Configuration Of Green Spaces Research Articles

Research on the aging-suitability of community outdoor spaces in Zhengzhou based on the analytic hierarchy process and semantic differential method

BackgroundAs global populations age, the suitability of community outdoor spaces for older adult residents has become a critical urban planning concern. However, comprehensive evaluation methods for assessing these spaces are lacking. Objective: This study aims to evaluate the aging-suitability of community outdoor spaces in Zhengzhou, China, and provide optimization suggestions for urban planners and policymakers.MethodsAn evaluation index system was established using the analytic hierarchy process (AHP), with aging-suitability as the goal layer. The criteria layer included outdoor behavioral activities, green space configuration, transportation and road systems, and basic service facilities. The semantic differential (SD) method was employed to conduct a comprehensive evaluation among older adult residents in three communities (A, B, and C) in Zhengzhou city.ResultsThe evaluation revealed that older adult residents generally had a favorable assessment of their community spaces’ aging-suitability. Community A received the highest overall rating. Green space configuration and transportation systems emerged as critical factors influencing aging-suitability.ConclusionThe combined AHP-SD approach proved effective in evaluating the aging-suitability of community outdoor spaces. The study identified key areas for improvement in each community, with variations in strengths and weaknesses across the three sites. Implications: Based on the findings, optimization suggestions are proposed in four aspects: enhancing outdoor behavioral activities, improving green space landscapes, refining road transportation systems, and upgrading basic service facilities. These recommendations can guide urban planners and policymakers in creating more age-friendly community environments.

Greenness and excess deaths from heat in 323 Latin American cities: Do associations vary according to climate zone or green space configuration?

Green vegetation may protect against heat-related death by improving thermal comfort. Few studies have investigated associations of green vegetation with heat-related mortality in Latin America or whether associations are modified by the spatial configuration of green vegetation. We used data from 323 Latin American cities and meta-regression models to estimate associations between city-level greenness, quantified using population-weighted normalized difference vegetation index values and modeled as three-level categorical terms, and excess deaths from heat (heat excess death fractions [heat EDFs]). Models were adjusted for city-level fine particulate matter concentration (PM2.5), social environment, and country group. In addition to estimating overall associations, we derived estimates of association stratified by green space clustering by including an interaction term between a green space clustering measure (dichotomized at the median of the distribution) and the three-level greenness variable. We stratified analyses by climate zone (arid vs. temperate and tropical combined). Among the 79 arid climate zone cities, those with moderate and high greenness levels had modestly lower heat EDFs compared to cities with the lowest greenness, although protective associations were more substantial in cities with moderate versus high greenness levels and confidence intervals (CI) crossed the null (Beta: −0.41, 95% CI: −1.06, 0.25; Beta −0.23, 95% CI: −0.95, 0.49, respectively). In 244 non-arid climate zone cities, associations were approximately null. We did not observe evidence of effect modification by green space clustering. Our results suggest that greenness may offer modest protection against heat-related mortality in arid climate zone Latin American cities.

Influence of urban green space landscape pattern on river water quality in a highly urbanized river network of Hangzhou city

Optimizing urban green space landscape patterns is a key goal for improving river water quality. However, little is known about the spatial heterogeneity of the impact of urban green spatial patterns on river-water environments. This study investigated the influence of urban green space patterns on the spatiotemporal heterogeneity of river water quality in the Hangzhou section of the Beijing-Hangzhou Canal through exploratory regression analysis and a combination of geographically weighted regression analysis (GWR) and spatial interpolation. The results show that (1) total nitrogen (TN) and nitrate nitrogen (NO3–-N) are the leading indicators of river pollution in the study area, (2) green space configuration is more crucial for improving water quality than composition, and (3) GWR can effectively explain the impact of urban green space on river water quality. For example, landscape shape and edge indices have a great impact on ammonia nitrogen (NH4+-N), TN and total phosphorus (TP); the more complex the shape and edge of the green space, the more beneficial it is for water purification. The interpretation of NO3–-N is complex and mainly influenced by the largest patch index (LPI) and landscape composition. Given the limited land availability in urban area, the spatial configuration of urban green space should be optimized without additional land use to minimize the non-point source (NPS) pollution with the smallest possible green space area. The proposed approach provides a new understanding of the interaction between spatial patterns of green space and the urban water environment, and valuable information for developing green space planning policies for local sites.

Monitoring and assessment of urban green space loss and fragmentation using remote sensing data in the four cities of Malawi from 1986 to 2021

Urban green spaces enhance cities' natural beauty, boost biodiversity, and promote the health and happiness of city residents, among other benefits. Despite the benefits of urban green spaces, their spatial configuration and composition are impacted by urban expansion. This study aims to investigate the spatial-temporal fragmentation trends of urban green spaces in four cities in Malawi (Blantyre, Zomba, Lilongwe, and Mzuzu). We, therefore, applied multi-temporal Landsat images to understand trends in urban green spaces from 1986 to 2021. Five landscape metrics, namely: percentage of land area (PLAND), number of patches (NP), patch density, largest patch index (LPI), landscape shape index (LSI), and mean patch size (MPS), were used to quantify the degree of urban green space fragmentation in Fragstats software. The results showed an increase in the NP, PD, and LSI and a decline in the LPI and MPA in the four cities. This is an indication of fragmentation and a reduction in green space. Rapid urbanisation has resulted in the loss and fragmentation of urban green space areas, which has been attributed to the rapid expansion of built-up areas at the expense of green spaces. The present study is the first to incorporate landscape metrics to understand the spatial heterogeneity of the composition and configuration of green spaces in all the cities of Malawi. The findings of this study contribute to an understanding of how urban growth impacts fragmentation and the loss of urban green spaces and offer valuable insights for better spatial planning and management of cities.

Concatenating Daily Exercise Routes with Public Sports Facilities, Bicycle Lanes, and Green Spaces: A Feasibility Analysis in Nanjing, China

Public sports facilities have the potential to improve their functions as active living infrastructures (ALIs) in combination with bicycle lanes and green spaces. A favorable sequence of exercise intensities in different scenes is important for individuals to take physical activity scientifically. Our research aimed to explore the feasibility of promoting and consolidating this sequence using reasonable daily exercise routes concatenated by public sports facilities, green spaces, and bicycle lanes. Taking 25 major public sports facilities in Nanjing as an example, we obtained the cycling routes from open-source data and delineated the facilities’ cycling catchment areas to assess the coordination of bicycle lanes and facilities. Further, we evaluated the potential interactions between facilities and green spaces by checking the spatial intersections between park entrances and the above routes. The results revealed that with the integration of bicycle lanes, public sports facilities could provide services to most residential areas, and potential interactions between the facilities and parks existed already. Therefore, it was feasible to design reasonable daily exercise routes coupled with the existing facility layout. Moreover, the service gaps and potential interactions were affected by the layout of the facilities, the density of the bicycle lanes, the configuration of green spaces, and the official planning proposals. This research advances the understanding of how public sports facilities can be pivotal to the cooperation of ALIs with other infrastructures.

Integrated Effects of Building Morphology and Green Space Configuration on Thermal Environment and Air Quality in a Station Square

Integrated Effects of Building Morphology and Green Space Configuration on Thermal Environment and Air Quality in a Station Square

Urban green space alone is not enough: A landscape analysis linking the spatial distribution of urban green space to mental health in the city of Chicago

Research on the association between urban green space and mental health has largely focused on the presence or quantity of green space, rather than on the spatial distribution of green spaces within the urban landscape. We therefore investigated the relationship between the amount, composition, and spatial distribution of urban green space and the level of psychological distress reported by residents of a large metropolitan city (Chicago, Illinois, USA). We used mental health data collected from 6405 residents in 61 communities by the Chicago Department of Public Health as part of their Healthy Chicago Survey, and quantified landscape metrics related to the amount and configuration of green space within these community ‘landscapes’. Using generalized linear mixed models that controlled for socio-economic confounds, we found that residents reported less psychological distress within urban landscapes that had small-sized water bodies and greater distances between forested areas, which tend to characterize the distribution of large forest parks throughout Chicago. In terms of total green space, however, psychological distress levels were lower in landscapes having a disaggregated distribution of urban green spaces (i.e., many small green spaces) relative to a single (or a few) large green spaces. Our study thus highlights that the configuration of urban green space may be as important as the amount of green space to the mental health of urban residents.

Green space configuration and its impact on human behavior and URBAN environments

Trees and green spaces are part of the environmental systems that are essential to the quality of human life in urban spaces. In general, Brazilian cities have a high proportion of impermeable surfaces which affect the urban microclimate. This paper examined the impact of vegetation presence and configuration on human behavior in three downtown squares in Aracaju, Brazil. The monitored period was summer in 2014–2015. The study collected data on the microclimates of urban squares, conducted surveys of urban features and pedestrian preferences, and developed human behavior maps. Results showed that the green spaces provided more stable microclimates during the day and lower surface temperatures than other urban settings in the squares, which provided a more comfortable thermal environment for people. However, the preferences of pedestrians were not aligned to green spaces in the human behavior maps in two of these squares. It was found that the configuration of the landscape design in squares and surrounding commercial activity influenced human behavior more than the microclimate benefits of vegetation in the urban environment. Urban planning laws can be used to adjust the design and environmental conditions in highly developed urban centers to increase thermal comfort or climate resilience.

Detecting factors controlling spatial patterns in urban land surface temperatures: A case study of Beijing

Exploring the driving forces responsible for heterogeneous surface temperatures is important for selecting proper mitigation strategies to improve the urban thermal environment. Many previous studies have examined the relationship between Land Surface Temperature (LST) and landscape composition and configuration of greenspace. However, investigations focused on the influence of artificial surface on LST are limited. This study develops a method for exploring the driving forces of LST heterogeneity at various spatial scales in Beijing, China. We classified LSTs into six sequential temperature classes to which we applied stepwise regression analysis to detect factors controlling LST variation. We found that: (1) high and low temperature patches were unevenly distributed across the city, with high temperature patches often forming high temperature belts that might negate the expected environmental benefits of planned urban greenspaces, (2) the explanatory power of parameters significantly associated with LST variation was noticeably reduced at finer spatial scales, and (3) variations in significant parameters in low temperature areas can serve as reference target for improving the thermal environment of high temperature areas. Our findings provide insights that can be used to mitigate the impact of urbanization on the thermal environments of cities and achieve the sustainable urban development.

Effects of green space on walking: Does size, shape and density matter?

The role of the built environment in improving public health through fostering physical activity has come under increased scrutiny in recent years. This study investigates relationships between walking activity and the configuration of green spaces in Greater London. Pedestrian activity for N = 54,910 walking trip stages is gathered through the London Travel Demand Survey (LTDS), with routes between origin and destination mapped onto the street network from the Integrated Transport Network of Ordnance Survey. Green spaces were extracted from UKMap and agglomerated to form London’s hundreds of parks. Regressions of pedestrian activity on park configuration, controlling for built environment metrics, revealed that catchments around smaller parks have more walking trips. Irregularity of park shape has the opposite effect. Park density, measured as number of parks inside a catchment, is insignificant in regression. Parks adjacent to retail areas were associated with pronounced increases in walking. The study contributes to landscape, urban management, environmental policy and urban planning and design literature. The evidence provides implications for performance-oriented policy and design decisions that configure a city’s green spaces to improve citizens’ public health through enhancing walkability.

Assessment of the Effect of Neyshabur Green Spatial Configuration on the Temperature of Land Surface and Heat Islands

Urban heat island is a global issue and a consequence of rapid urbanization that leads to higher land surface temperature in urban areas. The range is 0.6°C - 1.3°C compared to rural and suburban areas. LST (Land surface temperature) is an important parameter in determining the heat island. Understanding the relationship between green space configuration and LST is essential to the effective design of the mechanisms, which reduce the effect of urbanization on UHI (urban heat island). This study examines the correlation between LST and spatial configuration of green space in the urban landscape of Neyshabur city, Iran. Satellite images are obtained from Landsat ETM+ satellite sensor with a spatial resolution of 60 meters in August 2010 and used for the estimation of LST. In order to identify the configuration of green space, five configuration metrics LSI (landscape Shape Index), MPFD (Mean Patch Fractal Dimension), ED (Edge Density), MPS (Mean Patch Size) and MSI (Mean Shape Index) are used. In addition, configuration of the green space and temperature is compared by Pearson’s correlation-coefficient. Negative values represent a suppressive/negative effect on each other; the fact that other indicators of spatial configuration are inversely related to temperature means that they weaken the effect of UHI. Results of the study showed that the spatial configuration of the green space notably affects increased LST and UHI. On the other hand, the configuration indicator with the greatest impact on LST was ED, because with increase in margin density further decreases LST.

Land Surface Temperature with Land Cover Classes in ASTER and Landsat Data

Land surface temperature (LST) from satellite data is a challenging task due to the atmospheric absorption and diversification of earth surface emissivity. The analysis show that land surface temperature influenced by water content or vegetation condition. The combination of HDF Explorer and ArcGIS software was useful for automatically processing the pixel latitude, longitude and brightness temperature (BT) information from the ASTER HDF and Landsat imagery files. Forest areas with more moisture and water body have shown smaller temperature than settlements. The urban area refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding vegetation areas. A lookup table of effective temperature anomalies is constructed based on the BT to resolve the inconsistencies between infrared and BT variation. Here ASTER and Landsat data show similar behavior for all land cover classes temperature. The results can be referred to similar areas of the world for LST retrieval or land surface process research, in particular under extreme bad weather conditions. So mitigation of the high temperature effects via the configuration of green spaces and sustainable designs of urban environments have become an issue of increasing concern under changing climate.

Understanding the dynamic of greenspace in the urbanized area of Beijing based on high resolution satellite images

Urban greenspace plays an essential role in urban ecosystem and highly contributes to the welfare of urban residents. Understanding the dynamics of greenspace is crucial for its planning and management. Previous studies have largely focused on changes in greenspace in urbanizing regions, using medium resolution remotely sensed data. However, the changes of greenspace in urbanized areas need to be accurately quantified based on high spatial resolution images because they are directly related to human health and well-being. This paper aims to enhance the understanding on dynamics of greenspace within well-developed areas of the city, using Beijing City, China as a case study. Using high spatial resolution remotely sensed imagery, we analyzed the spatial pattern of greenspace and its change on two scales: (1) the entire area within the 5th ring road, and (2) in 4 belts from urban center to fringe. We found urban greenspace was very dynamic. The proportion of urban greenspace increased by 5.45%, or 36.3km2 in size from 2005 to 2009. The amounts of gain and loss of greenspace were 69km2 and 32.7km2, respectively, or 10.36% and 4.91% of the entire study area. Because of the very limited lands for greening in urbanized areas, the new patches of greenspace were generally small, with the mean patch size of 676.31m2. However, those small patches enhanced the connectivity and continuity of urban greenspace. In addition, we found the differences in configuration of greenspace patches across the 4 belts were greater than the differences in total percent cover, indicating that compared to percent coverage, greenspace configuration may be more influenced by the development age.

Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation

The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding rural areas. Mitigation of the UHI effects via the configuration of green spaces and sustainable design of urban environments has become an issue of increasing concern under changing climate. In this paper, the effects of the composition and configuration of green space on land surface temperatures (LST) were explored using landscape metrics including percentage of landscape (PLAND), edge density (ED) and patch density (PD). An oasis city of Aksu in Northwestern China was used as a case study. The metrics were calculated by moving window method based on a green space map derived from Landsat Thematic Mapper (TM) imagery, and LST data were retrieved from Landsat TM thermal band. A normalized mutual information measure was employed to investigate the relationship between LST and the spatial pattern of green space. The results showed that while the PLAND is the most important variable that elicits LST dynamics, spatial configuration of green space also has significant effect on LST. Though, the highest normalized mutual information measure was with the PLAND (0.71), it was found that the ED and PD combination is the most deterministic factors of LST than the unique effects of a single variable or the joint effects of PLAND and PD or PLAND and ED. Normalized mutual information measure estimations between LST and PLAND and ED, PLAND and PD and ED and PD were 0.7679, 0.7650 and 0.7832, respectively. A combination of the three factors PLAND, PD and ED explained much of the variance of LST with a normalized mutual information measure of 0.8694. Results from this study can expand our understanding of the relationship between LST and street trees and vegetation, and provide insights for sustainable urban planning and management under changing climate.

Spatial pattern of greenspace affects land surface temperature: evidence from the heavily urbanized Beijing metropolitan area, China

The urban heat island describes the phenomenon that air/surface temperatures are higher in urban areas compared to their surrounding rural areas. Numerous studies have shown that increased percent cover of greenspace (PLAND) can significantly decrease land surface temperatures (LST). Fewer studies, however, have investigated the effects of configuration of greenspace on LST. This paper aims to fill this gap using Beijing, China as a case study. PLAND along with six configuration metrics were used to measure the composition and configuration of greenspace. The metrics were calculated based on a greenspace map derived from SPOT imagery, and LST data were retrieved from Landsat TM thermal band. Ordinary least squares regression and spatial autoregression were employed to investigate the relationship between LST and spatial pattern of greenspace using the census tract as the analytical unit. The results showed that PLAND was the most important predictor of LST. A 10 % increase in PLAND resulted in approximately a 0.86 °C decrease in LST. Configuration of greenspace also significantly affected LST. Given a fixed amount of greenspace, LST increased significantly with increased patch density. In addition, the variance of LST was largely explained by both composition and configuration of greenspace. The unique variation explained by the composition was relatively small, and was close to that of the configuration. Results from this study can expand our understanding of the relationship between LST and vegetation, and provide insights for improving urban greenspace planning and management.