Pattern change and dynamic evolution of urban green space based on multi-temporal remote sensing images: a case study of Xuzhou City

摘要

Taking Xuzhou city as an example, the urban green space categories system are established using multi-temporal/-source remotely sensed images. After classification adopted decision tree and object-oriented methods, the urban green space pattern changes are captured and evolution rules are analyzed based on the landscape pattern indices on the patch/class and landscape metrics. In addition, the economic/social statistics are listed for quantitative analyzing dynamic evolution. Finally, the all driving factors impacting urban green space pattern are analyzed using the principal component analysis.