Assessing city-scale green roof development potential using Unmanned Aerial Vehicle (UAV) imagery
- Authors
- Shao, Huamei; Song, Peihao; Mu, Bo; Tian, Guohang; Chen, Qian; He, Ruizhen; Kim, Gunwoo
- Issue Date
- Jan-2021
- Publisher
- ELSEVIER GMBH
- Keywords
- China; City-scale; Green roof; Green spaces; Roof spatial resources; Unmanned Aerial Vehicle (UAV)
- Citation
- URBAN FORESTRY & URBAN GREENING, v.57, pp.1 - 10
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- URBAN FORESTRY & URBAN GREENING
- Volume
- 57
- Start Page
- 1
- End Page
- 10
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/142553
- DOI
- 10.1016/j.ufug.2020.126954
- ISSN
- 1618-8667
- Abstract
- While green roofs have been deemed promising in mitigating environmental issues caused by rapid urban development, city-scale green roof studies have faced various obstacles, especially difficulties in obtaining accurate data for analysis. This study developed a new, cost-effective approach to assessing green roof development potential by using ultra-high-resolution (UHR) (0.09 m) Unmanned Aerial Vehicle (UAV) imagery in a case study site (Central Luohe with an area of 158 km(2)) in China. Specifically, the data was processed, interpreted, and classified to create highly accurate land-use and building roof spatial resources databases. A decision-making flowchart was developed for preliminary determination of a building stock's suitability for green roof implementation and the preferred type based on the five influencing factors and building roof classification. Subsequently, a two-stage strategy for large-scale green roof development was proposed. The approach demonstrated in this research greatly improves the accuracy of city-scale studies on roof spatial resources and enables better planning and development of urban green spaces at the local level.
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