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  • 1
    Online Resource
    Online Resource
    Applications of machine learning and deep learning methods for climate change mitigation and adaptation
    SAGE Publications ; 2022
    In:  Environment and Planning B: Urban Analytics and City Science Vol. 49, No. 4 ( 2022-05), p. 1314-1330
    Details
    In: Environment and Planning B: Urban Analytics and City Science, SAGE Publications, Vol. 49, No. 4 ( 2022-05), p. 1314-1330
    Abstract: Climate change is a global issue that must be considered and addressed immediately. Many articles have been published on climate change mitigation and adaptation. However, new methods are required to explore the complexities of climate change and provide more efficient and effective adaptation and mitigation policies. With the advancement of technology, machine learning (ML) and deep learning (DL) methods have gained considerable popularity in many fields, including climate change. This paper aims to explore the most popular ML and DL methods that have been applied for climate change mitigation and adaptation. Another aim is to determine the most common mitigation and adaptation measures/actions in general, and in urban areas in particular, that have been studied using ML and DL methods. For this purpose, word frequency analysis and topic modeling, specifically the Latent Dirichlet allocation (LDA) as a ML algorithm, are used in this study. The results indicate that the most popular ML technique in both climate change mitigation and adaptation is the Artificial Neural Network. Moreover, among different research areas related to climate change mitigation and adaptation, geoengineering, and land surface temperature are the ones that have used ML and DL algorithms the most.
    Type of Medium: Online Resource
    ISSN: 2399-8083 , 2399-8091
    URL: Article
    DOI: 10.1177/23998083221085281
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2879402-3
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  • 2
    Online Resource
    Online Resource
    A GIS-Based Approach for Spatially-Explicit Sustainable Development Assessments in East Azerbaijan Province, Iran
    MDPI AG ; 2020
    In:  Sustainability Vol. 12, No. 24 ( 2020-12-12), p. 10413-
    Details
    In: Sustainability, MDPI AG, Vol. 12, No. 24 ( 2020-12-12), p. 10413-
    Abstract: We propose an efficient integrated approach of spatial decision-making systems and geographical information science for spatially explicit sustainable development mapping. The approach was developed, and its efficiency examined for sustainability assessment in East Azerbaijan Province, Iran. To achieve this goal, sustainable development indicators were employed through GIS decision rule and spatial analysis. Accordingly, 13 main criteria and 44 sub-criteria were identified and prepared as GIS dataset. The fuzzy analytical network process (FANP) method was employed to derive the criteria weights and their significance. We also applied the Global Sensitivity Analysis (GSA) for minimizing the uncertainties associated with the FANP weights. The Ordered Weighted Averaging (OWA) method was applied to aggregate the indicators and develop the sustainable development maps. Results confirmed that integrated GIS-based decision rules can be applied for any sustainable development mapping efficiently. Results of this research present an approach for sustainable development assessment and can be applied for similar research effectually. In the case of East Azerbaijan Province, the detailed results represent the unbalanced sustainable development within the different counties of this province. This requires taking necessary actions to ensure more balanced and just economic development in the province. The degree of sustainable development shows a significant spatial correlation with the industrial activities, employment, demography, poverty and infrastructure properties. The obtained results are of great importance for decision makers to identify efficient approaches in light of sustainable development mapping.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su122410413
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2518383-7
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  • 3
    Online Resource
    Online Resource
    Betting on negative emissions
    Springer Science and Business Media LLC ; 2014
    In:  Nature Climate Change Vol. 4, No. 10 ( 2014-10), p. 850-853
    Details
    In: Nature Climate Change, Springer Science and Business Media LLC, Vol. 4, No. 10 ( 2014-10), p. 850-853
    Type of Medium: Online Resource
    ISSN: 1758-678X , 1758-6798
    URL: Article
    DOI: 10.1038/nclimate2392
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2014
    detail.hit.zdb_id: 2603450-5
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  • 4
    Online Resource
    Online Resource
    Handling climate change education at universities: an overview
    Springer Science and Business Media LLC ; 2021
    In:  Environmental Sciences Europe Vol. 33, No. 1 ( 2021-12)
    Details
    In: Environmental Sciences Europe, Springer Science and Business Media LLC, Vol. 33, No. 1 ( 2021-12)
    Abstract: Climate change is a problem which is global in nature, and whose effects go across a wide range of disciplines. It is therefore important that this theme is taken into account as part of universities´ teaching and research programs. Methods A three-tiered approach was used, consisting of a bibliometric analysis, an online survey and a set of case studies, which allow a profile to be built, as to how a sample of universities from 45 countries handle climate change as part of their teaching programs. Results This paper reports on a study which aimed at identifying the extent to which matters related to climate change are addressed within the teaching and research practices at universities, with a focus on the training needs of teaching staff. It consists of a bibliometric analysis, combined with an online worldwide survey aimed at ascertaining the degree of involvement from universities in reducing their own carbon footprint, and the ways they offer training provisions on the topic. This is complemented by a set of 12 case studies from universities round the world, illustrating current trends on how universities handle climate change. Apart from reporting on the outcomes of the study, the paper highlights what some universities are doing to handle climate issues, and discusses the implications of the research. Conclusions The paper lists some items via which universities may better educate and train their students on how to handle the many challenges posed by climate change.
    Type of Medium: Online Resource
    ISSN: 2190-4707 , 2190-4715
    URL: Article
    DOI: 10.1186/s12302-021-00552-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2593962-2
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  • 5
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    An overview and thematic analysis of research on cities and the COVID-19 pandemic: Toward just, resilient, and sustainable urban planning and design
    Elsevier BV ; 2022
    In:  iScience Vol. 25, No. 11 ( 2022-11), p. 105297-
    Details
    In: iScience, Elsevier BV, Vol. 25, No. 11 ( 2022-11), p. 105297-
    Type of Medium: Online Resource
    ISSN: 2589-0042
    URL: Article
    DOI: 10.1016/j.isci.2022.105297
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2927064-9
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  • 6
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    Online Resource
    Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review
    Springer Science and Business Media LLC ; 2023
    In:  Energy Informatics Vol. 6, No. 1 ( 2023-04-05)
    Details
    In: Energy Informatics, Springer Science and Business Media LLC, Vol. 6, No. 1 ( 2023-04-05)
    Abstract: There have recently been intensive efforts aimed at addressing the challenges of environmental degradation and climate change through the applied innovative solutions of AI, IoT, and Big Data. Given the synergistic potential of these advanced technologies, their convergence is being embraced and leveraged by smart cities in an attempt to make progress toward reaching the environmental targets of sustainable development goals under what has been termed “environmentally sustainable smart cities.” This new paradigm of urbanism represents a significant research gap in and of itself. To fill this gap, this study explores the key research trends and driving factors of environmentally sustainable smart cities and maps their thematic evolution. Further, it examines the fragmentation, amalgamation, and transition of their underlying models of urbanism as well as their converging AI, IoT, and Big Data technologies and solutions. It employs and combines bibliometric analysis and evidence synthesis methods. A total of 2,574 documents were collected from the Web of Science database and compartmentalized into three sub-periods: 1991–2015, 2016–2019, and 2020–2021. The results show that environmentally sustainable smart cities are a rapidly growing trend that markedly escalated during the second and third periods—due to the acceleration of the digitalization and decarbonization agendas—thanks to COVID-19 and the rapid advancement of data-driven technologies. The analysis also reveals that, while the overall priority research topics have been dynamic over time—some AI models and techniques and environmental sustainability areas have received more attention than others. The evidence synthesized indicates that the increasing criticism of the fragmentation of smart cities and sustainable cities, the widespread diffusion of the SDGs agenda, and the dominance of advanced ICT have significantly impacted the materialization of environmentally sustainable smart cities, thereby influencing the landscape and dynamics of smart cities. It also suggests that the convergence of AI, IoT, and Big Data technologies provides new approaches to tackling the challenges of environmental sustainability. However, these technologies involve environmental costs and pose ethical risks and regulatory conundrums. The findings can inform scholars and practitioners of the emerging data-driven technology solutions of smart cities, as well as assist policymakers in designing and implementing responsive environmental policies.
    Type of Medium: Online Resource
    ISSN: 2520-8942
    URL: Article
    DOI: 10.1186/s42162-023-00259-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2942905-5
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  • 7
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    Online Resource
    Smart city indicators: Towards exploring potential linkages to disaster resilience abilities
    Asia-Pacific Network for Global Change Research ; 2022
    In:  APN Science Bulletin Vol. 12, No. 1 ( 2022-8-5), p. 75-89
    Details
    In: APN Science Bulletin, Asia-Pacific Network for Global Change Research, Vol. 12, No. 1 ( 2022-8-5), p. 75-89
    Abstract: Recent advances in Information and Communication Technologies (ICTs) have transformed all aspects of human life. Enabled by these advances, over the past few decades, many smart city initiatives have been developed across the world. Subsequently, various efforts have been made to develop indicators and frameworks for the assessment of smart cities. Generally, smart cities are expected to enhance the quality of life and provide solutions to deal with societal challenges. One major societal challenge is the increase in the frequency and intensity of disasters and adverse events. Therefore, smart cities are expected to contribute to enhancing disaster resilience. Integrating resilience thinking into smart city indicators and assessment frameworks is likely to promote better attention to the resilience contributions of smart cities. Against this background, through reviewing the literature, I first introduce a comprehensive list of indicators for assessing city smartness. Multiple indicators related to economy, people, governance, environment, mobility, living and data dimensions of a smart city are listed. Next, I explore if these indicators are aligned with the four resilience abilities: planning, absorption, recovery, and adaptation. Results show that smart city indicators are particularly linked to planning and absorption abilities. More attention to the recovery and adaptation abilities is, therefore, needed.
    Type of Medium: Online Resource
    ISSN: 2185-761X , 2522-7971
    URL: Journal
    URL: Article
    DOI: 10.30852/sb
    DOI: 10.30852/sb.2022.1873
    Language: Unknown
    Publisher: Asia-Pacific Network for Global Change Research
    Publication Date: 2022
    detail.hit.zdb_id: 3062662-6
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  • 8
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    Modeling and Analysis of Barriers to Climate Change Adaptation in Tehran
    MDPI AG ; 2020
    In:  Climate Vol. 8, No. 10 ( 2020-09-24), p. 104-
    Details
    In: Climate, MDPI AG, Vol. 8, No. 10 ( 2020-09-24), p. 104-
    Abstract: Since the impacts of climate change will last for many years, adaptation to this phenomenon should be prioritized in urban management plans. Although Tehran, the capital of Iran, has been subject to a variety of climate change impacts in recent years, appropriate adaptation measures to address them are yet to be taken. This study primarily aims to categorize the barriers to climate change adaptation in Tehran and analyze the way they interact with each other. The study was done in three steps: first, the focus group discussion (FGD) method was used to identify the barriers; next, the survey and the structural equation modeling (SEM) were used to validate the barriers, identify their importance, and examine their possible inter-relationships; and finally, the interpretive structural modeling (ISM) was applied to categorize and visualize the relationships between the barriers. Results show that barriers related to the ‘structure and culture of research’, ‘laws and regulations’, and ‘planning’ belong to the cluster of independent barriers and are of greater significance. The ‘social’ barrier and barriers related to ‘resources and resource management’ are identified as dependent barriers and are of lesser importance. Barriers related to ‘governance’, ‘awareness’, ‘education and knowledge’, ‘communication and interaction’, and ‘economy’ are identified at the intermediate cluster. The findings of this study can provide planners and decision makers with invaluable insights as to how to develop strategies for climate change adaptation in Tehran. Despite the scope of the study being confined to Tehran, its implications go far beyond this metropolis.
    Type of Medium: Online Resource
    ISSN: 2225-1154
    URL: Article
    DOI: 10.3390/cli8100104
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2720343-8
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  • 9
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    Comparative Analysis of the Surface Urban Heat Island (SUHI) Effect Based on the Local Climate Zone (LCZ) Classification Scheme for Two Japanese Cities, Hiroshima, and Sapporo
    MDPI AG ; 2023
    In:  Climate Vol. 11, No. 7 ( 2023-07-10), p. 142-
    Details
    In: Climate, MDPI AG, Vol. 11, No. 7 ( 2023-07-10), p. 142-
    Abstract: The Local Climate Zone (LCZ) classification system is used in this study to analyze the impacts of urban morphology on a surface urban heat island (SUHI). Our study involved a comparative analysis of SUHI effects in two Japanese cities, Sapporo and Hiroshima, between 2000 to 2022. We used geographical-information-system (GIS) mapping techniques to measure temporal LST changes using Landsat 7 and 8 images during the summer’s hottest month (August) and classified the study area into LCZ classes using The World Urban Database and Access Portal Tools (WUDAPT) method with Google Earth Pro. The urban thermal field variance index (UTFVI) is used to examine each LCZ’s thermal comfort level, and the SUHI heat spots (HS) in each LCZ classes are identified. The research findings indicate that the mean LST in Sapporo only experienced a 0.5 °C increase over the time, while the mean LST increased by 1.8 °C in Hiroshima City between 2000 and 2022. In 2000, open low-rise (LCZ 6) areas in Sapporo were the hottest, but by 2022, heavy industry (LCZ 10) became the hottest. In Hiroshima, compact mid-rise (LCZ 2) areas were the hottest in 2000, but by 2022, heavy-industry areas took the lead. The study found that LCZ 10, LCZ 8, LCZ E, and LCZ 3 areas in both Dfa and Cfa climate classifications had unfavorable UTFVI conditions. This was attributed to factors such as a high concentration of heat-absorbing materials, impervious surfaces, and limited green spaces. The majority of the SUHI HS and areas with the highest surface temperatures were situated near industrial zones and large low-rise urban forms in both cities. The study offers valuable insights into the potential long-term effects of various urban forms on the SUHI phenomenon.
    Type of Medium: Online Resource
    ISSN: 2225-1154
    URL: Article
    DOI: 10.3390/cli11070142
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2720343-8
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  • 10
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    Online Resource
    The Nexus between Digitalization and Sustainability a Scientometric Analysis
    Elsevier BV ; 2022
    In:  SSRN Electronic Journal
    Details
    In: SSRN Electronic Journal, Elsevier BV
    Type of Medium: Online Resource
    ISSN: 1556-5068
    URL: Article
    DOI: 10.2139/ssrn.4170538
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
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