The core issue of sustainable development refers to the coordinated development of economic-social-environmental issues. In the present study, by complying with the China Sustainable Development Indicator System (CSDIS) concept, a comprehensive index system was built; besides, Natural Breaks (Jenks) Classification Method, Exploratory Spatial Data Analysis and Geographic Detector Analysis were conducted to delve into the sustainability and coordinated degree at city level in China from 2007 to 2017. The achieved results are presented as follows. First, for spatial differentiation, the overall spatial distribution pattern was characterized by the high-value units in eastern China and the low-value units in western China from 2007 to 2017. To be specific, the high-value units were radiated along the Beijing-Guangdong Axis (Jing-Guang Axis) centered on the core of Beijing-Tianjin-Hebei Region, the middle-value units were distributed in strips along the coast, and the low-value units were vastly gathered in western China and gradually break via the Hu Huanyong line (Hu Line) in south China from 2007 to 2017. More specifically, based on the five subsystems, the pattern of each system was consistent with the whole, whereas the degree of concentration was different. Second, for spatial correlation, the significant High-High (HH) areas were primarily distributed in the core of Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta Regions. The significant Low-Low (LL) areas were continuously distributed in the southwest China and broke through the Hu Line from 2007 to 2017. There were insufficient number of significant High-Low (HL) and significant Low-High (LH) areas, whereas the spatial agglomeration of them was less obvious. Third, for internal coupling coordination, the spatial differentiation between the coupling degree and the coupling coordinated degree was significantly consistent in 2007 and 2017. The Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta Regions have demonstrated a high level of coordinated evolution, and the pattern of western mountainous areas exhibited a low degree of coordinated growth. Lastly, based on the combination of quantitative and qualitative, its factors were underpinned by robust economic strength, the vitality support of the information level and the basic support function of the topography, active guidance of national policies and path dependence and industrial transfer.

<p>Based on the index of tourism Baidu search volume and total tourism income of 667 research units at county scale in Yellow River Economic Belt, this paper uses spatial classification, exploratory analysis of spatial data, nuclear density estimation and other methods to compare and analyze the spatial pattern of county tourism economy in the Yellow River Economic Belt, and then uses the geographical detector model to analyze the influencing factors. The results are drawn as follows. Firstly, from the perspective of spatial distribution pattern, the imbalance of the overall tourism economy is obvious, and the spatial pattern shows a “one big, three small” four core agglomeration pattern. Secondly, from the perspective of spatial correlation pattern, significant HH and LL areas are dominant whether virtual economy or a real economy, and spatial agglomeration effect is obvious. Real economic significant HH areas mainly distribute in the tourism economic developed areas of Shaanxi and Shandong, while real economic significant LL areas are mainly concentrated in the middle and east of Inner Mongolia, the south of Shanxi, most of Qinghai and the north of Ningxia, and scattered in Henan, Gansu and other places. Compared with the entity level, the HH areas of the virtual economy are significantly expanded, mainly distributing in Shandong, Shaanxi and the eastern part of Inner Mongolia. The number of significant LL areas is significantly increased and the distribution range has changed, and the distribution scope of low-value cluster areas mainly distributes in most areas of Qinghai, south and north of Shanxi, and sporadically distributes in Gansu. From the perspective of nuclear density, the spatial structure of virtual and real economy is similar, and the high-value counties mainly distribute in Shandong, Henan and Shanxi forming a high-value gathering area expanding into a core development area. It is worth noting that the virtual economy scope in the north of Shaanxi and the northeast of Inner Mongolia has formed many sub-cores, which indicates that the level of virtual economy in the region is rapidly rising. Finally, according to the results of the Geo-detector model and the coupling matching analysis model, we found the real economy is mainly affected by the resources support level. We also found virtual economy is mainly affected by the level of information technology.</p>