Research note : linking sensory perceptions with landscape elements through a combined approach based on prior knowledge and machine learning
- Author
- Tianchen Zheng (UGent) , Quan Pan (UGent) , Xucai Zhang (UGent) , Chenxing Wang, Yan Yan and Tim Van de Voorde (UGent)
- Organization
- Abstract
- Abstract: Challenges remain when assessing cultural ecosystem services (CES) due to the subjective and intangible features. Landsense ecology highlights the individual perception, providing a novel dimension to the CES assessment. Based on landsense ecology, this study aims to identify and correlate landscape elements and sensory perceptions using social media data. Taking the case of Belgian greenspaces, the factors were identified using custom lexicons through unsupervised and weakly supervised learning methods. The perception correlation network was established to link sensory perceptions with landscape elements. Integrating data from different platforms, we found that social elements were perceived frequently and that the most significant perceptions were vision and touch. Results also revealed that the perceptions of vision, hearing and smell were collectively affected by multiple elements, while the perceptions of taste and touch were strongly related to specific elements. Finally, this study encouraged creating multi-sensory spaces in greenspace management.
- Keywords
- Management, Monitoring, Policy and Law, Nature and Landscape Conservation, Ecology, Urban Studies, Cultural Ecosystem Services, Landsense, Text analysis, Landscape element, Sensory perception, CULTURAL ECOSYSTEM SERVICES, URBAN GREEN SPACES, PARKS, EXPERIENCES, NETWORKS, PLACE
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HNAF0M9K9NXZEKJQJ82MR1YK
- MLA
- Zheng, Tianchen, et al. “Research Note : Linking Sensory Perceptions with Landscape Elements through a Combined Approach Based on Prior Knowledge and Machine Learning.” LANDSCAPE AND URBAN PLANNING, vol. 242, 2024, doi:10.1016/j.landurbplan.2023.104928.
- APA
- Zheng, T., Pan, Q., Zhang, X., Wang, C., Yan, Y., & Van de Voorde, T. (2024). Research note : linking sensory perceptions with landscape elements through a combined approach based on prior knowledge and machine learning. LANDSCAPE AND URBAN PLANNING, 242. https://doi.org/10.1016/j.landurbplan.2023.104928
- Chicago author-date
- Zheng, Tianchen, Quan Pan, Xucai Zhang, Chenxing Wang, Yan Yan, and Tim Van de Voorde. 2024. “Research Note : Linking Sensory Perceptions with Landscape Elements through a Combined Approach Based on Prior Knowledge and Machine Learning.” LANDSCAPE AND URBAN PLANNING 242. https://doi.org/10.1016/j.landurbplan.2023.104928.
- Chicago author-date (all authors)
- Zheng, Tianchen, Quan Pan, Xucai Zhang, Chenxing Wang, Yan Yan, and Tim Van de Voorde. 2024. “Research Note : Linking Sensory Perceptions with Landscape Elements through a Combined Approach Based on Prior Knowledge and Machine Learning.” LANDSCAPE AND URBAN PLANNING 242. doi:10.1016/j.landurbplan.2023.104928.
- Vancouver
- 1.Zheng T, Pan Q, Zhang X, Wang C, Yan Y, Van de Voorde T. Research note : linking sensory perceptions with landscape elements through a combined approach based on prior knowledge and machine learning. LANDSCAPE AND URBAN PLANNING. 2024;242.
- IEEE
- [1]T. Zheng, Q. Pan, X. Zhang, C. Wang, Y. Yan, and T. Van de Voorde, “Research note : linking sensory perceptions with landscape elements through a combined approach based on prior knowledge and machine learning,” LANDSCAPE AND URBAN PLANNING, vol. 242, 2024.
@article{01HNAF0M9K9NXZEKJQJ82MR1YK,
abstract = {{Abstract: Challenges remain when assessing cultural ecosystem services (CES) due to the subjective and intangible features. Landsense ecology highlights the individual perception, providing a novel dimension to the CES assessment. Based on landsense ecology, this study aims to identify and correlate landscape elements and sensory perceptions using social media data. Taking the case of Belgian greenspaces, the factors were identified using custom lexicons through unsupervised and weakly supervised learning methods. The perception correlation network was established to link sensory perceptions with landscape elements. Integrating data from different platforms, we found that social elements were perceived frequently and that the most significant perceptions were vision and touch. Results also revealed that the perceptions of vision, hearing and smell were collectively affected by multiple elements, while the perceptions of taste and touch were strongly related to specific elements. Finally, this study encouraged creating multi-sensory spaces in greenspace management.}},
articleno = {{104928}},
author = {{Zheng, Tianchen and Pan, Quan and Zhang, Xucai and Wang, Chenxing and Yan, Yan and Van de Voorde, Tim}},
issn = {{0169-2046}},
journal = {{LANDSCAPE AND URBAN PLANNING}},
keywords = {{Management, Monitoring, Policy and Law,Nature and Landscape Conservation,Ecology,Urban Studies,Cultural Ecosystem Services,Landsense,Text analysis,Landscape element,Sensory perception,CULTURAL ECOSYSTEM SERVICES,URBAN GREEN SPACES,PARKS,EXPERIENCES,NETWORKS,PLACE}},
language = {{eng}},
pages = {{13}},
title = {{Research note : linking sensory perceptions with landscape elements through a combined approach based on prior knowledge and machine learning}},
url = {{http://doi.org/10.1016/j.landurbplan.2023.104928}},
volume = {{242}},
year = {{2024}},
}
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