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Dependence between urban morphology and outdoor air temperature: A tropical campus study using random forests algorithm

https://doi.org/10.1016/j.scs.2020.102200
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Sky view factor analysis of street canyons and its implications for daytime intra‐urban air temperature differentials in high‐rise, high‐density urban areas of Hong Kong: a GIS‐based simulation approach
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Landscape configuration and urban heat island effects: assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona
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Environmental study of the impact of greenery in an institutional campus in the tropics
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Urban design factors influencing heat island intensity in high-rise high-density environments of Hong Kong
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Summertime heat island intensities in three high-rise housing quarters in inner-city Shanghai China: Building layout, density and greenery
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Study on correlation between air temperature and urban morphology parameters in built environment in northern China
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Urban tree design approaches for mitigating daytime urban heat island effects in a high-density urban environment
inferredcites →https://doi.org/10.1016/j.enbuild.2017.05.024openalex-snapshot
A customizable framework for computing sky view factor from large-scale 3D city models
inferredcites →https://doi.org/10.1016/j.envsci.2016.08.012openalex-snapshot
The social and spatial distribution of temperature-related health impacts from urban heat island reduction policies
inferredcites →https://doi.org/10.1016/j.habitatint.2007.02.006openalex-snapshot
The influence of land use on the urban heat island in Singapore
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CFD simulation of pollutant dispersion around isolated buildings: On the role of convective and turbulent mass fluxes in the prediction accuracy
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Spatial statistical analysis and simulation of the urban heat island in high-density central cities
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Mapping maximum urban air temperature on hot summer days
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A review on modeling and simulation of building energy systems
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A new method to quantify surface urban heat island intensity
inferredcites →https://doi.org/10.1016/j.scs.2015.04.001openalex-snapshot
Recent challenges in modeling of urban heat island
inferredcites →https://doi.org/10.1016/j.scs.2016.05.002openalex-snapshot
Toward advanced representations of the urban microclimate in building performance simulation
inferredcites →https://doi.org/10.1016/j.scs.2017.06.012openalex-snapshot
Thermal environment assessment around bodies of water in urban canyons: A scale model study
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inferredcites →https://doi.org/10.1016/s0169-2046(02)00191-3openalex-snapshot
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inferredcites →https://doi.org/10.1016/s0378-7788(99)00018-3openalex-snapshot
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inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
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inferredcites →https://doi.org/10.1023/b:clim.0000013675.66917.15openalex-snapshot
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inferredcites →https://doi.org/10.1080/0964401042000310178openalex-snapshot
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inferredcites →https://doi.org/10.1175/bams-d-15-00308.1openalex-snapshot
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inferredcites →https://doi.org/10.1201/9781315139470openalex-snapshot
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inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
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inferredcites →https://doi.org/10.2307/2530946openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python

What points at this work

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Comment on egusphere-2024-1200
inferred← citeshttps://doi.org/10.5194/egusphere-2024-3111-ac1openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/egusphere-2024-3111-ac2openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/egusphere-2024-3111-rc1openalex-snapshot
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Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.