Dong Dong , Mingxin Chen , Xin Wen , Qing Li , Tieqiao Xiao , Fengquan Ji
{"title":"城市近自然植物群落景观视觉质量的时空尺度评价:一种nomogram可视化方法","authors":"Dong Dong , Mingxin Chen , Xin Wen , Qing Li , Tieqiao Xiao , Fengquan Ji","doi":"10.1016/j.ecolind.2025.113683","DOIUrl":null,"url":null,"abstract":"<div><div>Quantifying factors influencing landscape visual quality (LVQ) in urban near-natural plant communities (NNPCs) is essential for promoting the mainstreaming of Nature-based Solutions (NbS) and revealing connections between human perception and natural environments. However, existing research often relies on complex formulations that hinder practical application of the models constructed. This study systematically evaluated the LVQ of plant communities across spatiotemporal scales by surveying 65 NNPCs in Hefei city, capturing landscape photographs covering four seasons from two viewpoints (interior and exterior landscapes), and employing the Scenic Beauty Estimation (SBE) method. The research identified 25 landscape characteristic indicators across four dimensions: structural, phenological, environmental, and morphological. Logistic regression was used for indicator analysis, while nomograms were employed to illustrate relationships between key factors and LVQ. Unlike other models, the nomogram visualization model intuitively displays the contribution weight of each indicator to LVQ, making complex statistical relationships easier to understand and apply. The study found that background clarity (OR <sub>interior “clear”</sub> = 5.53, OR <sub>exterior “clear”</sub> = 3.63), green view ratio (OR <sub>interior</sub> = 1.62, OR <sub>exterior</sub> = 2.23), and permeability (OR <sub>interior</sub> = 1.84, OR <sub>exterior</sub> = 1.70) had significant impacts across different seasons and spatial scales, while other factors exhibited obvious seasonal or spatial specificity. Some qualitative indicators showed higher influence levels when at “medium” states, indicating that maintaining reasonable indicator levels plays an important role in enhancing LVQ. The research results provide intuitive, quantifiable scientific evidence for urban designers and planners, helping to optimize plant configuration in urban green spaces and improve overall landscape quality. Meanwhile, this study has significant implications for promoting the application and evaluation of NNPC as NbS in human-dominated landscapes.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113683"},"PeriodicalIF":7.0000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatio-temporal scale evaluation of landscape visual quality in urban near-natural plant communities: A nomogram visualization approach\",\"authors\":\"Dong Dong , Mingxin Chen , Xin Wen , Qing Li , Tieqiao Xiao , Fengquan Ji\",\"doi\":\"10.1016/j.ecolind.2025.113683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Quantifying factors influencing landscape visual quality (LVQ) in urban near-natural plant communities (NNPCs) is essential for promoting the mainstreaming of Nature-based Solutions (NbS) and revealing connections between human perception and natural environments. However, existing research often relies on complex formulations that hinder practical application of the models constructed. This study systematically evaluated the LVQ of plant communities across spatiotemporal scales by surveying 65 NNPCs in Hefei city, capturing landscape photographs covering four seasons from two viewpoints (interior and exterior landscapes), and employing the Scenic Beauty Estimation (SBE) method. The research identified 25 landscape characteristic indicators across four dimensions: structural, phenological, environmental, and morphological. Logistic regression was used for indicator analysis, while nomograms were employed to illustrate relationships between key factors and LVQ. Unlike other models, the nomogram visualization model intuitively displays the contribution weight of each indicator to LVQ, making complex statistical relationships easier to understand and apply. The study found that background clarity (OR <sub>interior “clear”</sub> = 5.53, OR <sub>exterior “clear”</sub> = 3.63), green view ratio (OR <sub>interior</sub> = 1.62, OR <sub>exterior</sub> = 2.23), and permeability (OR <sub>interior</sub> = 1.84, OR <sub>exterior</sub> = 1.70) had significant impacts across different seasons and spatial scales, while other factors exhibited obvious seasonal or spatial specificity. Some qualitative indicators showed higher influence levels when at “medium” states, indicating that maintaining reasonable indicator levels plays an important role in enhancing LVQ. The research results provide intuitive, quantifiable scientific evidence for urban designers and planners, helping to optimize plant configuration in urban green spaces and improve overall landscape quality. Meanwhile, this study has significant implications for promoting the application and evaluation of NNPC as NbS in human-dominated landscapes.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"176 \",\"pages\":\"Article 113683\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2025-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1470160X25006132\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X25006132","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Spatio-temporal scale evaluation of landscape visual quality in urban near-natural plant communities: A nomogram visualization approach
Quantifying factors influencing landscape visual quality (LVQ) in urban near-natural plant communities (NNPCs) is essential for promoting the mainstreaming of Nature-based Solutions (NbS) and revealing connections between human perception and natural environments. However, existing research often relies on complex formulations that hinder practical application of the models constructed. This study systematically evaluated the LVQ of plant communities across spatiotemporal scales by surveying 65 NNPCs in Hefei city, capturing landscape photographs covering four seasons from two viewpoints (interior and exterior landscapes), and employing the Scenic Beauty Estimation (SBE) method. The research identified 25 landscape characteristic indicators across four dimensions: structural, phenological, environmental, and morphological. Logistic regression was used for indicator analysis, while nomograms were employed to illustrate relationships between key factors and LVQ. Unlike other models, the nomogram visualization model intuitively displays the contribution weight of each indicator to LVQ, making complex statistical relationships easier to understand and apply. The study found that background clarity (OR interior “clear” = 5.53, OR exterior “clear” = 3.63), green view ratio (OR interior = 1.62, OR exterior = 2.23), and permeability (OR interior = 1.84, OR exterior = 1.70) had significant impacts across different seasons and spatial scales, while other factors exhibited obvious seasonal or spatial specificity. Some qualitative indicators showed higher influence levels when at “medium” states, indicating that maintaining reasonable indicator levels plays an important role in enhancing LVQ. The research results provide intuitive, quantifiable scientific evidence for urban designers and planners, helping to optimize plant configuration in urban green spaces and improve overall landscape quality. Meanwhile, this study has significant implications for promoting the application and evaluation of NNPC as NbS in human-dominated landscapes.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.