西北林学院学报2024，Vol.39Issue(2)：156-165,10.DOI:10.3969/j.issn.1001-7461.2024.02.20
道路绿视率不同识别方法比较研究
A Comparative Study on Different Identification Methods for Road Green Wiew Index
摘要
Abstract
It is of great significance to explore the influence of different identification methods on green view index(GVI)to improve the accuracy rate of GVI and the formulation of GVI standard.Taking three types of characteristic sections in Xuzhou City as the research objects,three different recognition methods were used to extract road GVI in local mobile datasets.The influence of different methods on the recognition value and accuracy of road GVI was analyzed.The results showed that 1)the method based on RGB and HSL color underestimated the value of green apparent ratio.The SegNet method based on machine learning was superior to the RGB and HSL methods based on color extraction in recognition accuracy.2)The group of different sections and image brightness had no significant correlation with the difference of GVI and the difference of accuracy,while the color bias coefficient had a significantly positive correlation with the differ-ence of GVI.The results of this study provide methodological empirical reference and suggestion for the government GVI standard formulation and GVI monitoring.关键词
绿视率/街景图像/RGB-Ⅵ/HSL-Ⅵ/SegNetKey words
green view index/street image/RGB-Ⅵ/HSL-Ⅵ/SegNet分类
农业科技引用本文复制引用
陶贵鑫,周宏轩,王昭清,聂艳霞,周凤林..道路绿视率不同识别方法比较研究[J].西北林学院学报,2024,39(2):156-165,10.基金项目
国家自然科学基金项目(51908544) （51908544）
教育部人文社会科学研究(19YJC760169) （19YJC760169）
江苏省研究生实践与创新项目(KYCX21_2436) （KYCX21_2436）
中国矿业大学研究生创新计划(2021WLJCRCZL171). （2021WLJCRCZL171）
