TY - JOUR
T1 - Assessing urban greenery by harvesting street view data
T2 - A review
AU - Lu, Yanzhi
AU - Ferranti, Emma
AU - Chapman, Lee
AU - Pfrang, Christian
PY - 2023/5
Y1 - 2023/5
N2 - Urban greenery is of great significance for sustainable urban development due to the diverse ecosystem services it provides. Assessing urban greenery can reveal its impact on urban areas and provide the evidence base for strategic urban forest management and planning, thereby contributing to sustainable urban development. Street View (SV) images are being used more frequently and widely for assessing urban greenery due to the advantages of providing new perspective and saving workload and research costs. In this paper, 135 peer-reviewed publications that employed SV to assess urban greenery between 2010 and 2022 are reviewed. Presently, the most widely applied area of SV-based urban greenery research is to extract the green view index. Although this has many potential applications for assessing ecosystem services, it has most often been used to date to identify the impact of street greenery on residents' physical and mental health, activities, and well-being (i.e., cultural services). In contrast, fewer studies have explored the other ecosystem services related to the greening. Overall, as an emerging urban environment research method, this review shows that there are still challenges in the utilisation of SV images for assessing urban greenery applications. These include the insufficient spatial and temporal coverage of SV images, low data collection accuracy and immaturity of suitable deep learning techniques on object identification. However, there is clear potential for these approaches to be developed to support a broader range of urban greenery studies that consider different ecosystem services and/or specific types of green infrastructure, for example, street trees.
AB - Urban greenery is of great significance for sustainable urban development due to the diverse ecosystem services it provides. Assessing urban greenery can reveal its impact on urban areas and provide the evidence base for strategic urban forest management and planning, thereby contributing to sustainable urban development. Street View (SV) images are being used more frequently and widely for assessing urban greenery due to the advantages of providing new perspective and saving workload and research costs. In this paper, 135 peer-reviewed publications that employed SV to assess urban greenery between 2010 and 2022 are reviewed. Presently, the most widely applied area of SV-based urban greenery research is to extract the green view index. Although this has many potential applications for assessing ecosystem services, it has most often been used to date to identify the impact of street greenery on residents' physical and mental health, activities, and well-being (i.e., cultural services). In contrast, fewer studies have explored the other ecosystem services related to the greening. Overall, as an emerging urban environment research method, this review shows that there are still challenges in the utilisation of SV images for assessing urban greenery applications. These include the insufficient spatial and temporal coverage of SV images, low data collection accuracy and immaturity of suitable deep learning techniques on object identification. However, there is clear potential for these approaches to be developed to support a broader range of urban greenery studies that consider different ecosystem services and/or specific types of green infrastructure, for example, street trees.
KW - Street-level image
KW - Urban greening
KW - Street trees
KW - Ecosystem services
U2 - 10.1016/j.ufug.2023.127917
DO - 10.1016/j.ufug.2023.127917
M3 - Review article
SN - 1618-8667
VL - 83
JO - Urban Forestry & Urban Greening
JF - Urban Forestry & Urban Greening
M1 - 127917
ER -