The paper presents an integrated methodology to assess psychological and physiological responses of people when exposed to forests, with the main objective of assessing the suitability of different stands for stress recovery on the basis of tree species and density. From the methodological viewpoint, the study applies both a Restoration Outcome Scale (ROS) questionnaire and a neuroscientific technique grounded on electro-encephalographic (EEG) measurement. Results show different outcomes for conifers and broadleaves as well as a statistical significance of density in the evaluation of an individual’s emotional state. A forest with a high density of conifers and low density of broadleaves seems to be the proper combination for stress recovery. The differences among psychological stated preferences and EEG trends highlights potential conflict among “needs” and “wants” of people in the topic of stress relief. Potential applications of the research for health care and territorial marketing operations are suggested.

Cities are human ecosystems. Understanding human ecology is important for designing and planning the built environment. The ability to respond to changes and adapt actions in a positive way helps determine the health of cities. Recently, many studies have highlighted the great potential of photographic data shared on the Flickr platform for the analysis of environmental perceptions in landscape and urban planning. Other research works used panoramic images from the Google Street View (GSV) web service to extract urban quality data. Although other researches have used social media to characterize human habitat from an emotional point of view, there is still a lack of knowledge of the correlation between environmental and physical variables of the city and visual perception, especially at a scale suitable for urban planning and design. In ecology, the environmental suitability of a territory for a given biological community is studied through species distribution models (SDM). In this work we have adopted the state of the art of SDM (the ensemble approach) to develop a methodology transferable to cities with different sizes and characteristics that uses data deriving from many sources available on a global scale: social media platform, Google internet services, shared geographical information, remote sensing and geomorphological data. The result of our application in the city of Livorno offers important information on the most significant variables for the conservation, planning and design of urban public spaces at the project scale. However, further research developments will be needed to test the model in cities of different sizes and geographic locations, integrate the model with other social media, other databases and with traditional surveys and improve the quality of indicators that can be derived from information shared on the Internet.

No abstract