Environment Development and Sustainability, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 30, 2024
Язык: Английский
Environment Development and Sustainability, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 30, 2024
Язык: Английский
Innovative Infrastructure Solutions, Год журнала: 2025, Номер 10(1)
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
3Building and Environment, Год журнала: 2022, Номер 228, С. 109884 - 109884
Опубликована: Дек. 2, 2022
Язык: Английский
Процитировано
47Theoretical and Applied Climatology, Год журнала: 2023, Номер 153(1-2), С. 367 - 395
Опубликована: Май 17, 2023
Язык: Английский
Процитировано
37Building and Environment, Год журнала: 2023, Номер 240, С. 110445 - 110445
Опубликована: Май 24, 2023
Язык: Английский
Процитировано
31Sustainability, 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
16Habitat International, Год журнала: 2024, Номер 150, С. 103129 - 103129
Опубликована: Июнь 17, 2024
Язык: Английский
Процитировано
13Remote 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
2Building and Environment, Год журнала: 2025, Номер unknown, С. 112705 - 112705
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
2International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105384 - 105384
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
2Energy Reports, Год журнала: 2025, Номер 13, С. 3760 - 3772
Опубликована: Март 27, 2025
Язык: Английский
Процитировано
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