed risk mapping over city-central areas, and the utility potential of increasing high-quality geospatial datasets.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106344"},"PeriodicalIF":10.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Urban ventilation network identification to mitigate heat island effect

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-08 DOI: 10.1016/j.scs.2025.106364

Aokang Xu , Jing Shi , Lefan Zhao , Tianqi Ji , Xiangyun Meng

{"title":"Urban ventilation network identification to mitigate heat island effect","authors":"Aokang Xu , Jing Shi , Lefan Zhao , Tianqi Ji , Xiangyun Meng","doi":"10.1016/j.scs.2025.106364","DOIUrl":"10.1016/j.scs.2025.106364","url":null,"abstract":"<div><div>Global warming and rapid urbanization aggravate the urban heat island (HI) effect significantly, and alleviating the HI effect can promote urban sustainable development and improve residents' livability. Relevant studies mainly use the single perspective of cold island (CI) or HI network to discuss the methods of mitigating HI, which ignores the potential cold and hot interaction process between CI and HI driven by complex temperature gradient inside the city, limiting the comprehensiveness of mitigation strategies to a certain extent. Therefore, it is particularly critical to establish the potential connection between CI and HI to achieve systematic optimization of urban thermal environment. Taking the main urban area of Xi'an as the research object, we combined morphological spatial pattern analysis (MSPA), landscape connectivity, circuit theory and robustness analysis to construct CI ventilation network (CIVN) and cold heat ventilation network (CHVN) from multiple perspectives and levels. CIVN identifies and strengthens the urban cold system, while CHVN establishes the airflow interaction path between CI and HI. This also reflects the impact of HI on CI, which has a far greater impact on CI than the impact from CI airflow. CIVN robustness decreases after CI is impacted by heat flow, while CIVN robustness is improved by adding CI according to urban planning and key nodes of VN. In addition, priority protection for CI with low LSI and high node degrees (Low bearing capacity and high heat flow threat) can prevent CIVN degradation. This study is expected to provide new ideas for mitigating urban HI effects, and also provide guidance for making climate-resilient urban planning and promoting urban sustainable development.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106364"},"PeriodicalIF":10.5,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Urban cities heatwaves vulnerability and societal responses towards hazard zoning: Social media real-time based heatwave detection using deep learning

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-05 DOI: 10.1016/j.scs.2025.106360

Shan-e-hyder Soomro , Muhammad Waseem Boota , Gul-e-Zehra Soomro , Mairaj Hyder Alias Aamir Soomro , Caihong Hu , Yinghai Li , Jiali Guo , Junaid Abdul Wahid

{"title":"Urban cities heatwaves vulnerability and societal responses towards hazard zoning: Social media real-time based heatwave detection using deep learning","authors":"Shan-e-hyder Soomro , Muhammad Waseem Boota , Gul-e-Zehra Soomro , Mairaj Hyder Alias Aamir Soomro , Caihong Hu , Yinghai Li , Jiali Guo , Junaid Abdul Wahid","doi":"10.1016/j.scs.2025.106360","DOIUrl":"10.1016/j.scs.2025.106360","url":null,"abstract":"<div><h3>Study region</h3><div>Pakistan.</div></div><div><h3>Study focus</h3><div>Enhanced social media data accessibility facilitates the effective detection of disaster-associated information, exemplified by urban heatwaves. Social media elucidates human behavior and geographical trends in Sindh Province, Pakistan, amidst intensifying extreme heat events. The utilization of this data facilitates a comprehensive examination of heatwaves, thereby enhancing the real-time management and mitigation strategies within urban environments.</div></div><div><h3>Innovative insights</h3><div>This study introduces an innovative framework for the real-time extraction and analysis of heatwave-related data from Facebook in areas impacted by disasters. This framework employs topic modeling and transfer learning for examining heatwave disaster dynamics. It extracts temperature and humidity information from both textual content and visual representation using state-of-the-art deep learning techniques and fuses these insights via decision-making processes. A fine-grained location corpus specific to urban heatwaves was developed using a named entity recognition (NER) model. The BERT-BiLSTM-CRF model was then utilized to extract heatwave data accurately. In the case of southeastern Pakistan, the extracted heatwave points aligned with 86 % of officially documented incidents, predominantly occurring near urban areas. This framework improves situational awareness and supports real-time spatiotemporal analyses of the urban heatwaves, thus providing a new approach for effective disaster management and response.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106360"},"PeriodicalIF":10.5,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

R-ECO: An R script to measure the supply of urban ecosystem services in Europe

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-03 DOI: 10.1016/j.scs.2025.106358

Daniel Jato-Espino , Marina B. Jensen

{"title":"R-ECO: An R script to measure the supply of urban ecosystem services in Europe","authors":"Daniel Jato-Espino , Marina B. Jensen","doi":"10.1016/j.scs.2025.106358","DOIUrl":"10.1016/j.scs.2025.106358","url":null,"abstract":"<div><div>Implementing Green Infrastructure (GI) can help achieve sustainable urbanism by addressing challenges such as land cover and climate changes through the supply of Ecosystem Services (ES). However, an accurate yet accessible means of determining the ES at small urban scales is lacking. In response, this research developed a tool to automate the measurement of ES supply at the district level, with a focus on the role of GI. This led to R-ECO, a script developed in the R's free software environment to process fifteen indicators representing provisioning (e.g., food supply, timber production), regulating (e.g., climate regulation, air purification, water flow control), supporting (e.g., biodiversity conservation, habitat connectivity) and cultural (e.g., recreation, noise management, aesthetic value) ES using spatial and statistical functions. Using Multi-Criteria Decision Analysis (MCDA) methods, the proposed indicators were combined to result in a single metric reporting the ES of urban districts. The tool was valid as designed for Europe as it is fed with data from open repositories on that continent. Still, it can be adapted internationally by incorporating region-specific or global datasets, thereby allowing for urban sustainability assessments in diverse geographical contexts. Testing R-ECO using Copenhagen (Denmark) as a case study proved its usefulness to identify areas that are deficient in ES due to various reasons such as poor climate regulation capacity or insufficiently accessible natural and seminatural areas. Therefore, public institutions concerned with the sustainability of their cities can turn to R-ECO to support the deployment of ES through the implementation of GI.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106358"},"PeriodicalIF":10.5,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating the quantitative impact of the vegetation indices on the urban thermal comfort based on machine learning: A case study of the Qinhuai River Basin, China

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-03 DOI: 10.1016/j.scs.2025.106357

Jianqing Zhao , Chunguang Hu , Zhuoqi Li , Maomao Zhang , Houbao Fan , Kaili Li , Ruidi Yuan

{"title":"Investigating the quantitative impact of the vegetation indices on the urban thermal comfort based on machine learning: A case study of the Qinhuai River Basin, China","authors":"Jianqing Zhao , Chunguang Hu , Zhuoqi Li , Maomao Zhang , Houbao Fan , Kaili Li , Ruidi Yuan","doi":"10.1016/j.scs.2025.106357","DOIUrl":"10.1016/j.scs.2025.106357","url":null,"abstract":"<div><div>Rapid urbanization and economic development in China have reshaped land cover and impacted urban Thermal Comfort (TC). This study examines the relationship between Vegetation Indices (VIs) and TC in the Qianhai River Basin using multi-temporal remote sensing data and Machine Learning (ML) models. TC classifications were derived through inversion and analyzed using the standard deviation ellipse and Moran's I. This study uses Random Forest Regression (RFR) to evaluate the predictive performance of 14 vegetation indices. The results revealed that in 2022, high TC areas (917.52 km²) were mostly found in green areas, farmlands, and water bodies, while low TC areas were concentrated in urban and industrial zones. VIs such as the Normalized Difference Moisture Index (NDMI), Shortwave Infrared Vegetation Index (SWIRVI), and Global Environment Monitoring Index, which reflect vegetation moisture and growth, were key in characterizing TC. The study refines the mechanism of VIs on the scale of urban functional areas, which fills the deficiency of neglecting the differences of functional areas in previous studies. SWRWI and Vegetation Growth Period Index were more relevant in agricultural zones, whereas indices emphasizing impervious surfaces better represented TC in urban areas. Identifying the most impactful VIs provides valuable insights for developing targeted urban planning strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106357"},"PeriodicalIF":10.5,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing biogenic carbon storage at urban scale through urban building energy modelling

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-03 DOI: 10.1016/j.scs.2025.106355

Maryam Meshkinkiya , Alina Galimshina , Illias Hischier , Arno Schlueter

{"title":"Assessing biogenic carbon storage at urban scale through urban building energy modelling","authors":"Maryam Meshkinkiya , Alina Galimshina , Illias Hischier , Arno Schlueter","doi":"10.1016/j.scs.2025.106355","DOIUrl":"10.1016/j.scs.2025.106355","url":null,"abstract":"<div><div>Curbing embodied emissions is essential for reducing greenhouse gas emissions. In the building construction sector, bio-based materials have shown promising solutions in reducing embodied emissions while offering carbon storage potential. This study presents a framework to assess the potential of biogenic carbon storage at the urban scale. A district in Zurich, Switzerland, is selected as the case study, incorporating Swiss-based life cycle data for building construction along with current and projected grid carbon intensities. Our work expands the CityEnergyAnalyst tool to include biogenic carbon data in building archetypes. The effects of retrofit on operational and embodied emissions are evaluated using three representative scenarios: low, intermediate, and intensive retrofit rates. The embodied emissions and the potential for carbon storage are assessed by comparing conventional, low-carbon, and carbon-negative materials. The temporal patterns of emissions show that grid decarbonization and building electrification are essential for reaching net-zero emissions by 2060. Furthermore, increasing the retrofit rate notably curbs operational emissions regardless of the grid decarbonization scenario. For instance, increasing the retrofit rate from 1.0 % to 1.9 % could reduce operational emissions by 16 %. Retrofitting the walls alone could store up to 360 ktCO<sub>2</sub> eq. in a district of approximately 2200 buildings. The study underlines that the properties of a carbon-negative material—such as its conductivity and density—play a significant role in biogenic carbon storage capabilities. The findings indicate that a carbon-negative material could boost biogenic carbon storage six-fold compared to low-carbon alternatives.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106355"},"PeriodicalIF":10.5,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven neighborhood-level carbon emission accounting models and decarbonization strategies: Empirical study on Central Shenyang City

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-02 DOI: 10.1016/j.scs.2025.106346

Xiaobin Ye , Zhenyu Wang , Kexin Cui , Shaoxuan Meng , Xin Ning

{"title":"Data-driven neighborhood-level carbon emission accounting models and decarbonization strategies: Empirical study on Central Shenyang City","authors":"Xiaobin Ye , Zhenyu Wang , Kexin Cui , Shaoxuan Meng , Xin Ning","doi":"10.1016/j.scs.2025.106346","DOIUrl":"10.1016/j.scs.2025.106346","url":null,"abstract":"<div><div>Neighborhood is the basic unit for fine-grained management of urban carbon emissions and the best place to apply low-carbon concepts and technologies. However, accurately calculating carbon emissions at this level remains a challenge, complicating the identification of effective decarbonization strategies. This research proposes utilizing urban land use at the neighborhood level as a decarbonization unit and taking Central Shenyang City as an example to measure the carbon emission characteristics of different sectors by integrating multi-source data. Then, based on the carbon emission intensity of the lands, establishing a baseline for decarbonization and measuring its effectiveness accordingly. The results show that in Central Shenyang City, 90.99 % of CO<sub>2</sub> emissions come from the building and transportation sectors, with carbon sinks offsetting a mere 2.20 % of these emissions. Commercial land has the highest overall level of carbon emissions per unit area, while industrial land records the highest per capita carbon emissions. In addition, there is a significant imbalance in the spatial distribution of carbon emissions among various sectors. Through a graded decarbonization strategy based on the baseline indicators, an overall decarbonization of 19.79 % in carbon emissions is achieved. This study introduces a data-driven model with potential applications in other regions.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106346"},"PeriodicalIF":10.5,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the seasonal impacts of morphological spatial pattern of green spaces on the urban heat island

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-01 DOI: 10.1016/j.scs.2025.106352

Jialong Xu , Yingying Jin , Yun Ling , Yiyan Sun , Yuan Wang

{"title":"Exploring the seasonal impacts of morphological spatial pattern of green spaces on the urban heat island","authors":"Jialong Xu , Yingying Jin , Yun Ling , Yiyan Sun , Yuan Wang","doi":"10.1016/j.scs.2025.106352","DOIUrl":"10.1016/j.scs.2025.106352","url":null,"abstract":"<div><div>Studying the influencing factors of urban heat island (UHI) is the key to improving the urban thermal environment. Research has shown that the spatial pattern of green space is an essential factor, but the impact of morphological spatial pattern of green spaces on UHI intensity has not yet been thoroughly explored. Compared to traditional landscape pattern indices, Morphological Spatial Pattern Analysis (MSPA) is more accurate and efficient in identifying different morphological types. Therefore, this study takes Nanjing, China as a case study and combines MSPA with landscape indices to analyze the spatial patterns of seven green space morphological types. Pearson's coefficients and Random Forest models were used to quantitatively assess their relationships with UHI intensity in different seasons. The results indicate that all green space morphological types are negatively correlated with UHI intensity, with the core being the most critical type to mitigate UHI, followed by perforation, and islet showing the weakest cooling capacity. Moreover, the impact of each green space morphological type on UHI exhibits seasonal differences, with summer being most prominent. The study further reveals that rational optimization of key morphological elements can significantly enhance their cooling effects. Expanding the core area is the most rewarding option to improve cooling, while improving the core connectivity, increasing the edge length and density of the core also yields high returns. Additionally, increasing the density, number, aggregation, and shape complexity of perforation is an effective strategy. In contrast, additional islets are unlikely to yield a significant benefit. These findings highlight that it is crucial to rationally consider their morphological spatial pattern in the actual planning and management of green spaces. This study provides valuable insights for formulating more refined UHI mitigation strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106352"},"PeriodicalIF":10.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Precise mitigation strategies for urban heat island effect in Hong Kong's new towns using automated machine learning

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-04-01 DOI: 10.1016/j.scs.2025.106350

Yiyan Li , Hongsheng Zhang , Yinyi Lin , Jing Ling , Huiyuan Xue , Peizhuo Guo

{"title":"Precise mitigation strategies for urban heat island effect in Hong Kong's new towns using automated machine learning","authors":"Yiyan Li , Hongsheng Zhang , Yinyi Lin , Jing Ling , Huiyuan Xue , Peizhuo Guo","doi":"10.1016/j.scs.2025.106350","DOIUrl":"10.1016/j.scs.2025.106350","url":null,"abstract":"<div><div>New town developments aim to enhance the spatial layout and quality of living environments in metropolitan areas. These areas are vulnerable to the urban heat island (UHI) effect owing to high-density development and poor long-term planning. However, few studies have investigated the spatial distribution of the influence of built environments on UHI, limiting the ability of urban planners to develop targeted mitigation strategies. To address this gap, we analyzed the complex spatial relationship between land surface temperature (LST), an important indicator of UHI, and the built environment in all new towns in Hong Kong. We employed remote sensing images, street view images, geographical information science (GIS) data, and land-use data with automated machine learning to model the LST-built environmental relationship at various spatial scales, using Shapley Additive Explanations (SHAP) to interpret the model to show the spatial distribution of the influence of the built environment on UHI. Our best model was the Extreme Gradient Boosting Machine model with a 210-m grid R-squared value of 0.79. We found that 1) the land-use feature class had the most significant influence on LST, and 2) there was spatial heterogeneity among the major contributors to UHI. The refined UHI attribution analysis method proposed in this study enables precise modeling for smart and sustainable city planning. (211 words)</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106350"},"PeriodicalIF":10.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0