Accumulated evidence claims that urban green spaces (UGS) have a positive impact on the physical and mental health of humans. However, little information is available to clearly reveal what the most important driving factors are for human psychophysiological restoration. In order to unveil this uncertainty, this study employed virtual reality (VR) technology to investigate the physiological (electroencephalogram, EEG), and psychological (attention, positive mood, negative mood) responses and individual preferences for different urban environments. Participants (120) were recruited and randomly assigned to experience six different types of environments varying in land use and vegetation structures, which were: Grey space, blue space, open green space, partly open green space, partly closed green space, and closed green space. The results showed that the experience of the six environmental types through VR devices had positive restorative effects on the individuals’ attentional fatigue and negative mood; however, all the participants obtained the highest levels of physiological stress restoration when asked to close their eyes for relaxation. The physiological measurements of the EEG showed no significant differences among the selected types of environments. Meanwhile, the results of the psychological measures suggested that only negative mood showed significant differences of change among the six types of environments, and while the partly open green space had the most positive effect on negative mood, the closed green space had the worst. The blue space and partly closed green space received higher recreational preference ratings than the other four environments, while the closed green space received the lowest recreational preference rating. Moreover, the findings showed that there was a strong positive correlation between people’s preferences and the improvement of their positive mood. This indicated that as the popularity of a natural environment increased, so did the benefits of human health and well-being. In addition, this study shows that VR technology may be utilized as a possible surrogate measure to real scenes in evaluating human physiological and psychological restoration in the future. The present findings can provide the theoretical basis and practical guidance for future optimal planning of urban restorative environments.

Accurate individual tree segmentation (ITS) is fundamental to forest management and to the studies of forest ecosystem. Unmanned Aerial Vehicle Light Detection and Ranging (UAV-LiDAR) shows advantages for ITS and tree height estimation at stand and landscape scale. However, dense deciduous forests with tightly interlocked tree crowns challenge the performance for ITS. Available LiDAR points through tree crown and appropriate algorithm are expected to attack the problem. In this study, a new UAV-LiDAR dataset that fused leaf-off and leaf-on point cloud (FULD) was introduced to assess the synergetic benefits for ITS and tree height estimation by comparing different types of segmentation algorithms (i.e., watershed segmentation, point cloud segmentation and layer stacking segmentation) in the dense deciduous forests of Northeast China. Field validation was conducted in the four typical stands, including mixed broadleaved forest (MBF), Mongolian oak forest (MOF), mixed broadleaf-conifer forest (MBCF) and larch plantation forest (LPF). The results showed that the combination of FULD and the layer stacking segmentation (LSS) algorithm produced the highest accuracies across all forest types (F-score: 0.70 to 0.85). The FULD also showed a better performance on tree height estimation, with a root mean square error (RMSE) of 1.54 m at individual level. Compared with using the leaf-on dataset solely, the RMSE of tree height estimation was reduced by 0.22 to 0.27 m, and 12.3% more trees were correctly segmented by the FULD, which are mainly contributed by improved detection rate at nearly all DBH levels and by improved detection accuracy at low DBH levels. The improvements are attributed to abundant points from the bole to the treetop of FULD, as well as each layer point being included for segmentation by LSS algorithm. These findings provide useful insights to guide the application of FULD when more multi-temporal LiDAR data are available in future.

In order to identify the effects and divergences of the different landscape perception approaches on landscape preference, this study investigated people’s preferences for urban green spaces with different vegetation structures in the early spring through using three approaches, which were on-site survey, photo elicitation and VR technology. The results showed that: (a) There were significant differences among the three approaches for landscape preference, among which there was a significant difference between VR technology and the other two approaches, while no differences between on-site survey and photo elicitation were found. (b) The respondents showed significant differences in their preferences for the urban green spaces with the different vegetation structures through VR technology, and the semi-open green space received the highest preference score. (c) Whatever the approach employed, there were no significant differences in gender and professional background groups for landscape preference. (d) In the comparisons of the three different approaches, the respondents were more willing to choose physical recreational activities to be conducted in the early spring. Based on the above results, the three approaches of landscape perception were divergent and irreplaceable. It is, thus, suggested that the approach of landscape perception should be carefully selected for a specific landscape in a certain season, so as to provide a scientific basis for the evaluation of landscape perception and preference in the future.

The world is facing the challenge of aging populations. Urban natural environments, including green spaces and blue spaces, have been demonstrated to have great benefits to the mental restoration of the elderly. However, the study of the specific characteristics of urban environments that are popular and the most restorative for the elderly is still lacking. Photo elicitation as visual stimuli was utilized to explore the differences in preference and psychological restoration of the elderly through the perception of the eight perceived sensory dimensions (PSDs) in different types of urban environments. The results showed that: (1) The respondents had different perceptions of the eight PSDs in the different urban natural environments. Blue space and partly-closed green space were more preferred by the elderly, and also had more psychological restorative effects on the elderly. (2) There was no significant correlation between the number of highly perceived PSDs and preference, as well as between the number of highly perceived PSDs and psychological restoration. However, there was a significant correlation between preference and psychological restoration. (3) Partly-closed green space with more Serene and Refuge qualities, and blue space with more Serene, Refuge and Prospect properties were optimal characteristics for psychological restoration of the elderly. In addition, open green space with more Prospect, Serene and Social qualities, and closed green space with more Space, Refuge and less Nature properties could also increase psychological restoration of older adults. These findings can provide useful guidelines for restorative environmental design for the elderly in the future.

Although the soundscape in cities is receiving increased attention in urban planning, there is still a lack of knowledge of how personal factors influence the perception of and preference for soundscapes. Most present studies are linked to one or a few specific soundscapes and do not have a holistic approach exploring the pros and cons of all soundscapes in a place. This study surveyed individuals to assess how soundscape perceptions and preferences may differ among various attendees of typical urban forest recreational parks in Xi’an, China, using an on-site questionnaire. The respondents (N = 2034) revealed that rare natural sounds were perceived more positively than the dominating artificial sounds. Five main dimensions of social, demographic, and behavioral attributes were found to be linked to the soundscape perceptions and preferences: (1) familiarity of the park and attendees’ age made people more tolerant towards sounds that others find annoying; (2) higher education and higher socio-economic status showed lower tolerance towards sounds; (3) having companions and specific types of recreational use increased the frequent perception of artificial sounds; (4) females generally showed higher sensitivity and lower tolerance than males towards several sounds; and (5) the longer attendees remained in the park, the more positive the overall soundscape preference was. The results indicate that numerous sounds are affecting people’s overall experience in the parks. These findings could help decision-makers and urban forest recreational park designers to formulate relevant strategies for park design that are in tune with varying public needs and expectations towards soundscape. The implementation of human-oriented soundscape design can therefore enhance people’s well-being.