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

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 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
Volume57
DOIs
StatePublished - 2021 Jan

Keywords

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

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