《Quantitative Relationship between Urban Green Canopy Area and Urban Greening Land Area》

打印
作者
Jiening Wang;Peizhuo Yin;Duanjie Li;Guoqiang Zheng;Bojie Sun
来源
JOURNAL OF URBAN PLANNING AND DEVELOPMENT,Vol.147,Issue2
语言
英文
关键字
作者单位
Ph.D. Candidate, School of Landscape Architecture, Nanjing Forestry Univ., Nanjing 210037, China; Associate Professor, School of Architecture and Urban Planning, Shandong Jianzhu Univ., Jinan 250101, China (corresponding author). ORCID: https://orcid.org/0000-0002-1728-0358. Email: [email protected];Qingdao Jiedi Architectural Design Co., Ltd, Qingdao 401121, China. Email: [email protected];Senior Engineer, School of Architecture and Urban Planning, Shandong Jianzhu Univ., Jinan 250101, China. Email: [email protected];Associate Professor, School of Surveying and Geo-Informatics, Shandong Jianzhu Univ., Jinan 250101, China. Email: [email protected];Master Candidate, School of Architecture and Urban Planning, Shandong Jianzhu Univ., Jinan 250101, China. Email: [email protected]
摘要
The urban green space ratio (GSR) is the ratio of the urban greening land area to the built-up area and is an indicator for controlling land use for greening in urban development in China. However, the statistical process for the urban GSR by field manual survey or remote sensing imagery visual interpretation is a time-consuming and labor-intensive task. While estimating the urban green canopy ratio (GCR) by spatial information technology has been wildly accepted in the industry. This research investigates the influencing factors between the urban greening land area and the urban green canopy area for exploring the quantitative relationship between GSR and GCR. The results showed that the urban street tree greenbelt is a positive correlation factor, while pavement and water bodies in an urban park are the negative correlation factors. Then, a calculation model of the urban GSR was proposed that will reduce the workload of green space statistics and achieve a high efficiency and accuracy for urban GSR surveys. This model would be applicable in the spatial mapping fields and the spatial planning fields.