Desert urban ecology: urban forest, climate, and ecosystem services DOI
Rıfat Olgun, Chingwen Cheng, Paul Coseo

и другие.

Environment Development and Sustainability, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 30, 2024

Язык: Английский

Thermal distribution of paver block with machine learning optimized design with alternative eco-friendly materials DOI

G. Uday Kiran,

G. Nakkeeran,

Dipankar Roy

и другие.

Innovative Infrastructure Solutions, Год журнала: 2025, Номер 10(1)

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

3

The influence of outdoor thermal comfort on acoustic comfort of urban parks based on plant communities DOI

Negar Mohammadzadeh,

Alireza Karimi, Robert D. Brown

и другие.

Building and Environment, Год журнала: 2022, Номер 228, С. 109884 - 109884

Опубликована: Дек. 2, 2022

Язык: Английский

Процитировано

47

Response of soil moisture and vegetation conditions in seasonal variation of land surface temperature and surface urban heat island intensity in sub-tropical semi-arid cities DOI

Shahfahad,

Ahmed Ali Bindajam, Mohd Waseem Naikoo

и другие.

Theoretical and Applied Climatology, Год журнала: 2023, Номер 153(1-2), С. 367 - 395

Опубликована: Май 17, 2023

Язык: Английский

Процитировано

37

Microclimatic analysis of outdoor thermal comfort of high-rise buildings with different configurations in Tehran: Insights from field surveys and thermal comfort indices DOI Creative Commons
Alireza Karimi,

A. Bayat,

Negar Mohammadzadeh

и другие.

Building and Environment, Год журнала: 2023, Номер 240, С. 110445 - 110445

Опубликована: Май 24, 2023

Язык: Английский

Процитировано

31

Towards a Sustainable Urban Future: A Comprehensive Review of Urban Heat Island Research Technologies and Machine Learning Approaches DOI Open Access
Siavash Ghorbany, Ming Hu, Siyuan Yao

и другие.

Sustainability, Год журнала: 2024, Номер 16(11), С. 4609 - 4609

Опубликована: Май 29, 2024

The urban heat island (UHI) is a crucial factor in developing sustainable cities and societies. Appropriate data collection, analysis, prediction are essential first steps studying the effects of UHI. This research systematically reviewed papers related to UHI that have used on-site collection United States Canada predicting analyzing this effect these regions. To achieve goal, study extracted 330 articles from Scopus Web Science and, after selecting papers, 30 detail 1998 2023. findings paper indicated methodological shift traditional sensors loggers towards more innovative customized technologies. Concurrently, reveals growing trend using machine learning, moving supportive direct predictive roles techniques like neural networks Bayesian networks. Despite maturation due developments, they also present challenges technology complexity integration. review emphasizes need for future focus on accessible, accurate Moreover, interdisciplinary approaches addressing an era climate change.

Язык: Английский

Процитировано

16

Urban expansion and vegetation dynamics: The role of protected areas in preventing vegetation loss in a growing mega city DOI

Shahfahad,

Swapan Talukdar, Mohd Waseem Naikoo

и другие.

Habitat International, Год журнала: 2024, Номер 150, С. 103129 - 103129

Опубликована: Июнь 17, 2024

Язык: Английский

Процитировано

13

Harnessing Multi-Source Data and Deep Learning for High-Resolution Land Surface Temperature Gap-Filling Supporting Climate Change Adaptation Activities DOI Creative Commons

Katja Kustura,

Daniel J. Conti,

Matthias Sammer

и другие.

Remote Sensing, Год журнала: 2025, Номер 17(2), С. 318 - 318

Опубликована: Янв. 17, 2025

Addressing global warming and adapting to the impacts of climate change is a primary focus adaptation strategies at both European national levels. Land surface temperature (LST) widely used proxy for investigating climate-change-induced phenomena, providing insights into radiative properties different land cover types impact urbanization on local characteristics. Accurate continuous estimation across large spatial regions crucial implementation LST as an essential parameter in mitigation strategies. Here, we propose deep-learning-based methodology using multi-source data including Sentinel-2 imagery, cover, meteorological data. Our approach addresses common challenges satellite-derived data, such gaps caused by cloud image border limitations, grid-pattern sensor artifacts, temporal discontinuities due infrequent overpasses. We develop regression-based convolutional neural network model, trained ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer Experiment Space Station) mission which performs pixelwise predictions 5 × patches, capturing contextual information around each pixel. This method not only preserves ECOSTRESS’s native resolution but also fills enhances coverage. In non-gap areas validated against ground truth model achieves with least 80% all pixel errors falling within ±3 °C range. Unlike traditional satellite-based techniques, our leverages high-temporal-resolution capture diurnal variations, allowing more robust time periods. The model’s performance demonstrates potential integrating urban planning, resilience strategies, near-real-time heat stress monitoring, valuable resource assess visualize development use changes.

Язык: Английский

Процитировано

2

Granular Mapping of UHI and Heatwave Effects: Implications for Building Performance and Urban Resilience DOI
Alireza Karimi, David Moreno-Rangel, Antonio García Martínez

и другие.

Building and Environment, Год журнала: 2025, Номер unknown, С. 112705 - 112705

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2

Urban Heat Stress in the context of socioeconomic and environmental challenges: Heat risk analysis and online surveys in northwestern Portugal DOI Creative Commons
Hélder Silva Lopes,

P. Silva,

Bianca Lopes Lima Pinto

и другие.

International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105384 - 105384

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

2

Urban heat islands and energy consumption patterns: Evaluating renewable energy strategies for a sustainable future DOI
Muhammad Khalid Anser, Abdelmohsen A. Nassani,

Khalid M. Al-Aiban

и другие.

Energy Reports, Год журнала: 2025, Номер 13, С. 3760 - 3772

Опубликована: Март 27, 2025

Язык: Английский

Процитировано

1