How Green Are the Streets Within the Sixth Ring Road of Beijing? An Analysis Based on Tencent Street View Pictures and the Green View Index.

Rencai Dong,Yonglin Zhang,Jingzhu Zhao

doi:10.3390/ijerph15071367

Abstract

Street greenery, an important urban landscape component, is closely related to people’s physical and mental health. This study employs the green view index (GVI) as a quantitative indicator to evaluate visual greenery from a pedestrian’s perspective and uses an image segmentation method to calculate the quantity of visual greenery from Tencent street view pictures. This article aims to quantify street greenery in the area within the sixth ring road in Beijing, analyse the relations between road parameters and the GVI, and compare the visual greenery of different road types. The authors find that (1) the average GVI value in the study area is low, with low-value clusters inside the third ring road and high-value clusters outside; (2) wider minor roads tend to have higher GVI values than motorways, major roads and provincial roads; and (3) longer roads, except expressways, tend to have higher GVI values. This case study demonstrates that the GVI can effectively represent the quantity of visual greenery along roads. The authors’ methods can be employed to compare street-level visual greenery among different areas or road types and to support urban green space planning and management.

Highlights

Urban greenery can improve neighbourhood and landscape aesthetics and enhance human psychological well-being [1,2]
The results show that the green view index (GVI) values calculated by the current method are consistent with both the artificial extraction and the segmentation method (SegNet) semantic segmentation
The quantity of urban street greenery in the current study area has room for improvement according to our GVI results and the 0.25 standard

Summary

Introduction

Urban greenery can improve neighbourhood and landscape aesthetics and enhance human psychological well-being [1,2]. To measure the quantity of urban greenery perceived by people, Aoki first advanced the concept of the green view [10], which was defined as the proportion of green vegetation in a pedestrian’s field of view. High-resolution remote sensing images and oblique photographs were widely used in past studies of urban greenery to estimate the spatial distribution of green vegetation on the ground [17,18]. Recent studies have demonstrated that pictures of real scenes can act as alternative data sources [19] and that image processing algorithms can be adopted to objectively identify and extract green vegetation polygons from the pictures to estimate the quantity of perceived greenery [20]

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Discussion

Conclusion