Architecture, Building and Planning - Research Publications
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ItemA comparison of content from across contemporary Australian population health surveys(Wiley, 2024-06)Objective: Associations between place and population health are of interest to researchers and policymakers. The objective of this paper is to explore, summarise and compare content across contemporary Australian geo-referenced population health survey data sets. Methods: A search for recent (2015 or later) population health surveys from within Australia containing geographic information from participants was conducted. Survey response frames were analysed and categorised based on demographic, risk factor and disease-related characteristics. Analysis using interactive Sankey diagrams shows the extent of content overlap and differences between population health surveys in Australia. Results: Thirteen Australian geo-referenced population health survey data sets were identified. Information captured across surveys was inconsistent as was the spatial granularity of respondent information. Health and demographic features most frequently captured were symptoms, signs and clinical findings from the International Statistical Classification of Diseases and Related Health Problems version 11, employment, housing, income, self-rated health and risk factors, including alcohol consumption, diet, medical treatments, physical activity and weight-related questions. Sankey diagrams were deployed online for use by public health researchers. Conclusions: Identifying the relationship between place and health in Australia is made more difficult by inconsistencies in information collected across surveys deployed in different regions in Australia. Implications for Public Health: Public health research investigating place and health involves a vast and inconsistent patchwork of information within and across states, which may impact broad-scale research questions. The tools developed here assist public health researchers to identify surveys suitable for their research queries related to place and health.
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ItemImpacts of irrigation scheduling on urban green space cooling(Elsevier, 2024-08)The increasing heat stress in cities due to climate change and urbanisation can prevent people from using urban green spaces. Irrigating vegetation is a promising strategy to cool urban green spaces in summer. Irrigation scheduling, such as daytime vs night-time irrigation and the frequency of irrigation in a day, may influence the cooling benefit of irrigation. This study aimed to investigate whether irrigation scheduling can be optimised to increase the cooling benefit and determine how the cooling benefit changes with weather conditions. A field experiment with twelve identical turfgrass plots (three replicates × four irrigation treatments) was set up to measure the afternoon cooling benefits of irrigation. The four treatments included: no irrigation, single night-time irrigation (4 mm d–1), single daytime irrigation (4 mm d–1) and multiple daytime irrigation (4 x 1 mm d–1). The cooling benefit was defined as the air temperature difference measured at 1.1 m above the turfgrass between the irrigated and unirrigated treatments (air temperature sensor accuracy ± 0.2 °C). The afternoon (12:00–15:59) mean cooling benefit of multiple daytime irrigation (–0.9 °C) which was significantly stronger than that of single night-time irrigation (–0.6 °C) and single daytime irrigation (–0.5 °C). Regardless of irrigation scheduling, the afternoon mean cooling benefits of irrigation were greater for days when background air temperature, vapour pressure deficit and incoming shortwave radiation were greater. The findings suggested that irrigation scheduling can be optimised to increase the cooling benefit of urban green space irrigation without increasing overall water use.
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ItemIdentifying the mechanisms by which irrigation can cool urban green spaces in summer(Elsevier, 2024-05)High temperatures in summer can prevent people from using urban green spaces. Irrigating urban green spaces is a promising strategy to reduce temperatures. In this study, we aimed to a) identify the proportional contribution of different irrigation cooling mechanisms and b) quantify the impacts of different irrigation amounts (from 2 to 30 mm d−1) on the cooling effect of irrigating turfgrass in Melbourne, Australia. We first used a field experiment in Melbourne to provide empirical data to calibrate and verify the performance of an urban ecohydrological model, UT&C. Then, we used UT&C to predict the impacts of irrigating turfgrass on evapotranspiration, the energy balance and microclimate. UT&C predicted that irrigating turfgrass 4 mm d−1 would increase the evaporation from grass canopy and soil surface by 0.2 and 0.6 mm d−1, respectively, whereas it would reduce transpiration by 0.6 mm d−1 due to intercepted water covering part of the grass canopy following the irrigation. UT&C predicted that daytime (10:00–16:59) mean air temperature reductions would increase from 0.2 to 0.4 °C when the irrigation amount increased from 2 to 4 mm d−1. However, increasing the irrigation amount beyond 4 mm d−1 would not increase the cooling benefits.
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ItemNo Preview AvailableLand surface and air temperature dynamics: The role of urban form and seasonality(ELSEVIER, 2023-12-20)Due to the scarcity of air temperature (Ta) observations, urban heat studies often rely on satellite-derived Land Surface Temperature (LST) to characterise the near-surface thermal environment. However, there remains a lack of a quantitative understanding on how LST differs from Ta within urban areas and what are the controlling factors of their interaction. We use crowdsourced air temperature measurements in Sydney, Australia, combined with urban landscape data, Local Climate Zones (LCZ), high-resolution satellite imagery, and machine learning to explore the influence of urban form and fabric on the interaction between Ta and LST. Results show that LST and Ta have distinct spatiotemporal characteristics, and their relationship differs by season, ecological infrastructure, and building morphology. We found greater seasonal variability in LST compared to Ta, along with more pronounced intra-urban spatial variability in LST, particularly in warmer seasons. We also observed a greater temperature difference between LST and Ta in the built environment compared to the natural LCZs, especially during warm days. Natural LCZs (areas with mostly dense and scattered trees) showed stronger LST-Ta relationships compared to built areas. In particular, we observe that built areas with higher building density (where the heat vulnerability is likely more pronounced) show insignificant or negative relationships between LST- Ta in summer. Our results also indicate that surface cover, distance from the ocean, and seasonality significantly influence the distribution of hot and cold spots for LST and Ta. The spatial distribution for Ta hot spots does not always overlap with LST. We find that relying solely on LST as a direct proxy for the urban thermal environment is inappropriate, particularly in densely built-up areas and during warm seasons. These findings provide new perspectives on the relationship between surface and canopy temperatures and how these relate to urban form and fabric.
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ItemAssociation between network characteristics and bicycle ridership across a large metropolitan region(Taylor and Francis Group, 2024)Numerous studies have explored associations between bicycle network characteristics and bicycle ridership. However, the majority of these studies have been conducted in inner metropolitan regions and as such, there is limited knowledge on how various characteristics of bicycle networks relate to bicycle trips within and across entire metropolitan regions, and how the size and composition of study regions impact on the association between bicycle network characteristics and bicycle ridership. We conducted a retrospective analysis of household travel survey data and bicycle infrastructure in the Greater Melbourne region, Australia. Seven network metrics were calculated (length of the bicycle network, betweenness centrality, degree centrality, network density, network coverage, intersection density and average weighted slope) and Bayesian spatial models were used to explore associations between these network characteristics and bicycle ridership. We demonstrated that bicycle ridership was associated with several network characteristics, and that these characteristics varied according to the outcome (count of the number of trips made by bike or the proportion of trips made by bike) and the size and characteristics of the study region. These findings challenge the utility of approaches based on spatially modeling network characteristics and bicycle ridership when informing the monitoring and evaluation of bicycle networks. Further efforts are required to be able to quantify network characteristics that reflect the myriad of factors that influence comfort and safety for people of all ages and abilities.
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ItemNo Preview AvailableA systematic scoping review of methods for estimating link-level bicycling volumes(TAYLOR & FRANCIS LTD, 2023-07-04)
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ItemNo Preview AvailableEvaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results(WILEY, 2024-01)Abstract Accurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban‐focussed land surface models in over a decade. Here, in Phase 1 of the Urban‐PLUMBER project, we evaluate the ability of 30 land surface models to simulate surface energy fluxes critical to atmospheric meteorological and air quality simulations. We establish minimum and upper performance expectations for participating models using simple information‐limited models as benchmarks. Compared with the last major model intercomparison at the same site, we find broad improvement in the current cohort's predictions of short‐wave radiation, sensible and latent heat fluxes, but little or no improvement in long‐wave radiation and momentum fluxes. Models with a simple urban representation (e.g., ‘slab’ schemes) generally perform well, particularly when combined with sophisticated hydrological/vegetation models. Some mid‐complexity models (e.g., ‘canyon’ schemes) also perform well, indicating efforts to integrate vegetation and hydrology processes have paid dividends. The most complex models that resolve three‐dimensional interactions between buildings in general did not perform as well as other categories. However, these models also tended to have the simplest representations of hydrology and vegetation. Models without any urban representation (i.e., vegetation‐only land surface models) performed poorly for latent heat fluxes, and reasonably for other energy fluxes at this suburban site. Our analysis identified widespread human errors in initial submissions that substantially affected model performances. Although significant efforts are applied to correct these errors, we conclude that human factors are likely to influence results in this (or any) model intercomparison, particularly where participating scientists have varying experience and first languages. These initial results are for one suburban site, and future phases of Urban‐PLUMBER will evaluate models across 20 sites in different urban and regional climate zones.
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ItemNo Preview AvailableDaytime irrigation leads to significantly cooler private backyards in summer(ELSEVIER, 2022-12)
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ItemNo Preview AvailableIsolating the impacts of urban form and fabric from geography on urban heat and human thermal comfort(Elsevier, 2022-10-01)Public health risks resulting from urban heat in cities are increasing due to rapid urbanisation and climate change, motivating closer attention to urban heat mitigation and adaptation strategies that enable climate-sensitive urban design and development. These strategies incorporate four key factors influencing heat stress in cities: the urban form (morphology of vegetated and built surfaces), urban fabric, urban function (including human activities), and background climate and regional geographic settings (e.g. topography and distance to water bodies). The first two factors can be modified and redesigned as urban heat mitigation strategies (e.g. changing the albedo of surfaces, replacing hard surfaces with pervious vegetated surfaces, or increasing canopy cover). Regional geographical settings of cities, on the other hand, cannot be modified and while human activities can be modified, it often requires holistic behavioural and policy modifications and the impacts of these can be difficult to quantify. When evaluating the effectiveness of urban heat mitigation strategies in observational or traditional modelling studies, it can be difficult to separate the impacts of modifications to the built and natural forms from the interactions of the geographic influences, limiting the universality of results. To address this, we introduce a new methodology to determine the influence of urban form and fabric on thermal comfort, by utilising a comprehensive combination of possible urban forms, an urban morphology data source, and micro-climate modelling. We perform 9814 simulations covering a wide range of realistic built and natural forms (building, roads, grass, and tree densities as well as building and tree heights) to determine their importance and influence on thermal environments in urban canyons without geographical influences. We show that higher daytime air temperatures and thermal comfort indices are strongly driven by increased street fractions, with maximum air temperatures increases of up to 10 and 15 °C as street fractions increase from 10% (very narrow street canyons and/or extensive vegetation cover) to 80 and 90% (wide street canyons). Up to 5 °C reductions in daytime air temperatures are seen with increasing grass and tree fractions from zero (fully urban) to complete (fully natural) coverage. Similar patterns are seen with the Universal Thermal Climate Index (UTCI), with increasing street fractions of 80% and 90% driving increases of 6 and 12 °C, respectively. We then apply the results at a city-wide scale, generating heat maps of several Australian cities showing the impacts of present day urban form and fabric. The resulting method allows mitigation strategies to be tested on modifiable urban form factors isolated from geography, topography, and local weather conditions, factors that cannot easily be modified.
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ItemA Transformation in City-Descriptive Input Data for Urban Climate Models(FRONTIERS MEDIA SA, 2022-07-06)In urban climate studies, datasets used to describe urban characteristics have traditionally taken a class-based approach, whereby urban areas are classified into a limited number of typologies with a resulting loss of fidelity. New datasets are becoming increasingly available that describe the three-dimensional structure of cities at sub-metre micro-scale resolutions, resolving individual buildings and trees across entire continents. These datasets can be used to accurately determine local characteristics without relying on classes, but their direct use in numerical weather and climate modelling has been limited by their availability, and because they require processing to conform to the required inputs of climate models. Here, we process building-resolving datasets across large geographical extents to derive city-descriptive parameters suitable as common model inputs at resolutions more appropriate for local or meso-scale modelling. These parameter values are then compared with the ranges obtained through the class-based Local Climate Zone framework. Results are presented for two case studies, Sydney and Melbourne, Australia, as open access data tables for integration into urban climate models, as well as codes for processing high-resolution and three-dimensional urban datasets. We also provide an open access 300 m resolution building morphology and surface cover dataset for the Sydney metropolitan region (approximately 5,000 square kilometres). The use of building resolving data to derive model inputs at the grid scale better captures the distinct heterogenetic characteristics of urban form and fabric compared with class-based approaches, leading to a more accurate representation of cities in climate models. As consistent building-resolving datasets become available over larger geographical extents, we expect bottom-up approaches to replace top-down class-based frameworks.