Quantitative evaluation of landscape architecture environmental benefits based on multi-criteria decision-making
Shuhua Wang
International Journal of Environmental Technology and Management, 2022, vol. 25, issue 1/2, 95-107
Abstract:
Aiming at the problems of large spatial accuracy error and long evaluation time in the quantitative evaluation of environmental benefits of landscape architecture, a new research method for quantitative evaluation of environmental benefits of landscape architecture is proposed. The grey relational analysis method is used to calculate the weights of environmental benefit evaluation indexes and establish an evaluation index system. The multi-dimensional decision-making method is applied to the construction of the environmental benefit decision matrix. After the index weights are clarified, the weighted decision matrix is established to calculate the distance of the standard solutions of different environmental benefit evaluation indexes to obtain the quantitative assessment results of environmental benefits. Comparative experiments show that the spatial accuracy error is no more than 4%, the change curve of the environmental benefit evaluation index is relatively close to the average change curve, and the benefit evaluation time is less than 2 s.
Keywords: multi-criteria decision making; landscape environment; benefit; quantitative evaluation. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=120728 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijetma:v:25:y:2022:i:1/2:p:95-107
Access Statistics for this article
More articles in International Journal of Environmental Technology and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().