LCZ framework and landscape metrics: Exploration of urban and peri-urban thermal environment emphasizing 2/3D characteristics

Building and Environment, Год журнала: 2024, Номер 254, С. 111370 - 111370

Опубликована: Март 7, 2024

Язык: Английский

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Artificial Intelligence in Environmental Monitoring: Advancements, Challenges, and Future Directions

Hygiene and Environmental Health Advances, Год журнала: 2024, Номер unknown, С. 100114 - 100114

Опубликована: Окт. 1, 2024

Язык: Английский

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Modeling and Estimating the Land Surface Temperature (LST) Using Remote Sensing and Machine Learning (Case Study: Yazd, Iran)

Remote Sensing, Год журнала: 2024, Номер 16(3), С. 454 - 454

Опубликована: Янв. 24, 2024

The pressing issue of global warming is particularly evident in urban areas, where thermal islands amplify the effect. Understanding land surface temperature (LST) changes crucial mitigating and adapting to effect heat islands, ultimately addressing broader challenge warming. This study estimates LST city Yazd, Iran, field high-resolution image data are scarce. assessed through parameters (indices) available from Landsat-8 satellite images for two contrasting seasons—winter summer 2019 2020, then it estimated 2021. modeled using six machine learning algorithms implemented R software (version 4.0.2). accuracy models measured root mean square error (RMSE), absolute (MAE), logarithmic (RMSLE), standard deviation different performance indicators. results show that gradient boosting model (GBM) algorithm most accurate estimating LST. albedo NDVI features with greatest impact on both (with 80.3% 11.27% importance) winter 72.74% 17.21% importance). 2021 showed acceptable seasons. GBM each seasons useful modeling based learning, support decision-making related spatial variations temperatures. method developed can help better understand island mitigation strategies improve human well-being enhance resilience climate change.

Язык: Английский

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Climate models for predicting precipitation and temperature trends in cities: A systematic review

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106171 - 106171

Опубликована: Янв. 1, 2025

Язык: Английский

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Unveiling nonlinear effects of built environment attributes on urban heat resilience using interpretable machine learning

Urban Climate, Год журнала: 2024, Номер 56, С. 102046 - 102046

Опубликована: Июнь 28, 2024

Язык: Английский

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Generative design of walkable urban cool spots using a novel heuristic GAN×GAN approach

Building and Environment, Год журнала: 2024, Номер 266, С. 112027 - 112027

Опубликована: Авг. 30, 2024

Язык: Английский

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How do the 3D urban morphological characteristics spatiotemporally affect the urban thermal environment? A case study of San Antonio

Building and Environment, Год журнала: 2024, Номер 261, С. 111738 - 111738

Опубликована: Июнь 12, 2024

Язык: Английский

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Configuration of public transportation stations in Hong Kong based on population density prediction by machine learning

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2025, Номер 136, С. 104339 - 104339

Опубликована: Янв. 13, 2025

Язык: Английский

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Simulating Land Surface Temperature Impacts of Proposed Land Use and Land Cover Plans Using an Integrated Deep Neural Network Approach

Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115437 - 115437

Опубликована: Фев. 1, 2025

Язык: Английский

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Assessing and predicting habitat quality under urbanization and climate pressures

Journal for Nature Conservation, Год журнала: 2025, Номер unknown, С. 126903 - 126903

Опубликована: Март 1, 2025

Язык: Английский

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