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.