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Unlike car navigation, where almost all vehicles can traverse every route, one route might not be optimal or even suitable for all pedestrians. Route geometry information, including tortuosity, twists and turns along roads, junctions, and road slopes, among others, matters a great deal for specific types of pedestrians, particularly those with limited mobility, such as wheelchair users and older adults. Offering practical routing services to these users requires that pedestrian navigation systems provide further information on route geometry. Therefore, this article proposes a novel method for extracting and analyzing the geometry properties of the shortest pedestrian paths, with a focus on open geospatial data across four aspects: (a) similarity, (b) route curviness, (c) road turns and intersections, and (d) road gradients. Deriving from the Hausdorff distance, a metric called the "dissimilarity ratio" was developed, allowing us to determine whether pairs of routes show any tendencies to be similar to each other. Using the "sinuosity index", a segment-based technique quantified the route curviness based on the number and degree of the road turns along the route. Moreover, relying upon open elevation data, the road gradients were extracted to identify routes offering smoother motion and better accessibility. Lastly, the road turns and intersections were investigated as pedestrian convenience and safety indicators. A local government area of Greater Sydney in Australia was chosen as the case study. The analysis was implemented on OpenStreetMap (OSM) shortest pedestrian paths against Google Maps as a benchmark for real-world commercial applications. The similarity analysis indicated that over 90% of OSM routes were identical or roughly similar to Google Maps. In addition, while Spearman's rank correlation showed a direct relationship between route curviness and route length, r S (758) = 0.92, p < 0.001, OSM, on average, witnessed more tortuous routes and, consequently, shorter straight roads between turns. However, OSM routes could be more suitable for pedestrians when the frequency of intersections and road slopes are at the center of attention. Finally, the devised metrics in this study, including the dissimilarity ratio and sinuosity index, showed their practicability in translating raw values into meaningful indicators. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is critical in monitoring the time-lagged impacts of agrometeorological drought. In Australia and several south-west Pacific Small Island Developing States (SIDS), there are a limited number of in situ SM stations that can adequately assess soil-water availability in a near-real-time context. Satellite SM datasets provide a viable alternative for SM monitoring and agrometeorological drought provision in these regions. In this study, we investigated the performance of Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Operational Products System (SMOPS), SM from the Advanced Microwave Scanning Radiometer 2 (AMSR-2) and SM from the Advanced Scatterometer (ASCAT) over Australia and south-west Pacific SIDS. Products were first evaluated in Australia, given the presence of several in-situ SM monitoring stations and a state-of-the-art hydrological model—the Australian Water Resources Assessment Landscape modelling system (AWRA-L). We further investigated the accuracy of SM satellite datasets in Australia and the south-west Pacific through Triple Collocation analysis with two other SM reference datasets—ERA5 reanalysis SM data and model data from the Global Land Data Assimilation System (GLDAS) dataset. All datasets have differing observation periods ranging from 1911-now, with a common period of observations between 2015–2021. Results demonstrated that ASCAT and SMOS were consistently superior in their performance. Analysis in the six south-west Pacific SIDS indicated reduced performance for all products, with ASCAT and SMOS still performing better than others for most SIDS with median R values ranging between 0.3–0.9. We conducted a case study of the 2015 El Niño and Positive Indian Ocean Dipole-induced drought in Papua New Guinea. It was shown that ASCAT is a valuable dataset indicative of agrometeorological drought for the nation, highlighting the value of using satellite SM products to provide early warning of drought in data-sparse regions in the south-west Pacific. [ABSTRACT FROM AUTHOR]

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 (diversity, 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. [ABSTRACT FROM AUTHOR]

Tracking the settlement of culturally and linguistically diverse (CALD) populations serves as the foundation for population projection, urban planning, and policy making to achieve social justice, equity, and multicultural harmony. Drawing on census data in 2001, 2006, 2011, 2016 and 2021, our study contributes an Australian nationwide time-series study of the settlement of CALD populations at a fine neighbourhood level, enabling long-term tracking of changing settlement patterns and residential diversity and revealing potential drivers for such changes. Following segmented assimilation theory, we examine whether the CALD populations with higher education levels, higher socioeconomic status and better language skills may tend to partially move out and partially retain their ethnic concentrations, resulting in assimilation that occurs segmentally across urban fabrics. We find that both existing CALD communities and the formation of new CALD concentrations in peri-urban regions exhibit segmented assimilation over time. We also find the settlement patterns of CALD populations in urban areas are more diverse than in rural areas in most states/territories. Our study provides spatially explicit evidence with far-reaching policy implications for migration, place-based health, population and urban planning. • It contributes an Australian nationwide time-series study of the settlement of CALD populations. • The settlement changes of CALD populations exhibit segmented assimilation over time. • Early CALD communities and new CALD concentrations in peri-urban regions concurrently exist. • Their settlement patterns in urban areas are more diverse than in rural areas in most states. • Speaking good English and high education levels play important roles in driving settlement shift. [ABSTRACT FROM AUTHOR]

Extreme heat, also known as the silent killer that conceal its lethal effect behind heat-related deaths, has become one of the deadliest natural hazards globally. However, the evaluation of heat risks in many countries remains incomplete, overlooking an important component on population health conditions in the evaluation framework. Drawing on the IPCC's risk assessment framework, this study presents, for the first time, a comprehensive heat health risk assessment in Australian capital cities, consisting of three individual indexes—the heat exposure index, heat hazard index and heat vulnerability index—at the finest census unit, and an overall heat health risk index (HHRI). By involving health-related indicators in heat risk assessment, our evaluation takes into account people's sensitivity to heat in developing the heat health risk indexes. Using the HHRI, we identify high heat risk areas appearing primarily in higher density residential areas with some distances away from the inner cities. We also find that the inequity of demographic and socioeconomic characteristics, housing features, and built environment features exists in areas with different levels of heat risks. Our findings contribute not only to profiling heat risks in Australian cities, but also empirically advance our understanding of place-based risk reduction in the Southern Hemisphere by linking climate science with health and spatial science research. • This study contributes the first heat health risk assessment in Australian cities. • This study generates the index of heat hazard, vulnerability and exposure and the overall index of heat health risk. • The assessment framework can be applied to other contexts and natural hazards. • Heat health risk related datasets are publicly available. • Spatial and socioeconomic inequity exists across areas with different levels of heat risk. [ABSTRACT FROM AUTHOR]

Background and purpose: Physical inactivity and prolonged sitting have associations with adverse health. University office workers are at a high risk of psychological and pain issues. This study aimed to explore the differences in sitting time, levels of physical activity participation, stress, depression, anxiety, and pain among university office workers in China and Australia. Methods: Online surveys were distributed to university office workers over 55 years at two universities in China and Australia, respectively. Results: A total of 185 participants completed the online survey (119 in China and 66 in Australia). Significant differences were found in sitting time during workdays between the two countries (p < 0.05) with a longer sitting time in the Australian respondents (7.5 h/day) than those in China (4.6 h/day). Additionally, there were also significant differences in terms of levels of depression and pain symptoms within the two countries (p < 0.05). The Australian respondents reported high levels of depression and pain (M = 7.38, SD = 5.86 and M = 3.65, SD = 2.21, respectively) than those in China (M = 5.71, SD = 4.87 and M = 1.89, SD = 1.89, respectively). The gender, education level, and sitting time of participants were found to be associated with pain scores (p < 0.05). A significant association between marital status and pain scores was found among the Australian respondents (p < 0.05). Conclusions: Future studies with a larger population are needed to validate the results and to further explore the association between physical activity participation and psychological wellbeing among university office workers. [ABSTRACT FROM AUTHOR]

[Display omitted] While it is well recognised that increasing vegetation cover reduces the Urban Heat Island (UHI) effect in cities, less is understood about the spatial pattern of vegetation type required to maximise cooling benefits. This study examines how different urban vegetation spatial configuration and composition impact on the UHI phenomenon. We investigated this on a set of sites in Metropolitan Melbourne, Australia. Urban vegetation raster data at 20 cm resolution was used to define five height-based vegetation cover types (grass, shrub, small, medium and large trees); and to calculate eight landscape metrics: percentage of landscape (PLAND), mean patch area (AREA_MN), patch density (PD), edge density (ED), mean patch shape index (SHAPE_MN), mean Euclidean nearest-neighbour distance (ENN_MN), Shannon's diversity index (SHDI) and Landscape shape index (LSI). These vegetation landscape metrics of vegetation types were established as independent variables and statistically analysed with the UHI intensity as the dependent variable using Classification and Regression Tree analysis (CRT). The CRT model was developed based on 6469 records and including depth of 5, 41 nodes and 21 terminal nodes. From the total 43 independent variables, 11 were identified as high impact factors on UHI intensity. Our findings revealed a consistent negative statistical relationship between UHI intensity and PLAND-landscape, PLAND-large tree and PLAND-medium tree across the study sites. The PLAND, ED and AREA_MN were the most prevalent metrics to explain UHI effect, which has also principally demonstrated the joint impact of the three metrics on UHI effect. This study presents a new framework of a fine-scale assessment and modelling for the impact of urban vegetation on UHI; and elaborates a practical approach of using CRT technique to design local-based UHI mitigating strategies taking advantage of different vegetation structure. [ABSTRACT FROM AUTHOR]

People adapt to changes in livelihoods and risks caused by summer high temperature in the era of global warming, which may also lead to residential mobility at the individual level and migration flow at the aggregate level. However, little evidence is available to show the long-term localized impact of summer temperature on residential mobility. Our study aims to conduct a 20-year nationwide investigation of the heat-mobility relationship in Australia to reveal how the increase of summer temperature is associated with the change of residential mobility and how such relationship shifts over time. Employing a tri-environmental (i.e., social, built and natural environment) conceptual framework adapted from the Social Ecological Theory, our analyses draw on the Australian census data from 2001 to 2021 together with the earth observation data to quantify multiple confounders in the tri-environmental dimensions in order to reveal the heat-mobility relationship at the national, state, urban and rural scales. We find that locales with significant increase in summer temperature have less inbound residential mobility, that is, people are less likely to move into heat-affected areas. This study enhances the understanding of how global warming affects residential mobility and settlement, and what adaptation strategies are needed to reduce the heat threat and achieve urban sustainability. • It provides a 20-year nationwide study of the nexus between heat and residential mobility in Australia. • A tri-environmental framework was applied to analyze the heat-mobility nexus. • Such a nexus was examined by accounting for the complexity of confounders. • People are less likely to move to areas with the increase in temperature over time. • No substantial difference is observed in the heat-mobility nexus within and beyond the capital cities. [ABSTRACT FROM AUTHOR]

Embracing multiculturalism has become an important initiative for enhancing cultural identity, social cohesion, and harmony in many migrant-receiving countries. While a large body of literature has examined ethnic diversity in relation to migration, less attention has been given to tracking changes in ethnic diversity over time and from a spatial perspective. Our study aims to contribute to this gap by examining nationwide ethnic diversity in Australia from 2001 to 2021 at various spatial scales and exploring its relationship with the neighbourhood features of ethnic settlement to provide practical implications for urban planning and design. To measure ethnic diversity, we draw on the five census datasets from 2001, 2006, 2011, 2016, and 2021 and apply Shannon's diversity index to the smallest census unit, as well as to the levels of capital cities, rural areas, and states. We then employ a machine learning method to model the relationship between ethnic diversity and neighbourhood features of migrants' settlement, including demographic and socioeconomic features and housing characteristics, and to reveal changes in this relationship over time. Our key findings suggest that the level of ethnic diversity dropped during 2006–2011, possibly due to changes in migration policy in Australia, and dropped again during 2016–2021, possibly due to the outbreak of COVID-19. Neighbourhoods with high ethnic diversity are associated with populations that speak English fluently and hold high education degrees, as well as easy access to public transit and affordable housing. Our study provides practical suggestions and implications for migration and settlement policy-making and promoting better social cohesion through urban planning, neighbourhood design, and housing regulation. • It contributes a 20-year nationwide examination of ethnic diversity in Australia at multi-scales. • It explores the relationship between ethnic diversity and neighbourhood features. • It finds that the level of ethnic diversity dropped during 2006–2011 and dropped again during 2016–2021. • Ethnically diverse areas are associated with populations with good English fluently and high education. • Ethnically diverse areas are associated with easy access to public transit and affordable housing. [ABSTRACT FROM AUTHOR]

Background Recent developments in Western Australia's economy including widespread traffic congestion as well as road safety issues are increasingly becoming prominent. Previous studies relied on traditional statistical methods to investigate patterns and characteristics of motor vehicle crashes. Although useful, statistical analysis alone is incapable of providing a spatial context and is therefore unable to associate existing crash characteristics with a spatial distribution. Aims To identify concentrations or “hotspots” of articulated heavy vehicle crashes in WA between the years 2001–2013, by using a spatial analysis approach. Methods Spatial modelling and spatio-temporal analytical methods such as Emerging Hotspots were used to identify emerging hotspots on specific roads in Western Australia using the Integrated Road Information System (IRIS). Results The results suggest that the majority of articulated heavy vehicles crashes occurred in the vicinity or within the Perth metropolitan area. Based on spatial-temporal trend analyses, our findings highlight some regions that are emerging as areas of interest. Discussion This study was one of the first attempts to adopt a spatial analysis approach in studying heavy-vehicle crashes in Western Australia. Applying spatial methodologies to road safety data has the potential of obtaining previously undiscovered insights, which can be extended further, and provide future avenues to research in this field. [ABSTRACT FROM AUTHOR]

The warming trend over recent decades has already contributed to the increased prevalence of heat-vulnerable chronic diseases in many regions of the world. However, understanding the relationship between heat-vulnerable chronic diseases and heatwaves remains incomplete due to the complexity of such a relationship mingling with human society, urban and natural environments. Our study extends the Social Ecological Theory by constructing a tri-environmental conceptual framework (i.e., across social, built, and natural environments) and contributes to the first nationwide study of the relationship between heat-vulnerable chronic diseases and heatwaves in Australia. We utilize the random forest regression model to explore the importance of heatwaves and 48 tri-environmental variables that contribute to the prevalence of six types of heat-vulnerable diseases. We further apply the local interpretable model-agnostic explanations and the accumulated local effects analysis to interpret how the heat-disease nexus is mediated through tri-environments and varied across urban and rural space. The overall effect of heatwaves on diseases varies across disease types and geographical contexts (latitudes; inland versus coast). The local heat-disease nexus follows a J-shape function—becoming sharply positive after a certain threshold of heatwaves—reflecting that people with the onset of different diseases have various sensitivity and tolerance to heatwaves. However, such effects are relatively marginal compared to tri-environmental variables. We propose a number of policy implications on reducing urban-rural disparity in healthcare access and service distribution, delineating areas, and identifying the variations of sensitivity to heatwaves across urban/rural space and disease types. Our conceptual framework can be further applied to examine the relationship between other environmental problems and health outcomes. • This study constructs a tri-environmental framework to examine heat-disease relationship. • It contributes the first nationwide fine-grained study on heat-disease relationship in Australia. • It evaluates importance of heatwaves and 48 tri-environmental variables on six chronic diseases. • It finds that people with onset of diseases have various sensitivity and tolerance to heatwaves. • The effect of heatwaves on diseases is marginal compared to that of tri-environmental variables. [ABSTRACT FROM AUTHOR]