Abstract: Taking 30 provinces and autonomous regions of mainland in China as an example, exploratory spatial data analysis (ESDA), local indicator of spatial association (LISA) time path and LISA space-time transitions were utilized to analyze the spatial-temporal dynamics character of cumulative target completion rate of carbon intensity under the frame of ESTDA during 2011-2015. Meanwhile, the spatial error model (SEM) and geographical weighted regression (GWR) were utilized to investigate the influencing factors of cumulative target completion rate of carbon intensity in China’s provinces. The results as follows: ① There was a significant spatial disparities and spatial autocorrelation of the cumulative target completion rate of carbon intensity in China’s provinces during 2011-2015. ② The eastern China had a relatively stable local spatial structure. In the spatial dependence direction, the strongest stability displayed in Beijing, the most volatility displayed in Xinjiang. ③ The integration of spatial pattern evolution for cumulative target completion rate of carbon intensity was relatively weaker, however, the stability was stronger. Collaborative high growth provinces were concentrated in the central and western China, collaborative low growth provinces were concentrated in the eastern regions. ④ The important factors influencing the cumulative target completion rate of carbon intensity included industrial structure, energy intensity, energy self-sufficiency and energy consumption structure.
Key words：cumulative target completion rate of carbon intensity; spatial-temporal dynamics; LISA time path; LISA spatial-time transitions; geographical weighted regression