To explore the effects of different types of forest environments for forest therapy, this study focused on forest resting environments. Seven representative forest resting environments found in field research in Beijing were used as independent variables and were shown to subjects by a virtual reality (VR) video. Stress level was used as the dependent variable, and blood pressure, heart rate, salivary amylase, and the Brief Profile of Mood States (BPOMS) were used as physiological and psychological indicators. A between-subjects design was used in the experiment. A total of 96 subjects were randomly assigned to each environment type, and only one type of forest resting environment was observed. Through the relevant sample t-test and one-way analysis of variance, the pre- and post-test data of the indicators were analyzed. This study found that all the seven different types of forest resting environments can produce stress relief effects to some extent. Different types of forest resting environments have different effects on relieving stress. The most natural environment does not have the most significant effect on stress relief. A water landscape has a positive effect on the relief of stress. The conclusions of this study are conducive to the better use of the forest environment for forest therapy services.

Numerous studies have shown that participation in leisure activities not only prevents disease and improves physical health but also benefits mental health by reducing anxiety. The aim of this study was to explore the effects of various leisure activities on anxiety reduction and attention restoration. Five activities were chosen and classified into two groups: indoor and outdoor. Taiwanese students (N=203) each undertook one of the five activities. Results showed that: (a) moderate leisure activity, such as walking, was the best outdoor activity for improving mental health; (b) chatting also reduced anxiety and restored attention; and (c) surfing the Internet and exercising both failed to significantly improve mental health. In addition, outdoor activities were better for restoring attention compared to indoor activities.

Multiple studies have revealed the impact of walkable environments on physical activity. Scholars attach considerable importance to leisure and health-related walking. Recent studies have used Google Street View as an instrument to assess city streets and walkable environments; however, no study has compared the validity of Google Street View assessments of walkable environment attributes to assessments made by local residents and compiled from field visits. In this study, we involved nearby residents and compared the extent to which Google Street View assessments of the walkable environment correlated with assessments from local residents and with field visits. We determined the assessment approaches (local resident or field visit assessments) that exhibited the highest agreement with Google Street View. One city with relatively high-quality walkable environments and one city with relatively low-quality walkable environments were examined, and three neighborhoods from each city were surveyed. Participants in each neighborhood used one of three approaches to assess the walkability of the environment: 15 local residents assessed the environment using a map, 15 participants made a field visit to assess the environment, and 15 participants used Google Street View to assess the environment, yielding a total of 90 valid samples for the two cities. Findings revealed that the three approaches to assessing neighborhood walkability were highly correlated for traffic safety, aesthetics, sidewalk quality, and physical barriers. Compared with assessments from participants making field visits, assessments by local residents were more highly correlated with Google Street View assessments. Google Street View provides a more convenient, low-cost, efficient, and safe approach to assess neighborhood walkability. The results of this study may facilitate future large-scale walkable environment surveys, effectively reduce expenses, and improve survey efficiency.

An unmanned aerial vehicle (UAV) was used to capture high-resolution aerial images of crop fields. Software-based image analysis was performed to classify land uses. The purpose was to help relevant agencies use aerial imaging in managing agricultural production. This study involves five townships in the Chianan Plain of Chiayi County, Taiwan. About 100 ha of farmland in each township was selected as a sample area, and a quadcopter and a handheld fixed-wing drone were used to capture visible-light images and multispectral images. The survey was carried out from August to October 2018 and aerial photographs were captured in clear and dry weather. This study used high-resolution images captured from a UAV to classify the uses of agricultural land, and then employed information from multispectral images and elevation data from a digital surface model. The results revealed that visible-light images led to low interpretation accuracy. However, multispectral images and elevation data increased the accuracy rate to nearly 90%. Accordingly, such images and data can effectively enhance the accuracy of land use classification. The technology can reduce costs that are associated with labor and time and can facilitate the establishment of a real-time mapping database.

The environment can affect people’s health by relieving stress, and rural landscape as a special environment might influence human’s stress relief. This study takes different types of rural landscapes as the research object to explore their impact on stress levels, which are shown by photos. As an independent variable, the rural landscape is divided into three levels: Type 1 (natural landscape), type 2 (productive landscape), and type 3 (artificial landscape). Seventy-three subjects were randomly assigned to each type of rural landscape. Salivary cortisol, blood pressure, heart rate, and a subjective rating state scale (brief profile of mood states, BPOMS) were used as indicators of stress. At the same time, the influence of preference and familiarity on the stress relieving effect was also discussed. A paired t-test and one-way analysis of variance (ANOVA) were used as the main statistical methods. In the results of t-test for pre-posttest, significant difference was observed in high blood pressure, heart rate, and total mood disturbance (TMD) of type 1 and type 2, and the high and low blood pressure of type 3; ANOVA analysis revealed that for the difference of pre-posttest, significant difference was observed in the TMD value among the three types; except for type 3, blood pressure, heart rate, and BPOMS values were significantly affected by preference and familiarity. The conclusions include the following: The three types of rural landscapes have a positive effect on relieving stress; the productive landscape has the best effect on relieving stress; and users’ landscape preferences and familiarity with the environment can affect the effect of stress relief in rural landscapes.

Road traffic accidents are among the top 10 causes of death globally. With regard to potential accidents, if driver reaction time (RT) can be reduced, drivers would have more time to assess the situation and take appropriate action to avoid the accident. As natural elements in the environment can restore human attention, we conducted a random controlled trial to test the effects of road greenness on driver attention and RT. A driving simulator was employed to simulate highways with five road greening doses. During the simulation, an emergency incident was designed and video-displayed, and driver RT in the context of that situation was recorded. A total of 144 participants were recruited. The results revealed that with increased dose of road greening, driver attention level increased. In addition, a higher dose of greening resulted in a shorter RT during an emergency incident.