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

Innovative Infrastructure Solutions, Journal Year: 2025, Volume and Issue: 10(1)

Published: Jan. 1, 2025

Language: Английский

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

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(2), P. 318 - 318

Published: Jan. 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.

Language: Английский

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Urban Heat Stress in the context of socioeconomic and environmental challenges: Heat risk analysis and online surveys in northwestern Portugal

International Journal of Disaster Risk Reduction, Journal Year: 2025, Volume and Issue: unknown, P. 105384 - 105384

Published: March 1, 2025

Language: Английский

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

Building and Environment, Journal Year: 2022, Volume and Issue: 228, P. 109884 - 109884

Published: Dec. 2, 2022

Language: Английский

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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

Theoretical and Applied Climatology, Journal Year: 2023, Volume and Issue: 153(1-2), P. 367 - 395

Published: May 17, 2023

Language: Английский

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Microclimatic analysis of outdoor thermal comfort of high-rise buildings with different configurations in Tehran: Insights from field surveys and thermal comfort indices

Building and Environment, Journal Year: 2023, Volume and Issue: 240, P. 110445 - 110445

Published: May 24, 2023

Language: Английский

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Towards a Sustainable Urban Future: A Comprehensive Review of Urban Heat Island Research Technologies and Machine Learning Approaches

Sustainability, Journal Year: 2024, Volume and Issue: 16(11), P. 4609 - 4609

Published: May 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.

Language: Английский

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

Habitat International, Journal Year: 2024, Volume and Issue: 150, P. 103129 - 103129

Published: June 17, 2024

Language: Английский

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Granular Mapping of UHI and Heatwave Effects: Implications for Building Performance and Urban Resilience

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112705 - 112705

Published: Feb. 1, 2025

Language: Английский

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Urban heat islands and energy consumption patterns: Evaluating renewable energy strategies for a sustainable future

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 3760 - 3772

Published: March 27, 2025

Language: Английский

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