Temperature in housing: stratification and contextual                     factors

Baborska-Narożny, Magdalena; Stevenson, Fionn; Chatterton, Paul

doi:10.1680/jensu.14.00054

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…Before constructing contextual weighting matrices, these units were unified by computing the spatial and temporal distance. The cross-validation method has been proven to be an effective method for finding ways to eliminate standard errors and deviations [34]. The validation procedure was used in this study to acquire a suitable parameter value in terms of fitting accuracy, with the optimal bandwidth found to be B = 2221, τ = 80,118, and ς = 216,407 (Figure 3).…”

Section: Results Of the Local Modelmentioning

confidence: 99%

“…In addition to building structural and locational requirements, contextual attributes, obviously, also affect changes in residential land prices. For instance, two schools are near each other, but one has better educational facilities and resources; the selling prices of houses near these schools would be influenced by the neighborhood-level attribute space [33][34][35][36]. Rich Harris [30] proposed a contextualized geographically weighted regression (CGWR) to integrate attribute correlations between neighborhood-level observations and found that it was significant in a real estate context, but temporal information was ignored.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Effects of Contextual Factors on Residential Land Prices Using an Extended Geographically and Temporally Weighted Regression Model

Chai¹,

Yang²,

Zhao

et al. 2021

Land

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A spatial and temporal heterogeneity analysis of residential land prices, in general, is crucial for maintaining high-quality economic development. Previous studies have attempted to explain the geographical evolution rule by studying spatial-temporal heterogeneity, but they have neglected the contextual information, such as school district, industrial zone, population density, and job density, associated with residential land prices. Therefore, in this study, we consider contextual factors and propose a revised local regression algorithm called the contextualized geographically and temporally weighted regression (CGTWR), to effectively address spatiotemporal heterogeneity, and to creatively extend the feasibility of importing the contextualization into the GTWR model. The quantitative impact of contextual information on residential land prices was identified in Shijiazhuang (SJZ) city from 1974 to 2021. Empirical analyses demonstrated that school district and industrial zone factors played important roles in residential land prices. Notably, the distance from a residential area to an industrial zone was significantly positively correlated with residential land prices. In addition, a positive relationship between school districts and residential land prices was also observed. Finally, the R2 value of the CGTWR model was 92%, which was superior to those of ordinary least squares (OLS, 76%), geographically weighted regression (GWR, 85%), contextualized geographically weighted regression (CGWR, 86%), and GTWR (90%) models. These evaluation results indicate that the CGTWR algorithm, which incorporates contextual information and spatiotemporal variation, could provide policy makers with evidence for understanding the nature of varying relationships within a land price dataset in China.

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Section: Results Of the Local Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring the Effects of Contextual Factors on Residential Land Prices Using an Extended Geographically and Temporally Weighted Regression Model

Chai¹,

Yang²,

Zhao

et al. 2021

Land

View full text Add to dashboard Cite

show abstract

“…In the UK, 20% of households may already be at risk of overheating [15], and, with the predicted climate change, this percentage will likely increase [4]. Although no universal definition of overheating exists, the phenomenon has been widely monitored [15][16][17][18][19][20][21][22][23][24], and thermally modelled [25][26][27][28][29][30] using either static or adaptive assessment criteria. Numerous studies have examined a number of dwelling types that represent broadly the housing stock in the UK.…”

Section: Introductionmentioning

confidence: 99%

Overheating and Daylighting; Assessment Tool in Early Design of London’s High-Rise Residential Buildings

Nebia¹,

Aoul

2017

Sustainability

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High-rise residential buildings in dense cities, such as London, are a common response to housing shortage. The apartments in these buildings may experience different levels of thermal and visual comfort, depending on their orientation and floor level. This paper aims to develop simplified tools to predict internal temperatures and daylighting levels, and propose a tool to quickly assess overheating risk and daylight performance in London's high-rise residential buildings. Single-and double-sided apartments in a high-rise building were compared, and the impact of their floor level, glazing ratio, thermal mass, ventilation strategy and orientation was investigated. Using Integrated Environmental Solutions Virtual Environment (IES VE), temperature and daylight factor results of each design variable were used to develop early design tools to predict and assess overheating risks and daylighting levels. The results indicate that apartments that are more exposed to solar radiations, through either orientation or floor level, are more susceptible to overheat in the summer while exceeding the daylighting recommendations. Different design strategies at different levels and orientations are subsequently discussed.

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Energy effectiveness of passive cooling design strategies to reduce the impact of long-term heatwaves on occupants’ thermal comfort in Europe: Climate change and mitigation

Özarısoy

2022

Journal of Cleaner Production

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Temperature in housing: stratification and contextual factors

Cited by 6 publications

References 25 publications

Exploring the Effects of Contextual Factors on Residential Land Prices Using an Extended Geographically and Temporally Weighted Regression Model

Exploring the Effects of Contextual Factors on Residential Land Prices Using an Extended Geographically and Temporally Weighted Regression Model

Overheating and Daylighting; Assessment Tool in Early Design of London’s High-Rise Residential Buildings

Energy effectiveness of passive cooling design strategies to reduce the impact of long-term heatwaves on occupants’ thermal comfort in Europe: Climate change and mitigation

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