scholarly journals Assessing Emotional Responses to the Spatial Quality of Urban Green Spaces through Self-Report and Face Recognition Measures

2021 ◽  
Vol 18 (16) ◽  
pp. 8526
Author(s):  
Lin Qiao ◽  
Jingwei Zhuang ◽  
Xuan Zhang ◽  
Yang Su ◽  
Yiping Xia
Keyword(s):  
Face Recognition ◽  
Emotional Responses ◽  
Assessment Method ◽  
The Self ◽  
Self Report ◽  
Green Spaces ◽  
Recognition Model ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Spatial Quality

Although creating a high-quality urban green space (UGS) is of considerable importance in public health, few studies have used individuals’ emotions to evaluate the UGS quality. This study aims to conduct a multidimensional emotional assessment method of UGS from the perspective of spatial quality. Panoramic videos of 15 scenes in the West Lake Scenic Area were displayed to 34 participants. For each scene, 12 attributes regarding spatial quality were quantified, including perceived plant attributes, spatial structure attributes, and experiences of UGS. Then, the Self-Assessment-Manikin (SAM) scale and face recognition model were used to measure people’s valence-arousal emotion values. Among all the predictors, the percentages of water and plants were the most predictive indicators of emotional responses measured by SAM scale, while the interpretation rate of the model measured by face recognition was insufficiently high. Concerning gender differences, women experienced a significantly higher valence than men. Higher percentages of water and plants, larger sizes, approximate shape index, and lower canopy densities were often related to positive emotions. Hence, designers must consider all structural attributes of green spaces, as well as enrich visual perception and provide various activities while creating a UGS. In addition, we suggest combining both physiological and psychological methods to assess emotional responses in future studies. Because the face recognition model can provide objective measurement of emotional responses, and the self-report questionnaire is much easier to administer and can be used as a supplement.

scholarly journals The Socioeconomic Welfare of Urban Green Areas and Parks; A Literature Review of Available Evidence

2021 ◽  
Vol 13 (14) ◽  
pp. 7863
Author(s):  
Antonios Kolimenakis ◽  
Alexandra D. Solomou ◽  
Nikolaos Proutsos ◽  
Evangelia V. Avramidou ◽  
Evangelia Korakaki ◽  
...  
Keyword(s):  
Literature Review ◽  
Urban Policy ◽  
Green Spaces ◽  
Future Research ◽  
Natural Environments ◽  
Exclusion Criteria ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Urban Green Areas ◽  
Green Areas

Urban green areas present a lucid example for the harmonious co-existence of the artificial and natural environments best illustrated by their interdependence and interconnection in urban spaces. Urban green areas are essential for the health and wellbeing of citizens. The present study aimed to investigate those multiple benefits for citizens that arise through the existence of urban green areas, as well as important policy dimensions that should be considered when designing the expansion of urban green spaces in urban development. The study was based on a literature review to examine for available evidence on the benefit levels derived by the existence of urban green areas. An extended literature review was followed by a structured review, based on specific inclusion and exclusion criteria, which partly followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search was conducted in two databases, and a total of 1674 articles and abstracts were identified through the database searches. After removing 114 duplicates, 1560 records were initially screened based on title and abstract. Following inclusion and exclusion criteria, 14 articles were incorporated in the structured review and a total of 47 in the extended review. The extended literature review identified 33 additional articles examining aspects of benefits that did not fall under the pre-established inclusion and exclusion criteria used in the structured review, such as health benefits and other social parameters associated with urban green spaces. The selected studies were allocated in five principal groups according to study types: three of the them consisted of studies employing “willingness to pay” (WTP) methods, five were based on property values, two studies assigned monetary values, while another two assigned CO2 values, and, finally, two studies were based on qualitative criteria. The results indicated benefits to citizens and increased welfare levels gained by the existence of urban green areas. The conducted review revealed a number of findings and recommendations that could direct future research and urban policy. Those hints could assist local authorities as well as stakeholders in order to measure and assess the benefits of green spaces and urban parks and promote measures and programs to assist their further deployment.

Social inequalities in the associations between urban green spaces, self-perceived health and mortality in Brussels: Results from a census-based cohort study

2021 ◽  
Vol 70 ◽  
pp. 102603
Author(s):  
Lucía Rodriguez-Loureiro ◽  
Lidia Casas ◽  
Mariska Bauwelinck ◽  
Wouter Lefebvre ◽  
Charlotte Vanpoucke ◽  
...  
Keyword(s):  
Cohort Study ◽  
Social Inequalities ◽  
Perceived Health ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Health And Mortality

scholarly journals Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

2021 ◽  
Vol 10 (4) ◽  
pp. 251
Author(s):  
Christina Ludwig ◽  
Robert Hecht ◽  
Sven Lautenbach ◽  
Martin Schorcht ◽  
Alexander Zipf
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Open Data ◽  
Green Spaces ◽  
Data Sets ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Urban Quality Of Life ◽  
Shafer Theory ◽  
Sentinel 2

Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) data for urban green space mapping is high but limited due to their respective uncertainties. Sentinel-2 imagery cannot distinguish public from private green spaces and its spatial resolution of 10 m fails to capture fine-grained urban structures, while in OSM green spaces are not mapped consistently and with the same level of completeness everywhere. To address these limitations, we propose to fuse these data sets under explicit consideration of their uncertainties. The Sentinel-2 derived Normalized Difference Vegetation Index was fused with OSM data using the Dempster–Shafer theory to enhance the detection of small vegetated areas. The distinction between public and private green spaces was achieved using a Bayesian hierarchical model and OSM data. The analysis was performed based on land use parcels derived from OSM data and tested for the city of Dresden, Germany. The overall accuracy of the final map of public urban green spaces was 95% and was mainly influenced by the uncertainty of the public accessibility model.

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