Assessing city-scale green roof development potential using Unmanned Aerial Vehicle (UAV) imagery
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shao, Huamei | - |
dc.contributor.author | Song, Peihao | - |
dc.contributor.author | Mu, Bo | - |
dc.contributor.author | Tian, Guohang | - |
dc.contributor.author | Chen, Qian | - |
dc.contributor.author | He, Ruizhen | - |
dc.contributor.author | Kim, Gunwoo | - |
dc.date.accessioned | 2024-01-10T01:30:38Z | - |
dc.date.available | 2024-01-10T01:30:38Z | - |
dc.date.issued | 2021-01 | - |
dc.identifier.issn | 1618-8667 | - |
dc.identifier.issn | 1610-8167 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/193826 | - |
dc.description.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. | - |
dc.format.extent | 10 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | ELSEVIER GMBH | - |
dc.title | Assessing city-scale green roof development potential using Unmanned Aerial Vehicle (UAV) imagery | - |
dc.type | Article | - |
dc.publisher.location | 독일 | - |
dc.identifier.doi | 10.1016/j.ufug.2020.126954 | - |
dc.identifier.scopusid | 2-s2.0-85098470646 | - |
dc.identifier.wosid | 000619220800003 | - |
dc.identifier.bibliographicCitation | URBAN FORESTRY & URBAN GREENING, v.57, pp 1 - 10 | - |
dc.citation.title | URBAN FORESTRY & URBAN GREENING | - |
dc.citation.volume | 57 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 10 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Plant Sciences | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalResearchArea | Forestry | - |
dc.relation.journalResearchArea | Urban Studies | - |
dc.relation.journalWebOfScienceCategory | Plant Sciences | - |
dc.relation.journalWebOfScienceCategory | Environmental Studies | - |
dc.relation.journalWebOfScienceCategory | Forestry | - |
dc.relation.journalWebOfScienceCategory | Urban Studies | - |
dc.subject.keywordPlus | China | - |
dc.subject.keywordPlus | aerial survey | - |
dc.subject.keywordPlus | airborne sensing | - |
dc.subject.keywordPlus | cost-benefit analysis | - |
dc.subject.keywordPlus | decision making | - |
dc.subject.keywordPlus | remotely operated vehicle | - |
dc.subject.keywordPlus | roof | - |
dc.subject.keywordPlus | urban development | - |
dc.subject.keywordAuthor | China | - |
dc.subject.keywordAuthor | City-scale | - |
dc.subject.keywordAuthor | Green roof | - |
dc.subject.keywordAuthor | Green spaces | - |
dc.subject.keywordAuthor | Roof spatial resources | - |
dc.subject.keywordAuthor | Unmanned Aerial Vehicle (UAV) | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S1618866720307718?via%3Dihub | - |
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