ORCID Profile
0000-0002-1612-779X
Current Organisations
Pauls Stradins Clinical University Hospital
,
University of Queensland
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Geospatial Information Systems | Sociology | Geomatic Engineering | Urban Sociology and Community Studies |
Expanding Knowledge through Studies of Human Society | Urban and Industrial Land Management | Social Impacts of Climate Change and Variability
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 07-2022
Publisher: MDPI AG
Date: 18-10-2016
DOI: 10.3390/SU8101045
Publisher: MDPI AG
Date: 16-05-2019
DOI: 10.3390/IJGI8050229
Abstract: In the provision of urban residential areas, private land developers play critical roles in nearly all stages of the land development process. Despite their important role little is known about how the spatial decisions of in idual developers collectively influence urban growth. This paper employs an agent-based modelling approach to capture the spatial decisions of private land developers in shaping new urban forms. By drawing on microeconomic theory, the model simulates urban growth in the Jakarta Metropolitan Area, Indonesia, under different scenarios that reflect the decision behaviours of different types of developers. Results reveal that larger developers favour sites that are more proximate to the city centre whilst smaller developers prefer sites that are located further away from the city, that drive a more sprawled urban form. Our findings show that new urban areas are generated by different developers through different processes. The profit maximisation behaviour by developers with large capital reserves is more predictable than those with small capital funds. The imbalance in capital holdings by different types of developers interacts with one another to exert adverse impacts on the urban development process. Our study provides supporting evidence highlighting the need for urban policy to regulate urban expansion and achieve more sustainable urban development outcomes in a developing world context.
Publisher: Oxford University Press (OUP)
Date: 18-06-2022
Abstract: This study establishes a novel empirical framework using machine learning techniques to measure the urban-regional disparity of the public’s mental health signals in Australia during the pandemic, and to examine the interrelationships amongst mental health, demographic and socioeconomic profiles of neighbourhoods, health risks and healthcare access. Our results show that the public’s mental health signals in capital cities were better than those in regional areas. The negative mental health signals in capital cities are associated with a lower level of income, more crowded living space, a lower level of healthcare availability and more difficulties in healthcare access.
Publisher: Informa UK Limited
Date: 24-05-2017
Publisher: Elsevier BV
Date: 10-2018
Publisher: SAGE Publications
Date: 2013
DOI: 10.1068/B37142
Abstract: In this paper we present a cellular automata (CA) model based on nonlinear kernel principal component analysis (KPCA) to simulate the spatiotemporal process of urban growth. As a generalisation of the linear principal component analysis (PCA) method, the KPCA method was developed to extract the nonspatially correlated principal components amongst the various spatial variables which affect urban growth in high-dimensional feature space. Compared with the linear PCA method, the KPCA approach is superior as it generates fewer independent components while still maintaining its capacity to reduce the noise level of the original input datasets. The reduced number of independent components can be used to better reconstruct the nonlinear transition rules of a CA model. In addition, the principal components extracted through the KPCA approach are not linearly related to the input spatial variables, which accords well with the nonlinear nature of complex urban systems. The KPCA-based CA model (KPCA-CA) developed was fitted to a fast-growing region in China's Shanghai Metropolis for the sixteen-year period 1992–2008. The simulated patterns of urban growth matched well with the observed urban growth, as determined from historical remotely sensed images for the same period. The KPCA-CA model resulted in significant improvements in locational accuracy when compared with conventional CA models and acted to reduce simulation uncertainty.
Publisher: SAGE Publications
Date: 06-06-2018
Abstract: As people who live in closest proximity to us, the conduct of neighbours can have an impact upon our lives, even if they are relative strangers. While previous research has generally examined the positive effects of good neighbour interactions, neighbours can also be a source of nuisance, conflict and distress. In the advent of socio-structural processes of urban policy and change – such as gentrification and densification – the taken-for-granted conventions that once regulated neighbour interactions are being eroded, potentially leading to greater levels of neighbour problems and complaints. In this paper, we apply a latent modelling approach to identify subgroups of neighbourhoods based on their profiles of neighbour problems and to assess whether these subgroups are characterised by the degree of social change in the neighbourhood towards the dual processes of gentrification and densification. The findings show that high intensity problems are associated with both processes, but that class factors of gentrification are more influential than density in accounting for neighbour tensions.
Publisher: Springer Netherlands
Date: 09-09-2011
Publisher: Elsevier BV
Date: 06-2017
Publisher: Elsevier BV
Date: 10-2023
Publisher: Science Publications
Date: 04-2016
Publisher: Informa UK Limited
Date: 03-01-2023
Publisher: Informa UK Limited
Date: 11-06-2021
Publisher: SAGE Publications
Date: 09-10-2023
Publisher: Informa UK Limited
Date: 28-07-2010
Publisher: Monash University
Date: 12-2005
DOI: 10.2104/AG050027
Publisher: SAGE Publications
Date: 22-02-2022
DOI: 10.1177/23998083211069382
Abstract: Mainstream urban modelling literature focuses on urban expansion featured by a relatively fast urbanisation process, but relatively less research is available to understand and model the slow-paced urban and rural land development in the low-density peri-urban context. This study aims to address this knowledge gap by simulating the urban and rural land development in the Moreton Bay Region in South East Queensland (SEQ), Australia using two cellular automata (CA) models that are coupled with a generalised simulated annealing (GSA) algorithm. With the total land available for development estimated using a Markov Chain model, the GSA-CA urban and rural models were developed, respectively, to simulate urban and rural land development from 1991 to 2011, and then to predict their future development to 2041 following vigorous model calibrations. The modelling results illustrate three snapshots of the predicted spatial patterns of urban and rural development in 2021, 2031 and 2041, with moderate growth in both the urban and rural areas over time, but with urban development occurring in a more compact form than rural development. The GSA-CA modelling approach is capable of optimising the CA transition rules and has the potential to be applied to other geographical contexts to support regional planning, decision-making and scenario designation for future land development in cities that have entered the saturation phase of urbanisation.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Informa UK Limited
Date: 03-2013
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 03-2022
Publisher: Informa UK Limited
Date: 2008
Publisher: Wiley
Date: 09-07-2023
DOI: 10.1002/PAN3.10494
Abstract: Bio ersity offsets are a popular policy tool for mitigating the impact of development on bio ersity, but the ecological success of offsets arise from complex interactions among socio‐economic, ecological and policy processes, making outcomes challenging to assess. Many offset policies use habitat surrogates to determine offset requirements, rather than using direct measures of impacted biota, and this can lead to poor outcomes for species. One potential solution to this is for offsets to be delivered by a public agency (agency‐led) rather than by developers (developer‐led). This is because agencies may be able to strategically choose offset sites that maximise outcomes for species (e.g. abundance), while there may be little reason for developers to act strategically in this way when offset requirements are based purely on habitat surrogates. Yet, the success of a strategic agency‐led approach is likely to depend on patterns of development and offset site availability. To examine this, we developed a novel integrated spatially explicit model of land‐use change, habitat, species abundance and offset regulation. We apply the model to the Queensland Government's Environmental Offsets Policy for koalas Phascolarctos cinereus in South East Queensland, Australia, and test how patterns of development and offset site availability influence the performance of agency‐led versus developer‐led offsets. When potential offset sites were plentiful, agency‐led offsets tended to outperform developer‐led offset delivery for maximising koala abundance while achieving similar or better outcomes for habitat area. Yet, when potential offset sites were rare, the relative performance of agency‐led offset was often poor, and offset requirements for habitat area were less likely to be met. Different spatial patterns of development had little effect on the relative performance of agency‐led versus developer‐led offsets. Our analysis shows that agency‐led offsets with strategic choices of offset sites can improve species' outcomes for habitat‐based offsets but can also risk failing to meet habitat area requirements when the availability of offset sites is low. Importantly, our integrated spatial model provides a holistic approach to assessing policy options for bio ersity offsets in dynamic human‐modified landscapes. Read the free Plain Language Summary for this article on the Journal blog.
Publisher: SAGE Publications
Date: 07-06-2021
Abstract: This article explores the meaning of home to older Chinese migrants and what they do to construct a sense of home as they live and age in Australia. We conducted in-depth interviews with 20 older Chinese migrants (80 per cent aged 60+), who were born in mainland China and Hong Kong. Unlike the traditional interview method, we asked each participant to provide two photographs, which signified the concept of home to them and used these as visual elicitations for interviews. The findings from an inductive thematic analysis of the data show that the location of their adult children, home gardens, and cultural objects play a significant role in giving the participants a feeling of home in Australia. The study highlights that ageing in a foreign land involves older migrants’ continuous (re)integration of people and places in both the old country of origin and the new country of resettlement.
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Informa UK Limited
Date: 12-03-2019
Publisher: Springer International Publishing
Date: 2021
Publisher: SAGE Publications
Date: 18-09-2021
Abstract: The spatial decisions of land developers are known to play a significant role in driving urban expansion into previously undeveloped areas. This is especially the case in developing country contexts. Using the Jakarta Metropolitan Area as the case study context, we model the impact of capital possession by land developers on the location selection and unveil the way in which this exerts an effect on the spatial patterns of urban development. Through a hybrid agent-based and microeconomic modelling approach, different scenarios of capital possession and loans are simulated. Results show that areas with high values of return and low development costs are most likely to emerge as targeted locales. In order to result in measurable impact on the Jakarta Metropolitan Area urban footprint, developers need to possess a minimum capital investment of US$375 m allied with a 75% lending capacity. Results also reveal that the impact of the large land developers – those with in excess of US$750 m in capital that bring higher levels of lending leverage – extend the urban footprint in more predictable ways compared to land developers with less capital and lending capacity. Our study demonstrates the value of adopting an agent-based model to explore how human decisions at the in idual scale can influence the emergence of new urban forms in a rapidly developing metropolitan region.
Publisher: MDPI AG
Date: 21-07-2021
Abstract: Chronic illness is prevalent in older adults. While current scholarship has examined how various factors may be associated with the onset of chronic illnesses, fewer scholars have examined the role of health services availability. Drawing on a s le of older adults aged 50 and above from wave 16 of the Household, Income, and Labour Dynamics in Australia survey and geo-coded information of general practitioners (GPs) from the Australian Medical Directory, 2016, we investigated whether living in areas with a greater number of GPs is related to reports of living with a chronic illness. Contrary to our hypothesis, we did not find an association between the availability of health services and reports of chronic illnesses, though factors such as better socioeconomic status and better subjective wellbeing are related to lower likelihoods of reporting a chronic illness. We concluded that, while easy access to local health services may be important for the diagnosis and treatment of chronic illnesses, it is less persuasive to attribute the availability of health services to the likelihood of older adults reporting chronic illnesses without knowing how much or how often they use the services.
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 04-2023
Publisher: MDPI AG
Date: 18-07-2014
DOI: 10.3390/LAND3030719
Publisher: Elsevier BV
Date: 09-2011
Publisher: Informa UK Limited
Date: 03-2013
Publisher: JMIR Publications Inc.
Date: 02-06-2023
DOI: 10.2196/47225
Abstract: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people’s expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks detected on social media with actual suicidal behaviors. Corroborating this alignment is a crucial foundation for suicide prevention and intervention through social media and for estimating and predicting suicide in countries with no reliable suicide statistics. This study aimed to corroborate whether the suicide risks identified on social media align with actual suicidal behaviors. This aim was achieved by tracking suicide risks detected by 62 million tweets posted in Japan over a 10-year period and assessing the locational and temporal alignment of such suicide risks with actual suicide behaviors recorded in national suicide statistics. This study used a human-in-the-loop approach to identify suicide-risk tweets posted in Japan from January 2013 to December 2022. This approach involved keyword-filtered data mining, data scanning by human efforts, and data refinement via an advanced natural language processing model termed Bidirectional Encoder Representations from Transformers. The tweet-identified suicide risks were then compared with actual suicide records in both temporal and spatial dimensions to validate if they were statistically correlated. Twitter-identified suicide risks and actual suicide records were temporally correlated by month in the 10 years from 2013 to 2022 (correlation coefficient=0.533 P .001) this correlation coefficient is higher at 0.652 when we advanced the Twitter-identified suicide risks 1 month earlier to compare with the actual suicide records. These 2 indicators were also spatially correlated by city with a correlation coefficient of 0.699 (P .001) for the 10-year period. Among the 267 cities with the top quintile of suicide risks identified from both tweets and actual suicide records, 73.5% (n=196) of cities overlapped. In addition, Twitter-identified suicide risks were at a relatively lower level after midnight compared to a higher level in the afternoon, as well as a higher level on Sundays and Saturdays compared to weekdays. Social media platforms provide an anonymous space where people express their suicidal thoughts, ideation, and acts. Such expressions can serve as an alternative source to estimating and predicting suicide in countries without reliable suicide statistics. It can also provide real-time tracking of suicide risks, serving as an early warning for suicide. The identification of areas where suicide risks are highly concentrated is crucial for location-based mental health planning, enabling suicide prevention and intervention through social media in a spatially and temporally explicit manner.
Publisher: Australian Population Studies
Date: 26-05-2018
DOI: 10.37970/APS.V2I1.26
Abstract: No abstract
Publisher: BMJ
Date: 2022
DOI: 10.1136/BMJGH-2021-007081
Abstract: Widespread problems of psychological distress have been observed in many countries following the outbreak of COVID-19, including Australia. What is lacking from current scholarship is a national-scale assessment that tracks the shifts in mental health during the pandemic timeline and across geographic contexts. Drawing on 244 406 geotagged tweets in Australia from 1 January 2020 to 31 May 2021, we employed machine learning and spatial mapping techniques to classify, measure and map changes in the Australian public’s mental health signals, and track their change across the different phases of the pandemic in eight Australian capital cities. Australians’ mental health signals, quantified by sentiment scores, have a shift from pessimistic (early pandemic) to optimistic (middle pandemic), reflected by a 174.1% (95% CI 154.8 to 194.5) increase in sentiment scores. However, the signals progressively recessed towards a more pessimistic outlook (later pandemic) with a decrease in sentiment scores by 48.8% (95% CI 34.7 to 64.9). Such changes in mental health signals vary across capital cities. We set out a novel empirical framework using social media to systematically classify, measure, map and track the mental health of a nation. Our approach is designed in a manner that can readily be augmented into an ongoing monitoring capacity and extended to other nations. Tracking locales where people are displaying elevated levels of pessimistic mental health signals provide important information for the smart deployment of finite mental health services. This is especially critical in a time of crisis during which resources are stretched beyond normal bounds.
Publisher: Elsevier BV
Date: 02-2021
Publisher: Routledge
Date: 04-10-2016
Publisher: Informa UK Limited
Date: 07-2009
Publisher: Elsevier BV
Date: 12-2019
Publisher: MDPI AG
Date: 11-05-2021
DOI: 10.3390/SU13105372
Abstract: Studies on human mobility have a long history with increasingly strong interdisciplinary connections across social science, environmental science, information and technology, computer science, engineering, and health science. However, what is lacking in the current research is a synthesis of the studies to identify the evolutional pathways and future research directions. To address this gap, we conduct a systematic review of human mobility-related studies published from 1990 to 2020. Drawing on the selected publications retrieved from the Web of Science, we provide a bibliometric analysis and network visualisation using CiteSpace and VOSviewer on the number of publications and year published, authors and their countries and afflictions, citations, topics, abstracts, keywords, and journals. Our findings show that human mobility-related studies have become increasingly interdisciplinary and multi-dimensional, which have been strengthened by the use of the so-called ‘big data’ from multiple sources, the development of computer technologies, the innovation of modelling approaches, and the novel applications in various areas. Based on our synthesis of the work by top cited authors we identify four directions for future research relating to data sources, modelling methods, applications, and technologies. We advocate for more in-depth research on human mobility using multi-source big data, improving modelling methods and integrating advanced technologies including artificial intelligence, and machine and deep learning to address real-world problems and contribute to social good.
Publisher: Elsevier BV
Date: 02-2023
Publisher: Informa UK Limited
Date: 2012
Publisher: Elsevier BV
Date: 03-2018
Publisher: MDPI AG
Date: 13-02-2019
DOI: 10.3390/RS11040375
Abstract: Spatially explicit and reliable data on poverty is critical for both policy makers and researchers. However, such data remain scarce particularly in developing countries. Current research is limited in using environmental data from different sources in isolation to estimate poverty despite the fact that poverty is a complex phenomenon which cannot be quantified either theoretically or practically by one single data type. This study proposes a random forest regression (RFR) model to estimate poverty at 10 km × 10 km spatial resolution by combining features extracted from multiple data sources, including the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) Day/Night Band (DNB) nighttime light (NTL) data, Google satellite imagery, land cover map, road map and ision headquarter location data. The household wealth index (WI) drawn from the Demographic and Health Surveys (DHS) program was used to reflect poverty level. We trained the RFR model using data in Bangladesh and applied the model to both Bangladesh and Nepal to evaluate the model’s accuracy. The results show that the R2 between the actual and estimated WI in Bangladesh is 0.70, indicating a good predictive power of our model in WI estimation. The R2 between actual and estimated WI of 0.61 in Nepal also indicates a good generalization ability of the model. Furthermore, a negative correlation is observed between the district average WI and the poverty head count ratio (HCR) in Bangladesh with the Pearson Correlation Coefficient of -0.6. Using Gini importance, we identify that proximity to urban areas is the most important variable to explain poverty which contribute to 37.9% of the explanatory power. Compared to the study that used NTL and Google satellite imagery in isolation to estimate poverty, our method increases the accuracy of estimation. Given that the data we use are globally and publicly available, the methodology reported in this study would also be applicable in other countries or regions to estimate the extent of poverty.
Publisher: Oxford University Press (OUP)
Date: 15-07-2021
DOI: 10.1093/EURHEARTJ/EHAB424
Abstract: The aim of this study was to determine the frequency of heterozygous truncating ALPK3 variants (ALPK3tv) in patients with hypertrophic cardiomyopathy (HCM) and confirm their pathogenicity using burden testing in independent cohorts and family co-segregation studies. In a discovery cohort of 770 index patients with HCM, 12 (1.56%) were heterozygous for ALPK3tv [odds ratio(OR) 16.11, 95% confidence interval (CI) 7.94–30.02, P = 8.05e−11] compared to the Genome Aggregation Database (gnomAD) population. In a validation cohort of 2047 HCM probands, 32 (1.56%) carried heterozygous ALPK3tv (OR 16.17, 95% CI 10.31–24.87, P & 2.2e−16, compared to gnomAD). Combined logarithm of odds score in seven families with ALPK3tv was 2.99. In comparison with a cohort of genotyped patients with HCM (n = 1679) with and without pathogenic sarcomere gene variants (SP+ and SP−), ALPK3tv carriers had a higher prevalence of apical/concentric patterns of hypertrophy (60%, P & 0.001) and of a short PR interval (10%, P = 0.009). Age at diagnosis and maximum left ventricular wall thickness were similar to SP− and left ventricular systolic impairment (6%) and non-sustained ventricular tachycardia (31%) at baseline similar to SP+. After 5.3 ± 5.7 years, 4 (9%) patients with ALPK3tv died of heart failure or had cardiac transplantation (log-rank P = 0.012 vs. SP− and P = 0.425 vs. SP+). Imaging and histopathology showed extensive myocardial fibrosis and myocyte vacuolation. Heterozygous ALPK3tv are pathogenic and segregate with a characteristic HCM phenotype.
Publisher: MDPI AG
Date: 23-09-2018
DOI: 10.3390/RS10101526
Abstract: Whereas monthly and annual nighttime light (NTL) composite datasets are being increasingly used to estimate socioeconomic status, use of the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) Day/Night Band (DNB) daily data has been limited for detecting and assessing the impact of short-term disastrous events. This study explores the application of daily NPP-VIIRS DNB data in assessing the impact of three types of natural disasters: earthquakes, floods, and storms. Daily DNB images one month prior to and 10 days after a disastrous event were collected and a Percent of Normal Light (PNL) image was produced as the ratio of the mean DNB radiance of the pre- and post-disaster images. Areas with a PNL value lower than one were considered as being affected by the event. The results were compared with the damaged proxy map and the flood proxy map generated using synthetic aperture radar data as well as the reported power outage rates. Our analyses show that overall NPP-VIIRS DNB daily data are useful for detecting damages and power outages caused by earthquake, storm, and flood events. Cloud coverage was identified as a major limitation in using the DNB daily data rescue activities, traffic, and socioeconomic status of the areas also affect the use of DNB daily data in assessing the impact of natural disasters. Our findings offer new insight into the use of the daily DNB data and provide a practical guide for researchers and practitioners who may consider using such data in different situations or regions.
Publisher: Elsevier BV
Date: 11-2016
Publisher: Informa UK Limited
Date: 05-07-2021
Publisher: Elsevier BV
Date: 11-2022
Publisher: CRC Press
Date: 10-12-2008
Publisher: Informa UK Limited
Date: 06-09-2019
Publisher: Elsevier BV
Date: 11-2003
Publisher: Informa UK Limited
Date: 29-06-2023
Publisher: SPIE
Date: 13-10-2009
DOI: 10.1117/12.838657
Publisher: Wiley
Date: 14-12-2016
DOI: 10.1111/JCAL.12166
Publisher: SAGE Publications
Date: 05-06-2018
Publisher: Informa UK Limited
Date: 12-2004
Publisher: Elsevier BV
Date: 10-2022
Publisher: Informa UK Limited
Date: 2018
Publisher: Informa UK Limited
Date: 16-12-2022
Publisher: Elsevier BV
Date: 05-2018
Publisher: Informa UK Limited
Date: 22-09-2022
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: MDPI AG
Date: 29-10-2020
Abstract: The policy induced decline of human mobility has been recognised as effective in controlling the spread of COVID-19, especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling the data of confirmed COVID-19 cases with the Google mobility data in Australia, we present a state-level empirical study to: (1) inspect the temporal variation of the COVID-19 spread and the change of human mobility adherent to social restriction policies (2) examine the extent to which different types of mobility are associated with the COVID-19 spread in eight Australian states/territories and (3) analyse the time lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively the restriction of human mobility has a time lag effect on the growth rates of COVID-19, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between human mobility and COVID-19 spread varies across space and time and is subject to the types of mobility. Thus, it is important for government to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.
Publisher: Springer Science and Business Media LLC
Date: 11-08-2022
DOI: 10.1038/S41598-022-17878-6
Abstract: Assessing vulnerability to natural hazards is at the heart of hazard risk reduction. However, many countries such as Australia lack measuring systems to quantity vulnerability for hazard risk evaluation. Drawing on 41 indicators from multiple data sources at the finest spatial unit of the Australian census, we re-forged the Cutter’s classic vulnerability measuring framework by involving the ‘4D’ quantification of built environment ( ersity, design, density and distance), and constructed the first nationwide fine-grained measures of vulnerability for urban and rural locales, respectively. Our measures of vulnerability include five themes—(1) socioeconomic status (2) demographics and disability (3) minority and languages (4) housing characteristics and (5) built environment—that were further used to assess the inequality of vulnerability to three widely affected natural hazards in Australia (wildfires, floods, and earthquakes). We found the inequality of vulnerability in the affected areas of the three hazards in eight capital cities are more significant than that of their rural counterparts. The most vulnerable areas in capital cities were peri-urban locales which must be prioritised for hazard adaptation. Our findings contribute to the risk profiling and sustainable urban–rural development in Australia, and the broad understanding of place-based risk reduction in South Hemisphere.
Publisher: SAGE Publications
Date: 24-09-2023
DOI: 10.1177/23998083221129283
Abstract: Increasing urban density has become an important focus in mitigating the adverse impacts of urban sprawl. A common way to increase urban density is the development of multi-story residential housing, or vertical urban development (VUD). Compared to low-rise detached housing, VUD has been purported to be more effective in mitigating the adverse impact of urban sprawl. This paper examines factors influencing VUD through a case study of Brisbane, Australia. Three types of housing developments – low-rise detached houses, low-rise apartments, and medium- to high-rise apartments – are explored, with the latter two types classified as VUD. Building on the literature that suggests a range of environmental, socio-demographic, built environment, and planning regulations factors driving or constraining VUD, our study further explores how land parcel size and parcel change over time either through parcel amalgamation or sub ision as factors driving VUD. The findings show that parcel size and parcel amalgamation are key factors leading to VUD, particularly in the form of medium- to high-rise apartment development. On the other hand, land use upzoning alone does not appear to be sufficient to drive VUD. Our study enriches the understanding of the scale effects of land parcels and zoning regulation on vertical urban development, and contributes to parcel-based land use planning policies that are targeted at more intensive urban land use.
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 11-2021
DOI: 10.1016/J.SSTE.2021.100456
Abstract: The built environment has been identified as a key factor for health intervention and obesity prevention. However, it is still unclear to what extent the built environment is associated with obesity and general health and to what extent such an association is mediated through variation in physical activity. This study aims to examine the associations between in idual characteristics, the built environment, physical activity, general health and body mass index to reveal the pathways through which the built environment is associated with the prevalence of obesity. Using data from 1,788 adults aged 18 to 65 in Queensland from Wave 16 of the Household, Income, and Labour Dynamics in Australia survey, we use geographic information system-based methods to quantify built environment factors in 5D dimensions: Density, Diversity, Design, Distance and Destination accessibility. We then employ multi-level mixed-effect models to test the hypothesised relationships between in idual characteristics, the built environment, physical activity, general health and body mass index. The results indicate that physical activity is positively associated with general health and negatively associated with the prevalence of obesity. Adjusting for in idual characteristics, we find that built-environment factors have direct effects on physical activity but indirect effects on general health and obesity. Among these factors, greater green space exposure plays a key role in enhancing general health and reducing obesity. Low-density and car-dependent neighbourhoods can be activity-friendly and mitigate obesity if these neighbourhoods are also equipped with easy access to green space.
Publisher: Springer Science and Business Media LLC
Date: 07-01-2017
Publisher: SAGE Publications
Date: 23-12-2021
Abstract: The study of land use change in urban and regional systems has been dramatically transformed in the last four decades by the emergence and application of cellular automata (CA) models. CA models simulate urban land use changes which evolve from the bottom-up. Despite notable achievements in this field, there remain significant gaps between urban processes simulated in CA models and the actual dynamics of evolving urban systems. This article identifies contemporary issues faced in developing urban CA models and draws on this evidence to map out four interrelated thematic areas that require concerted attention by the wider CA urban modelling community. These are: (1) to build models that comprehensively capture the multi-dimensional processes of urban change, including urban regeneration, densification and gentrification, in-fill development, as well as urban shrinkage and vertical urban growth (2) to establish models that incorporate in idual human decision behaviours into the CA analytic framework (3) to draw on emergent sources of ‘big data’ to calibrate and validate urban CA models and to capture the role of human actors and their impact on urban change dynamics and (4) to strengthen theory-based CA models that comprehensively explain urban change mechanisms and dynamics. We conclude by advocating cellular automata that embed agent-based models and big data input as the most promising analytical framework through which we can enhance our understanding and planning of the contemporary urban change dynamics.
Publisher: SAGE Publications
Date: 02-06-2021
DOI: 10.1177/23998083211019756
Abstract: The elderly may have unique, daily travel behaviour characteristics compared to other age groups, associated with age and physical ability. Defining these characteristics can inform urban infrastructure construction and planning. In this study, 20 elders aged between 60 and 70 years, living in the city centre of Tianjin, were selected to complete the survey. A total of 2232 hours of participant travel behaviour were collected via GPS equipment from July to August 2019. Data were used to create a space–time cube. Based on a statistical analysis of the GPS data, results indicated that the elderly mainly had six kinds of daily travel behaviours: visiting, shopping, outdoor exercise, eating out, going to the hospital and picking up and dropping off grandchildren. The main activity time was from 10:00 a.m. to 9:00 p.m. Their travel mode was mostly pedestrian-based, with an average single travel distance of about 1.01 km, and an average single travel time of about 0.5 hours. Using the space–time cube, characteristics of elderly daily travel behaviour were visualised. In addition, a typical space–time cube was summarised and presented. Data and methods from this study can provide reference and support for future-related research.
Publisher: Informa UK Limited
Date: 23-09-2019
Publisher: MDPI AG
Date: 13-12-2018
DOI: 10.3390/SU10124754
Abstract: Economic resilience is a critical indicator of the sustainable development of an urban economy. This paper measures the urban economic resilience (UER) of 286 major cities in China from six indicators—economic growth, opening up, social development, environmental protection, natural conditions, and technological innovation—using a subjective and objective weighting method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. Furthermore, kernel density estimation (KDE) was used to reveal the spatial and temporal trends in UER across cities, and a social opportunity function was applied to access the opportunity for economic resilience and the fairness of opportunities for economic resilience in 19 urban agglomerations in China. The results show that the UER was, in general, low across all cities but increased over time. Geographically, the UER disperses from the eastern coast to inland cities. Amongst urban agglomerations in China, the economic resilience opportunity index also varies spatially and increases over time. On the other hand, the opportunity fairness index of UER remained largely stable and substantial inequalities exist across all urban agglomerations, indicating the need for differentiated policy intervention to ensure equality and the sustainable development of the region. The methodology developed in this research can also be applied in other cities and regions to test its re-applicability and to understand the UER in different contexts.
Publisher: MDPI AG
Date: 19-03-2022
DOI: 10.3390/GEOGRAPHIES2010010
Abstract: This paper considers whether existing approaches for quantifying variables in cellular automata (CA) modelling adequately incorporate all the relevant factors in typical actor decisions underpinning urban development. A survey of developers and planners is used to identify factors they incorporate to allow for or proceed with development, using South East Queensland as a reference region. Three types of decision factors are identified and ranked in order of importance: those that are already modelled in CA applications those that are not modelled but are quantifiable and those that are not (easily) quantifiable because they are subjective in nature. Factors identified in the second category include development height/scale, open space supply, and existing infrastructure capacity. Factors identified in the third category include political intent, community opposition, and lifestyle quality. Drawing on our analysis of these factors we suggest how and to what extent survey data might be used to address the challenges of incorporating actor variables into the CA modelling of urban change. The paper represents the first attempt to review what decision factors should be included in CA modelling, and how this might be enabled.
Publisher: Elsevier BV
Date: 09-2023
Publisher: International Community of Spatial Planning and Sustainable Development
Date: 15-07-2015
Publisher: Springer Science and Business Media LLC
Date: 31-08-2016
DOI: 10.1007/S10661-016-5558-Y
Abstract: The world's coastal regions are experiencing rapid urbanization coupled with increased risk of ecological damage and storm surge related to global climate and sea level rising. This urban development issue is particularly important in China, where many emerging coastal cities are being developed. Lingang New City, southeast of Shanghai, is an excellent ex le of a coastal city that is increasingly vulnerable to environmental change. Sustainable urban development requires planning that classifies and allocates coastal lands using objective procedures that incorporate changing environmental conditions. In this paper, we applied cellular automata (CA) modeling based on self-adaptive genetic algorithm (SAGA) to predict future scenarios and explore sustainable urban development options for Lingang. The CA model was calibrated using the 2005 initial status, 2015 final status, and a set of spatial variables. We implemented specific ecological and environmental conditions as spatial constraints for the model and predicted four 2030 scenarios: (a) an urban planning-oriented Plan Scenario (b) an ecosystem protection-oriented Eco Scenario (c) a storm surge-affected Storm Scenario and (d) a scenario incorporating both ecosystem protection and the effects of storm surge, called the Ecostorm Scenario. The Plan Scenario has been taken as the baseline, with the Lingang urban area increasing from 45.8 km(2) in 2015 to 66.8 km(2) in 2030, accounting for 23.9 % of the entire study area. The simulated urban land size of the Plan Scenario in 2030 was taken as the target to accommodate the projected population increase in this city, which was then applied in the remaining three development scenarios. We used CA modeling to reallocate the urban cells to other unconstrained areas in response to changing spatial constraints. Our predictions should be helpful not only in assessing and adjusting the urban planning schemes for Lingang but also for evaluating urban planning in coastal cities elsewhere.
Publisher: Informa UK Limited
Date: 12-2011
Publisher: Wiley
Date: 14-09-2018
Publisher: Springer Science and Business Media LLC
Date: 14-10-2016
Publisher: Springer Science and Business Media LLC
Date: 12-08-2016
Publisher: Informa UK Limited
Date: 02-10-2020
Publisher: American Meteorological Society
Date: 25-06-2021
Abstract: Both built environment and natural environment have physiological and psychological effect on human behaviour, which potentially affect their sensitivity and tolerance to surrounding noise, and leads to annoyance, nuisance, distress or overt actions and aggressive behaviours such as noise complaints to people living neighborly. This study aims to explore the extent weather conditions affect the prevalence of noise complaints between neighbours mediated through neighbourhood built environment. Using Brisbane, Australia as a study case, we draw on the large-scale administrative dataset in 2016 to explore the monthly and seasonal variations of noise complaints between neighbours, and employ a step-wise multiple regression to analyse the extent weather factors affect noise complaints. Our findings show that neighbours largely complain about noise made by animals and such complaints most frequently appear in March to May, the autumn season in the South Hemisphere. Built environment plays a primary role on noise complaints and culturally erse suburbs with less green space tend to have a higher likelihood of neighbour complaints in spring and summer such a likelihood is further increased by a higher level of wind, humidity, and temperature in a yearly frame. However, the effect of weather on animal and non-animal related noise complaints in different seasons is less consistent. Our findings, to a certain degree, reveal that weather conditions may serve as a psychological moderator to change people’s tolerance and sensitivity on noise, alter their routine activities and exposure to noise sources, and further affect the likelihood of imposing noise complaints between neighbours.
Publisher: Elsevier
Date: 2020
Publisher: Wiley
Date: 17-12-2015
DOI: 10.1111/CONL.12213
Publisher: Science Publications
Date: 02-2015
Publisher: Wiley
Date: 10-09-2018
DOI: 10.1111/BJET.12677
Publisher: Springer Science and Business Media LLC
Date: 02-07-2014
Publisher: Wiley
Date: 11-2017
Publisher: Springer Science and Business Media LLC
Date: 23-07-2015
Publisher: Elsevier BV
Date: 05-2023
Publisher: Elsevier BV
Date: 07-2019
Publisher: Network Design Lab - Transport Findings
Date: 03-06-2021
DOI: 10.32866/001C.23722
Abstract: Climate change poses risks of inundation to low-lying coastal cities and may cause residential relocation and change in housing demand. Taking the City of Gold Coast in Queensland, Australia as a case study, this paper reports on a survey that investigates the potential responses of residents living in the coastal city to flood risks and how the responses may relate to their socio-economic status. Through a combined online and mail-based survey, our data show that people’s perceptions of flooding have an important impact on their relocation choices. Their perceptions and relocation choices are associated with their socio-economic background. Furthermore, residents’ preferences of dwelling types appear to be affected by the level of flood risks we hypothesise in the survey. The findings from this study provide empirical evidence for future residential zoning and urban development.
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 11-2016
Publisher: Informa UK Limited
Date: 13-07-2020
Publisher: Informa UK Limited
Date: 22-03-2023
Publisher: AICIT
Date: 31-12-2012
Publisher: Elsevier BV
Date: 11-2021
Publisher: JMIR Publications Inc.
Date: 12-03-2023
Abstract: ocial media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people’s expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks detected on social media with actual suicidal behaviors. Corroborating this alignment is a crucial foundation for suicide prevention and intervention through social media and for estimating and predicting suicide in countries with no reliable suicide statistics. his study aimed to corroborate whether the suicide risks identified on social media align with actual suicidal behaviors. This aim was achieved by tracking suicide risks detected by 62 million tweets posted in Japan over a 10-year period and assessing the locational and temporal alignment of such suicide risks with actual suicide behaviors recorded in national suicide statistics. his study used a human-in-the-loop approach to identify suicide-risk tweets posted in Japan from January 2013 to December 2022. This approach involved keyword-filtered data mining, data scanning by human efforts, and data refinement via an advanced natural language processing model termed Bidirectional Encoder Representations from Transformers. The tweet-identified suicide risks were then compared with actual suicide records in both temporal and spatial dimensions to validate if they were statistically correlated. witter-identified suicide risks and actual suicide records were temporally correlated by month in the 10 years from 2013 to 2022 (correlation coefficient=0.533 i P /i & .001) this correlation coefficient is higher at 0.652 when we advanced the Twitter-identified suicide risks 1 month earlier to compare with the actual suicide records. These 2 indicators were also spatially correlated by city with a correlation coefficient of 0.699 ( i P /i & .001) for the 10-year period. Among the 267 cities with the top quintile of suicide risks identified from both tweets and actual suicide records, 73.5% (n=196) of cities overlapped. In addition, Twitter-identified suicide risks were at a relatively lower level after midnight compared to a higher level in the afternoon, as well as a higher level on Sundays and Saturdays compared to weekdays. ocial media platforms provide an anonymous space where people express their suicidal thoughts, ideation, and acts. Such expressions can serve as an alternative source to estimating and predicting suicide in countries without reliable suicide statistics. It can also provide real-time tracking of suicide risks, serving as an early warning for suicide. The identification of areas where suicide risks are highly concentrated is crucial for location-based mental health planning, enabling suicide prevention and intervention through social media in a spatially and temporally explicit manner.
Publisher: Atlantis Press
Date: 2015
Publisher: Springer Science and Business Media LLC
Date: 13-01-2021
Publisher: Edward Elgar Publishing
Date: 07-05-2021
Publisher: Elsevier BV
Date: 04-2019
Publisher: Elsevier BV
Date: 02-2020
Publisher: International Community of Spatial Planning and Sustainable Development
Date: 2016
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 07-2018
Publisher: SAGE Publications
Date: 30-10-2019
Abstract: The severe loss of human life and material damage caused by traffic accidents is a growing concern faced by many countries across the world. In Australia, despite a decline in the total number of traffic collisions since 2001, the number of hit-parked-vehicle (HPV) collisions as a special type of road accident has increased over time. Utilizing the road collisions and roadway network data in Brisbane, Australia over a 10-year period from 2001 to 2010, we generated graphics illustrating the spatial patterning of high-risk road segments for HPV crashes identified using the local indicator of network-constrained clusters (LINCS) approach. These spatial patterns vary by days of the week and times of the day. Roads with high risk for HPV collision tend to occur in high-density road networks and cluster around road intersections. The methodology applied in this work is applicable to other network-constrained point-pattern analysis.
Publisher: Informa UK Limited
Date: 04-05-2018
Publisher: Elsevier BV
Date: 11-2023
Publisher: SAGE Publications
Date: 04-10-2021
DOI: 10.1177/10780874211042811
Abstract: Where earlier conceptions of problem neighbors saw them as contributing to neighborhood level forms of disorder, neighbor problems, in contrast, occur in the everyday domestic setting of residential life and challenge conceptual boundaries between public rivate and civility/incivility. As a result, there is a need to better understand the phenomenon of problems between neighbors beyond conceptions of public disorder and to understand the processes that influence how and why neighbor problems arise. In this study, we examine neighbor problems as manifest in reported complaints to a local municipality in Australia to understand how neighborhood features affect the likelihood of neighbors experiencing problems with each other. We propose five hypotheses to examine the social-interactive, environmental, and geographical mechanisms of neighborhood effects and test these hypotheses through logistic regression models on the way certain neighborhood features relate to the prevalence of neighbor problems. The findings reveal the sources of neighbor problems that typically reside in a combination of the social-interactive dynamics of the neighborhood itself—including the composition of the resident population—and the environmental features of the neighborhood in terms of the condition, density and use of dwellings, but not in the location of the neighborhood relative to larger-scale political and economic forces of the city. The paper concludes with a discussion of the significance of these findings for research, policy, and practice.
Publisher: Cambridge University Press (CUP)
Date: 28-05-2019
Abstract: To determine accessibility of the primary healthcare system for patients with stroke recently discharged from hospital. This project mapped retrospective patient location data and the location of primary healthcare services in the same region. Patient location data were from all patients with stroke ( N = 1595: January 2011–January 2017) discharged from one metropolitan hospital to the local Primary Health Network. Geographic Information System technology was used to map the patient discharge locations and the spatial distribution of primary healthcare services (general practitioner, pharmacy, allied health) across the region. Road network data were used to measure the level of access from each patient’s discharge location to the services. Access to primary healthcare services was variable. Areas with larger proportions of patients with stroke did not necessarily have good service access. With an increase in travel time, the number of services accessible to patients also increased. However, the spatial variation of access to services remained largely unchanged. Access to primary healthcare services for patients with stroke varies spatially, with a trend towards relatively low levels of accessibility for many patients. There is an urgent need for future planning to consider geographical access to primary healthcare services for patients with stroke.
Publisher: Springer International Publishing
Date: 2019
Publisher: Elsevier BV
Date: 07-2019
Publisher: Elsevier BV
Date: 06-2015
Publisher: Elsevier BV
Date: 09-2014
Publisher: Springer Netherlands
Date: 19-10-2011
Publisher: SAGE Publications
Date: 04-10-2019
Abstract: The number of migrants from Mainland China (MC) to Australia have been sharply increasing since 2000 and MC became the largest non-Commonwealth source country in 2011. The integration process of migrants to the host society involves the exposure and movement of migrants to the majority, which is reflected by the settlement pathways of migrants moving from ethnic to non-ethnic communities over time. Most of the existing research regarding migrants’ pathways is constrained by the limitations of cross-sectional data, which are usually available at the community or above levels. Little is known about the in idual-level settlement pathways of migrants due to lack of data availability. In order to address this deficit, a 3D visualization is used to express the in idual pathways of MC-born migrants based on primary survey data. This enables a more detailed, spatio-temporal picture of how long migrants live at each address and how they move across neighbourhoods.
Location: Australia
Location: China
Location: Singapore
Start Date: 2011
End Date: 2012
Funder: Queensland Government
View Funded ActivityStart Date: 2019
End Date: 2022
Funder: National Natural Science Foundation of China
View Funded ActivityStart Date: 2015
End Date: 2018
Funder: Australian Research Council
View Funded ActivityStart Date: 2017
End Date: 2019
Funder: Australian Research Council
View Funded ActivityStart Date: 2018
End Date: 2019
Funder: Academy of the Social Sciences in Australia
View Funded ActivityStart Date: 2018
End Date: 2020
Funder: Queensland Government
View Funded ActivityStart Date: 2020
End Date: 2023
Funder: University of Melbourne
View Funded ActivityStart Date: 2007
End Date: 2010
Funder: Ministry of Education - Singapore
View Funded ActivityStart Date: 2015
End Date: 12-2018
Amount: $182,600.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2017
End Date: 06-2021
Amount: $308,000.00
Funder: Australian Research Council
View Funded Activity