Predicting Urban Heat Island severity on the census-tract level using Bayesian networks

Sustainable Cities and Society, Год журнала: 2023, Номер 97, С. 104756 - 104756

Опубликована: Июнь 27, 2023

Язык: Английский

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Using Data-Driven Feature Engineering Algorithms to Determine the Most Critical Factors Contributing to the Urban Heat Island Effect Associated with Global Warming

Computing in Civil Engineering, Год журнала: 2024, Номер unknown, С. 1055 - 1062

Опубликована: Янв. 25, 2024

Urban clusters are areas with high building and infrastructure concentration limited green natural landscapes. Since buildings, bridges, roads, other absorb heat from the sun re-emit it to atmosphere, urban becoming "islands" that have higher temperature compared rural surrounding areas. This phenomenon is known as island (UHI) effect, which associated global warming generated increased human activities. While previous studies examined potential factors could affect heat-related challenges, little-to-no research prioritized these using a data-driven approach. To address this knowledge gap, paper determined most critical contribute UHIs feature selection- machine learning-based methods. First, dataset was collected developed for all census tracts in state of New Jersey relation 14 impact UHI effect. These considered independent variables, while average day intensity each tract dependent variable. Second, engineering algorithms were implemented extract or identify prominent factors. Third, ranked prioritized. The results prioritization ranking different based on multiple so robust conclusions be obtained. study serves useful reference decision-makers involved addressing challenges resulting by offering better understanding important need controlled managed.

Язык: Английский

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Models and methods for quantifying the benefits of engineered heat mitigation initiatives: A critical review

Urban Climate, Год журнала: 2023, Номер 51, С. 101654 - 101654

Опубликована: Авг. 24, 2023

Язык: Английский

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