Assessing city-scale green roof development potential using Unmanned Aerial Vehicle (UAV) imagery

Huamei Shao, Peihao Song, Bo Mu, Guohang Tian, Qian Chen, Ruizhen He, Gunwoo Kim

Research output: Contribution to journalArticlepeer-review


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 km2) 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.

Original languageEnglish
Article number126954
JournalUrban Forestry and Urban Greening
StatePublished - 2021 Jan


  • China
  • City-scale
  • Green roof
  • Green spaces
  • Roof spatial resources
  • Unmanned Aerial Vehicle (UAV)


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