Your browser doesn't support javascript.
loading
Landscape and vegetation traits of urban green space can predict local surface temperature.
Chen, Daosheng; Zhang, Fei; Zhang, Mengru; Meng, Qingyan; Jim, Chi Yung; Shi, Jingchao; Tan, Mou Leong; Ma, Xu.
Afiliación
  • Chen D; Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China.
  • Zhang F; Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China. Electronic address: zhangfei3s@xju.edu.cn.
  • Zhang M; Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China.
  • Meng Q; Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Jim CY; Department of Social Sciences, Education University of Hong Kong, Lo Ping Road, Tai Po, Hong Kong, China.
  • Shi J; Departments of Earth Sciences, the University of Memphis, Memphis, TN 38152, USA.
  • Tan ML; GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang 11800, Malaysia.
  • Ma X; Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China.
Sci Total Environ ; 825: 154006, 2022 Jun 15.
Article en En | MEDLINE | ID: mdl-35192831
Asunto(s)
Palabras clave
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Parques Recreativos / Calor Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Total Environ Año: 2022 Tipo del documento: Article País de afiliación: China
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Parques Recreativos / Calor Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Total Environ Año: 2022 Tipo del documento: Article País de afiliación: China