"The Great Blackbury Pie" ~ or ~ Focal Area Bias in Geographically Weighted Analysis

Focal and geographically weighted analyses are commonplace in GIS applications across many fields and disciplines. However, where such analyses are based on ‘dense’ datasets (e.g., a raster surface), they can suffer from an unintended bias towards the periphery of the focal zone (neighbourhood), which (counterintuitively) is exacerbated by the use of distance weighting functions. This paper serves to characterise this problem, which we call focal area bias (FAB), present a proposed correction, and point to extensive simulation-based analysis, which demonstrates both the impact that this effect can have on analyses and the efficacy of our proposed solution

Understanding and assessing climate risk to green infrastructure: experiences from Greater Manchester (UK)

The existing body of research into the environmental and socio-economic benefits of green infra-structure supports the case for it to be positioned as a form of critical infrastructure, particularly in urban settings. It is broadly recognized that extreme weather and climate change pose signifi-cant risks to critical infrastructure systems linked to the provision of services including electrici-ty, water, communications, and transport, and consequently risk assessments and associated adaptation strategies are common practice. However, although green infrastructure is also at risk from extreme weather and climate change, threatening the realization of benefits that it can de-liver in urban settings, associated risks to green infrastructure are not widely understood or as-sessed in practice. This paper discusses the status of existing research on this topic and uses this as a foundation for a Greater Manchester (UK) case study that assesses the risk of low water avail-ability to grassed areas, which represent a key element of the city-region’s green infrastructure. In doing so, the paper demonstrates how risks linked to extreme weather and climate change can be assessed spatially to inform green infrastructure planning. In summary, this paper aims to raise awareness of extreme weather and climate change risk to urban green infrastructure, present an empirical case study and associated methodological approach on this topic, and ultimately to support efforts to enhance the resilience of urban green infrastructure to extreme weather and cli-mate change

Estimating multiple greenspace exposure types and their associations with neighbourhood premature mortality: A socioecological study.

BACKGROUND: Greenspace exposures are often measured using single exposure metrics, which can lead to conflicting results. Existing methodologies are limited in their ability to estimate greenspace exposure comprehensively. We demonstrate new methods for estimating single and combined greenspace exposure metrics, representing multiple exposure types that combine impacts at various scales. We also investigate the association between those greenspace exposure types and premature mortality. METHODS: We used geospatial data and spatial analytics to model and map greenspace availability, accessibility and eye-level visibility exposure metrics. These were harmonised and standardised to create a novel composite greenspace exposure index (CGEI). Using these metrics, we investigated associations between greenspace exposures and years of potential life lost (YPLL) for 1673 neighbourhoods applying spatial autoregressive models. We also investigated the variations in these associations in conjunction with levels of socioeconomic deprivation based on the index of multiple deprivations. RESULTS: Our new CGEI metric provides the opportunity to estimate spatially explicit total greenspace exposure. We found that a 1-unit increase in neighbourhood CGEI was associated with approximately a 10-year reduction in YPLL. Meaning a 0.1 increment or 10% increase in the CGEI is associated with an approximately one year lower premature mortality value. A single 1-unit increase in greenspace availability was associated with a YPLL reduction of 9.8 years, whereas greenness visibility related to a reduction of 6.14 years. We found no significant association between greenspace accessibility and YPLL. Our results further identified divergent trends in the relations between greenspace exposure types (e.g. availability vs. accessibility) and levels of socioeconomic deprivation (e.g. least vs. most). CONCLUSION: Our methods and metrics provide a novel approach to the assessment of multiple greenspace exposure types, and can be linked to the broader exposome framework. Our results showed that a higher composite greenspace exposure is associated with lower premature mortality

Estimating multiple greenspace exposure types and their associations with neighbourhood premature mortality: A socioecological study.

BACKGROUND: Greenspace exposures are often measured using single exposure metrics, which can lead to conflicting results. Existing methodologies are limited in their ability to estimate greenspace exposure comprehensively. We demonstrate new methods for estimating single and combined greenspace exposure metrics, representing multiple exposure types that combine impacts at various scales. We also investigate the association between those greenspace exposure types and premature mortality. METHODS: We used geospatial data and spatial analytics to model and map greenspace availability, accessibility and eye-level visibility exposure metrics. These were harmonised and standardised to create a novel composite greenspace exposure index (CGEI). Using these metrics, we investigated associations between greenspace exposures and years of potential life lost (YPLL) for 1673 neighbourhoods applying spatial autoregressive models. We also investigated the variations in these associations in conjunction with levels of socioeconomic deprivation based on the index of multiple deprivations. RESULTS: Our new CGEI metric provides the opportunity to estimate spatially explicit total greenspace exposure. We found that a 1-unit increase in neighbourhood CGEI was associated with approximately a 10-year reduction in YPLL. Meaning a 0.1 increment or 10% increase in the CGEI is associated with an approximately one year lower premature mortality value. A single 1-unit increase in greenspace availability was associated with a YPLL reduction of 9.8 years, whereas greenness visibility related to a reduction of 6.14 years. We found no significant association between greenspace accessibility and YPLL. Our results further identified divergent trends in the relations between greenspace exposure types (e.g. availability vs. accessibility) and levels of socioeconomic deprivation (e.g. least vs. most). CONCLUSION: Our methods and metrics provide a novel approach to the assessment of multiple greenspace exposure types, and can be linked to the broader exposome framework. Our results showed that a higher composite greenspace exposure is associated with lower premature mortality

Spatial dimensions of the influence of urban green-blue spaces on human health: A systematic review.

BACKGROUND: There is an increasing volume of literature investigating the links between urban environments and human health, much of which involves spatial conceptualisations and research designs involving various aspects of geographical information science. Despite intensifying research interest, there has been little systematic investigation of pragmatic methodological concerns, such as how studies are realised in terms of the types of data that are gathered and the analytical techniques that are applied, both of which have the potential to impact results. The aim of this systematic review is, therefore, to understand how spatial scale, datasets, methods, and analytics are currently applied in studies investigating the relationship between green and blue spaces and human health in urban areas. METHOD: We systematically reviewed 93 articles following PRISMA protocol, extracted information regarding different spatial dimensions, and synthesised them in relation to various health indicators. RESULTS AND DISCUSSION: We found a preponderance of the use of neighbourhood-scale in these studies, and a majority of the studies utilised land-use and vegetation indices gleaned from moderate resolution satellite imagery. We also observed the frequent adoption of fixed spatial units for measuring exposure to green and blue spaces based on physical proximity, typically ranging between 30 and 5000 m. The conceptual frameworks of the studies (e.g., the focus on physical vs. mental health or the definition of exposure to green space) were found to have an influence on the strength of association between exposure and health outcomes. Additionally, the strength and significance of associations also varied by study design, something which has not been considered systematically. CONCLUSION: On the basis of our findings, we propose a set of recommendations for standardised protocols and methods for the evaluation of the impact of green-blue spaces on health. Our analysis suggests that future studies should consider conducting analyses at finer spatial scales and employing multiple exposure assessment methods to achieve a comprehensive and comparable evaluation of the association between greenspace and health along multiple pathways

Walkability and Greenness Do Not Walk Together: Investigating Associations between Greenness and Walkability in a Large Metropolitan City Context.

BACKGROUND: The existing environment literature separately emphasizes the importance of neighborhood walkability and greenness in enhancing health and wellbeing. Thus, a desirable neighborhood should ideally be green and walkable at the same time. Yet, limited research exists on the prevalence of such "sweet spot" neighborhoods. We sought to investigate this question in the context of a large metropolitan city (i.e., Sydney) in Australia. METHODS: Using suburb level normalized difference vegetative index (NDVI), percentage urban greenspace, Walk Score® (Walk Score, Seattle, WA, USA), and other data, we explored the global and local relationships of neighborhood-level greenness, urban green space (percent park area) with walkability applying both non-spatial and spatial modeling. RESULTS: We found an overall negative relationship between walkability and greenness (measured as NDVI). Most neighborhoods (represented by suburbs) in Sydney are either walkable or green, but not both. Sweet spot neighborhoods that did exist were green but only somewhat walkable. In addition, many neighborhoods were both less green and somewhat walkable. Moreover, we observed a significant positive relationship between percentage park area and walkability. These results indicate walkability and greenness have inverse and, at best, mixed associations in the Sydney metropolitan area. CONCLUSIONS: Our analysis indicates an overall negative relationship between greenness and walkability, with significant local variability. With ongoing efforts towards greening Sydney and improving walkability, more neighborhoods may eventually be transformed into becoming greener and more walkable

Noncommunicable Diseases, Park Prescriptions, and Urban Green Space Use Patterns in a Global South Context: The Case of Dhaka, Bangladesh.

Urban green space use is often associated with improved physical and mental health and lower noncommunicable disease (NCDs) burdens. Factors that influence green space visits have been documented in cities of the Global North, but evidence of urban green space use patterns for cities in the Global South is scarce. The aim of this study is to investigate factors influencing urban green space use patterns in Dhaka, Bangladesh, a megacity of the Global South, with a particular focus on how poor health condition and healthcare professionals' prescriptions to exercise outdoors (park prescriptions-ParkRx) impact the green space use of middle-aged adults. We collected green space characteristics and use factors (i.e., availability, accessibility, attractiveness, and attachment), health condition, ParkRx, and urban green space use intensity (i.e., frequency and duration) via a self-reported questionnaire from 169 middle-aged residents of Dhaka. We used multivariate modeling to estimate the association of green space characteristics, health condition, and ParkRx with use intensity. We further applied a mediation analysis to determine the influence of ParkRx on the relationship between residents' poor health conditions and use intensity. We found that green space availability and accessibility did not significantly influence use intensity, but attractiveness was negatively associated with use intensity. Green space use intensity was significantly and positively associated with attachment to the green space, poor health condition (i.e., having noncommunicable diseases), and ParkRx. ParkRx significantly mediated the relationship between health condition and use intensity. We observed limited supply, poor access, and low attractiveness when studying the urban green spaces in Dhaka, but these qualities did not affect use intensity, as found in many case studies in the Global North. In contrast, urban green space use intensity in our case study is mostly dependent on poor health condition and park prescriptions

A citizen science toolkit to collect human perceptions of urban environments using open street view images

Street View-level Imagery (SVI) is a valuable data source for studies (e.g., environmental assessments, green space identification or land cover classification). While commercial SVI is available, such providers commonly restrict copying or reuse in ways necessary for research. Open SVI datasets are readily available from less restrictive sources, such as Mapillary, but due to the heterogeneity of the images, these require substantial preprocessing, filtering, and careful quality checks. We present an efficient method for automated downloading, processing, cropping, and filtering open SVI, to be used in a survey of human perceptions of the streets portrayed in these images. We demonstrate our open-source reusable SVI preparation and smartphone-friendly perception-survey software with Amsterdam (Netherlands) as the case study. Using a citizen science approach, we collected from 331 people 22,637 ratings about their perceptions for various criteria. We have published our software in a public repository for future re-use and reproducibility