<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>

No abstract