The heat penalty of walkable neighbourhoods

O’Brien, Grace; Ross, Nancy A.; Strachan, Ian B.

doi:10.1007/s00484-018-01663-0

Cited by 8 publications

(6 citation statements)

References 22 publications

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“…In such areas, further study is required to understand the influence of site-related physiological, psychological, social and meteorological factors on outdoor thermal comfort, as well as seasonal differences. To overcome issues related to LCZ application to human scale, researchers have explored alternative methods by developing miniaturized weather stations which could be directly worn by pedestrian [103,105,[112][113][114] or set on bicycles [89,115,116] or cars [117,118].…”

Section: Gaps Limitations and Future Directionsmentioning

confidence: 99%

Outdoor thermal comfort assessment: A review on thermal comfort research in Australia

Shooshtarian

Lam

Kenawy

2020

Building and Environment

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Outdoor thermal comfort could significantly affect the usage and success of urban places. Accordingly, it is recommended to be considered in both urban design and planning projects. Urbanisation has been recognised as a major factor in elevated daily temperature values in Australia. This study aims to investigate the past and current position of outdoor thermal comfort studies in the Australian context. A critical review is conducted to examine the quality 21 of thermal comfort assessment in Australia's cities. Twenty-five studies were reviewed to give a precise overview of past thermal comfort studies. The review scrutinises the focus of research, methodologies applied, data collection methods and results. This review helps main stakeholders in urban development better understand the evolution of outdoor thermal comfort with respect to liveability. In this line, where possible, the shortcomings are identified, certain solutions are provided and the need for further research is highlighted. In particular, future studies are necessary to cover missing geographical regions and ethnicities that are not considered in the existing literature. Furthermore, more psychological thermal adaptation studies are necessary, especially in transient thermal conditions. Qualitative analysis is also recommended to be incorporated in further studies in addition to considering the perceived environmental quality. The study serves as a reference to researchers, urban designers and planners to enhance their knowledge for achieving outdoor thermal comfort and understanding the gaps that need to be addressed in further studies.

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Section: Gaps Limitations and Future Directionsmentioning

confidence: 99%

Outdoor thermal comfort assessment: A review on thermal comfort research in Australia

Shooshtarian

Lam

Kenawy

2020

Building and Environment

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“…The modeling approach offers point-scale air temperature estimation at resampled street locations in Chicago, which can be further integrated into desired resolution. We believe that the approach presented in this study can contribute to the knowledge on important urban problems, such as street walkability (O'Brien et al, 2019), disproportional heat exposure (Chakraborty et al, 2019), heat-related health issues (Heaviside et al, 2017), and behavioral studies (Anderson, 1989;Reeping & Hemenway, 2020).…”

Section: Introductionmentioning

confidence: 95%

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

Li,

Sharma

2024

J Adv Model Earth Syst

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The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

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“…The modeling approach offers point-scale air temperature estimation at resampled street locations in Chicago, which can be further integrated into desired resolution. We believe that the approach presented in this study can contribute to the knowledge of important urban problems, such as street walkability (O'Brien et al, 2019), disproportional heat exposure (Chakraborty et al, 2019), heatrelated health issues (Heaviside et al, 2017), and behavioral studies (Anderson, 1989;Reeping and Hemenway, 2020).…”

Section: Introductionmentioning

confidence: 96%

Hyper-local temperature prediction using detailed urban climate informatics

Sharma

2023

Preprint

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Modeling urban microclimate accurately is challenging due to the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical-based models to fully utilize the high-resolution data under the constraints of computing resources. The advancement in machine learning techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a machine learning approach to estimate point-scale street-level air temperature from the urban-resolving mesoscale climate model and a suite of hyper-resolution urban informatics, including three-dimensional urban morphology, parcel-level land use inventory, and a dense weather observation network. We implemented this approach in the City of Chicago as a case study. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat-related behavioral studies. Moreover, we tested the model’s reliability on out-of-sample locations to investigate the application potentials to the other areas. This study also aims to gain insights into next-gen urban climate modeling and guide city observation efforts to build the strength for the holistic understanding of urban microclimate dynamics.

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The heat penalty of walkable neighbourhoods

Cited by 8 publications

References 22 publications

Outdoor thermal comfort assessment: A review on thermal comfort research in Australia

Outdoor thermal comfort assessment: A review on thermal comfort research in Australia

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

Hyper-local temperature prediction using detailed urban climate informatics

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