Spatial Visualization and Analysis of the Development of High-Paid Enterprises in the Yangtze River Delta

Big data technology is widely used in many fields. Facing a large amount of data management and analysis, traditional platforms have been unable to meet current demand. The large-capacity, multi-source heterogeneity, and real-time features of big data pose many challenges to data processing. Especially in the urban planning field where the development model is currently determined by flowing elements. In this chapter, we designed a solution for visual analysis of smart cities and big data management, and applied to the Yangtze River Delta region. First, through python programming, a web data crawler is designed to collect company registration information for 30 years in the Yangtze River Delta region from the websites. Secondly, in the management of big data, the collected data is stored in the MongoDB database, which realizes classification, storage and fast query of data, and solves the problem of storage and inefficiency of relational database. Finally, ArcGIS Engine is Embedded into C# to develop a visualization platform for geographic data. Through this platform, we can further analyze and mine data from the perspective of time and space, and then get the characteristics of the development of urban agglomeration companies. This chapter also applies the company’s development data to the construction of the subway as an example of the expansion of the research. This entire solution can also be extended and applied to research projects in other smart city groups.