A solution to cope with chaotic urban settlements and frenetic everyday life is refuging in nature as a way to reduce stress. In general—in recent years—it has been scientifically demonstrated how natural areas are an important environment for psycho-physiological health. As a consequence, it is important to plan dedicated spaces for stress recovery in order to increase the well-being of people. With respect to forests, there is a growing interest in understanding the marketing and tourist potential of forest-therapy activities and policies. This paper develops a decision support system (DSS) for decision makers, based on geographic information system to define the suitability of forest areas to improve psychological and physiological human well-being. Innovative technologies such as electroencephalography (EEG) and virtual reality (VR) are applied to test human status. The DSS combines four sets of indicators in a multi-attribute decision analysis and identifies the areas with the largest stress-recovery potential. Two multi-attribute model—one in summer and one in winter—are elaborated to obtain a dynamic evaluation of suitability. Results show significant differences among forest type, forest management, altitude range, and season in terms of stand suitability. EEG and VR seem to be promising technologies in this research area. Strengths and weaknesses of the approach, as well as potential future improvement and implications for territorial marketing, are suggested.

A Spatial Multi-criteria Decision Support System for Stress Recovery-Oriented Forest Management / Capecchi, Irene; Grilli, Gianluca; Barbierato, Elena; Sacchelli, Sandro. - (2021), pp. 171-184. (Intervento presentato al convegno 3rd International conference on Smart and Sustainable Planning for Cities and Regions, SSPCR 2019 tenutosi a Bolzano nel 9th-13th December 2019) [10.1007/978-3-030-57764-3_12].

A Spatial Multi-criteria Decision Support System for Stress Recovery-Oriented Forest Management

Grilli, Gianluca;
2021-01-01

Abstract

A solution to cope with chaotic urban settlements and frenetic everyday life is refuging in nature as a way to reduce stress. In general—in recent years—it has been scientifically demonstrated how natural areas are an important environment for psycho-physiological health. As a consequence, it is important to plan dedicated spaces for stress recovery in order to increase the well-being of people. With respect to forests, there is a growing interest in understanding the marketing and tourist potential of forest-therapy activities and policies. This paper develops a decision support system (DSS) for decision makers, based on geographic information system to define the suitability of forest areas to improve psychological and physiological human well-being. Innovative technologies such as electroencephalography (EEG) and virtual reality (VR) are applied to test human status. The DSS combines four sets of indicators in a multi-attribute decision analysis and identifies the areas with the largest stress-recovery potential. Two multi-attribute model—one in summer and one in winter—are elaborated to obtain a dynamic evaluation of suitability. Results show significant differences among forest type, forest management, altitude range, and season in terms of stand suitability. EEG and VR seem to be promising technologies in this research area. Strengths and weaknesses of the approach, as well as potential future improvement and implications for territorial marketing, are suggested.
2021
Smart and Sustainable Planning for Cities and Regions: Results of SSPCR 2019: Open Access Contributions
Cham, CH
Springer
978-3-030-57763-6
978-3-030-57764-3
Capecchi, Irene; Grilli, Gianluca; Barbierato, Elena; Sacchelli, Sandro
A Spatial Multi-criteria Decision Support System for Stress Recovery-Oriented Forest Management / Capecchi, Irene; Grilli, Gianluca; Barbierato, Elena; Sacchelli, Sandro. - (2021), pp. 171-184. (Intervento presentato al convegno 3rd International conference on Smart and Sustainable Planning for Cities and Regions, SSPCR 2019 tenutosi a Bolzano nel 9th-13th December 2019) [10.1007/978-3-030-57764-3_12].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/413391
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