Understanding the changes in spatial fairness of urban greenery using time-series remote sensing images: A case study of Guangdong-Hong Kong-Macao Greater Bay.

Yang, Guang; Zhao, Yaolong; Xing, Hanfa; Fu, Yingchun; Liu, Guilin; Kang, Xinyi; Mai, Xin

Yang, Guang; Zhao, Yaolong; Xing, Hanfa; Fu, Yingchun; Liu, Guilin; Kang, Xinyi; Mai, Xin.

Afiliación

Yang G; School of Geography, South China Normal University, Guangzhou 510631, China.
Zhao Y; School of Geography, South China Normal University, Guangzhou 510631, China. Electronic address: zhaoyaolong@m.scnu.edu.cn.
Xing H; School of Geography, South China Normal University, Guangzhou 510631, China; College of Geography and Environment, Shandong Normal University, Jinan 250300, China.
Fu Y; School of Geography, South China Normal University, Guangzhou 510631, China.
Liu G; School of Geography, South China Normal University, Guangzhou 510631, China.
Kang X; School of Geography, South China Normal University, Guangzhou 510631, China.
Mai X; School of Geography, South China Normal University, Guangzhou 510631, China.

Sci Total Environ ; 715: 136763, 2020 May 01.

Article en En | MEDLINE | ID: mdl-32007872

Asunto(s)

Bahías; Tecnología de Sensores Remotos; Ciudades; Hong Kong; Macao

Palabras clave

Gini coefficient; Human activities; Living environment; Remote sensing images; Spatial fairness; Urban greenery

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Bahías / Tecnología de Sensores Remotos País/Región como asunto: Asia Idioma: En Revista: Sci Total Environ Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google