This paper uses 2007—2016 panel data of Pingdingshan city to establish a performance evaluation index system of Pingdingshan's ecological transformation from residents' perception, ecological status, ecological governance and ecological improvement, and uses entropy to determine the weights of indexes, and applies structural function to score the performance in ecological transformation. During 2007 to 2016, Pingdingshan's ecological transformation has produced a good consequence marked by an increasing environmental governance, an improving ecological environment, rising residents' satisfaction, but remaining a room for improvement. A better ecological transformation performance is mainly contributed by decreasing unit GDP energy consumption, fog and SO₂ emission from ecological status. Governmental administration and policies are vital factors in ecological governance. Key factors in ecological improvement include expansion of natural reserves and added urban green area per capita.

Dual-core city cluster is a special geographic feature during China's city cluster development. This paper uses synergy theory and growth polarity theory to establish a dual-core city cluster compound system, applies compound system synergy model and 2011-2017 panel data to measure the order of central city sub-system, order of port city sub-system and synergy of compound system of eastern China's four dual-core city clusters, providing references for theory and practice of such city cluster coordinated development. Results show their synergy displays a rising trend, entering an excellent coordinated developing stage, marked by high-low-low high. Orders of central city sub-system and coastal city sub-system are rising at same pace. Central city sub-system has experienced disorder to a rising order synergy, varying in the south and north that northern central city generally prevails the south during 2011 to 2017. Orders of port city sub-system do not show a conspicuous high-low-low-high trend, below the central city sub-system.

This paper, according to China's fast marine economy growth and innovation and combined with marine economy innovation theories in the world, establishes an evaluation index system of marine economy innovation development from innovation environment, input, output and performance, and scores the 11 provinces/cities in their marine economy innovation development during 2010 to 2016 through centralizing the logarithmic primary data, covariance-improved eigenvalues extraction, and entropy-weighting principal component. System clustering is used to classify its hierarchy and to calculate the whole Moran's I index. Spatial correlation of Moran scatter points suggests China's marine economy innovation development is geographically of large difference between the north and the south, and balanced in the central, with each province/city slowly rising and a shrinking regional variance.