Evaluating urban environmental and ecological landscape characteristics as a function of land-sharing-sparing, urbanity and scale

The evolution of built-up areas in Ghana since 1975

We use high resolution satellite data on the proportion of buildings in a 250x250 meter cell to study the evolution of human settlement in Ghana over a 40 year period. We find a strong increase in built-up area over time, mostly concentrated in the vicinity of roads, and also directly on the coast. We find strong evidence of agglomeration effects both in the static sense—buildup in one cell predicts buildup in a nearby cell—and in a dynamic sense—buildup in a cell predicts buildup in that cell later on and an increase in buildup in nearby cells. These effects are strongest over a 3 to 15 Km radius, which corresponds to a natural hinterland for a population without mechanized transportation. We find no evidence that human settlements are spaced more or less equally either over the landscape or along roads. This suggests that arable land is not yet fully utilized, allowing rural settlements to be separated by areas of un-farmed land. By fitting a transition matrix to the data, we predict a sharp increase in the proportion of the country that is densely built-up by the middle and the end of the century, but no increase in the proportion of partially built-up locations.

A spatiotemporal analysis of urban resilience to the COVID-19 pandemic in the Yangtze River Delta

The COVID-19 pandemic has severely affected the normal socioeconomic operation of countries worldwide, causing major economic losses and deaths and posing great challenges to the sustainable development of cities that play a leading role in national socioeconomic development. The strength of urban resilience determines the speed of urban social and economic recovery. This paper constructed a comprehensive evaluation index system for urban resilience under the COVID-19 pandemic scenario considering four dimensions-economy, ecology, infrastructure, and social systems-conducted a quantitative evaluation of urban resilience in the Yangtze River Delta of China, revealed its spatiotemporal differences and change trends, and proposed targeted strategies for improving urban resilience. The results show that (1) the Yangtze River Delta urban resilience system is growing stronger every year, but there are significant differences in the level of urban resilience, its spatial distribution and regional urban resilience. (2) In the Yangtze River Delta urban agglomeration, there is less distribution of areas with a higher resilience index, while those with high and medium resilience levels are more distributed. However, the resilience of most cities is low. (3) The resilience index of eastern coastal cities is significantly higher, and the resilience of cities under the COVID-19 scenario presents obvious east-west differentiation. (4) When constructing urban resilience, the individual situation of cities should be taken into account, measures adjusted according to local conditions, reasonable lessons drawn from effective international urban resilience construction, and reasonable planning policies formulated; it is important to give play to the relationship between the whole and the parts of resilience to achieve unified and coordinated development.

The Urban Built Environment, Walking and Mental Health Outcomes Among Older Adults: A Pilot Study

The benefits of walking in older age include improved cognitive health (e.g., mental alertness, improved memory functioning) and a reduced risk of stress, depression and dementia. However, research capturing the benefits of walking among older people in real-time as they navigate their world is currently very limited. This study explores cognitive health and well-being outcomes in older people as they walk in their local neighborhood environment. Residents from an independent living facility for older people (mean age 65, n = 11) walked from their home in two dichotomous settings, selected on the basis of significantly different infrastructure, varying levels of noise, traffic and percentage of green space. Employing a repeated-measures, cross over design, participants were randomly allocated to one of two groups, and walked on different days in an urban busy “gray” district (a busy, built up commercial street) vs. an urban quiet “green” district (a quiet residential area with front gardens and street trees). Our study captured real-time air quality and noise data using hand-held Airbeam sensors and physiologic health data using a smart watch to capture heart rate variability (a biomarker of stress). Cognitive health outcome measures were a pre- and post-walk short cognitive reaction time (SRT) test and memory recall of the route walked (captured via a drawn mental map). Emotional well-being outcomes were a pre- and post-walk mood scale capturing perceived stress, happiness and arousal levels. Findings showed significant positive health benefits from walking in the urban green district on emotional well-being (happiness levels) and stress physiology (p < 0.05), accompanied by faster cognitive reaction times post-walk, albeit not statistically significant in this small sample. Cognitive recall of the route varied between urban gray and urban green conditions, as participants were more likely to rely on natural features to define their routes when present. The environmental and physiologic data sets were converged to show a significant effect of ambient noise and urban conditions on stress activation as measured by heart rate variability. Findings are discussed in relation to the complexity of combining real-time environmental and physiologic data and the implications for follow-on studies. Overall, our study demonstrates the viability of using older people as citizen scientists in the capture of environmental and physiologic stress data and establishes a new protocol for exploring relationships between the built environment and cognitive health in older people.

Walkable Urban Environments: An Ergonomic Approach of Evaluation

Background. The salutogenicity of urban environments is significantly affected by their ergonomics, i.e., by the quality of the interactions between citizens and the elements of the built environment. Measuring and modelling urban ergonomics is thus a key issue to provide urban policy makers with planning solutions to increase the well-being, usability and safety of the urban environment. However, this is a difficult task due to the complexity of the interrelations between the urban environment and human activities. The paper contributes to the definition of a generalized model of urban ergonomics and salutogenicity, focusing on walkability, by discussing the relevant parameters from the large and variegated sets proposed in the literature, by discussing the emerging model structure from a data mining process, by considering the background of the relevant functional dependency already established in the literature, and by providing evidence of the solutions’ effectiveness. The methodology is developed for a case study in central Italy, with a focus on the mobility issue, which is a catalyst to generate more salutogenic and sustainable behaviors.

Relationships between health outcomes in older populations and urban green infrastructure size, quality and proximity

Background

There is a growing body of literature supporting positive associations between natural environments and better health. The type, quality and quantity of green and blue space (‘green-space’) in proximity to the home might be particularly important for less mobile populations, such as for some older people. However, considerations of measurement and definition of green-space, beyond single aggregated metrics, are rare. This constitutes a major source of uncertainty in current understanding of public health benefits derived from natural environments. We aimed to improve our understanding of how such benefits are conferred to different demographic groups through a comprehensive evaluation of the physical and spatial characteristics of urban green infrastructure.

Methods

We employed a green infrastructure (GI) approach combining a high-resolution spatial dataset of land-cover and function with area-level demographic and socio-economic data. This allowed for a comprehensive characterization of a densely populated, polycentric city-region. We produced multiple GI attributes including, for example, urban vegetation health. We used a series of step-wise multi-level regression analyses to test associations between population chronic morbidity and the functional, physical and spatial components of GI across an urban socio-demographic gradient.

Results

GI attributes demonstrated associations with health in all socio-demographic contexts even where associations between health and overall green cover were non-significant. Associations varied by urban socio-demographic group. For areas characterised by having higher proportions of older people (‘older neighbourhoods’), associations with better health were exhibited by land-cover diversity, informal greenery and patch size in high income areas and by proximity to public parks and recreation land in low income areas. Quality of GI was a significant predictor of good health in areas of low income and low GI cover. Proximity of publicly accessible GI was also significant.

Conclusions

The influence of urban GI on population health is mediated by green-space form, quantity, accessibility, and vegetation health. People in urban neighbourhoods that are characterised by lower income and older age populations are disproportionately healthy if their neighbourhoods contain accessible, good quality public green-space. This has implications for strategies to decrease health inequalities and inform international initiatives, such as the World Health Organisation’s Age-Friendly Cities programme.

Relevance of the Cell Neighborhood Size in Landscape Metrics Evaluation and Free or Open Source Software Implementations

Landscape metrics constitute one of the main tools for the study of the changes of the landscape and of the ecological structure of a region. The most popular software for landscape metrics evaluation is FRAGSTATS, which is free to use but does not have free or open source software (FOSS). Therefore, FOSS implementations, such as QGIS’s LecoS plugin and GRASS’ r.li modules suite, were developed. While metrics are defined in the same way, the “cell neighborhood” parameter, specifying the configuration of the moving window used for the analysis, is managed differently: FRAGSTATS can use values of 4 or 8 (8 is default), LecoS uses 8 and r.li 4. Tests were performed to evaluate the landscape metrics variability depending on the “cell neighborhood” values: some metrics, such as “edge density” and “landscape shape index”, do not change, other, for example “patch number”, “patch density”, and “mean patch area”, vary up to 100% for real maps and 500% for maps built to highlight this variation. A review of the scientific literature was carried out to check how often the value of the “cell neighborhood” parameter is explicitly declared. A method based on the “aggregation index” is proposed to estimate the effect of the uncertainty on the “cell neighborhood” parameter on landscape metrics for different maps.