Reprint

Landsenses in Green Spaces

Edited by
April 2024
292 pages
  • ISBN978-3-7258-0602-7 (Hardback)
  • ISBN978-3-7258-0601-0 (PDF)

This book is a reprint of the Special Issue Landsenses in Green Spaces that was published in

Biology & Life Sciences
Environmental & Earth Sciences
Summary

The term “landsenses” is derived from “landsenses ecology”, a recently emerging scientific discipline grounded in ecological principles and an analytical framework encompassing natural elements, physical senses, psychological perceptions, socio-economic perspectives, process risk and related aspects. Landsenses emphasize the incorporation of human perception from sensory and psychological dimensions into ecological environmental research. Within this framework, we believe the theory advanced by landsense ecology not only offers an effective avenue for investigating the relationship between humans and the environment, but also serves as a crucial methodological and technical approach for the development of green spaces in the context of constructing smart and resilient cities. This reprint comprises 13 papers encompassing multi-sensory studies conducted in green spaces and an editorial published in the Special Issue of Forests titled “Landsenses in Green Spaces”.

Format
  • Hardback
License
© 2024 by the authors; CC BY-NC-ND license
Keywords
soundscape; waterfront space in mountainous cities; spatial elements; multisensory interaction; forest-type temple; urban-type temple; Han Chinese Buddhism; soundscape evaluation; influencing factors; landscape; soundscape; sound perception; visiting experience; structural equation model; scenic area; urban park waterfront; psychological response; semantic segmentation; landscape complexity; fractal dimension; eye tracking; preference; urban forest; forest landscape; soundscape preference; elderly; urban forest park; underdeveloped cities in China; subjective evaluation; traditional settlements; ENVI-met; green spaces; outdoor environment; thermal comfort; regional characteristics; soundscape; human perception; prediction model; visual–aural attributes; urban green spaces; landscape pattern; sound dominant degree; soundscape quality; residential area; green space; scale effect; multisensory perception; restoration effects; forest recreation; generative large language model; National Forest Parks; aesthetic sensory; landscape characteristics; traditional villages; public space; specialized garden; plant landscape space; spatial vitality; visitor behavior; landscape features; older adults; restorative environment; residential public space; physio-psychological recovery; n/a