Research And Application For GIS Model Of Industrial Upgrading

Being the inherent requirement of international competition and rapid development of economics, industrial upgrading has been concerned in political and economic fields. However, there is not an effective method to measure the upgrade industries. It lies on three respects: first, it is difficult to find a proper method to measure the industrial upgrading which is dynamic and spiral development; second, it is not easy to determine the related variables, most of which are not constant; third, industrial upgrading which is in its beginning stage gains a little attention. According to the above analysis, in this paper we construct the industrial upgrading model associated with the knowledge of my major.In this paper, to begin with, we analyze the related factors and seek the information of upgrade industries. Then, by the technique of principle component analysis, we reduce the dimension of information so that we can get a comprehensive variable weighing the upgrade industries which is called the industrial rank location value. Being obtained by analyzing the known data, future industrial rank location value is achieved after forecasting the future related information and analyzing it. In this study, we predict the variable value of associated factors by constructing the objective predictive functions. Afterwards, we construct the GIS Model of Upgrade Industries based on the second developing of ArcGIS with VBA and realize the visualization of upgrade industries by applying the statistical analysis and thematic mapping function. Finally, applying this model, we analyze the situation of upgrade industries in Henan Province.The purpose of this study is to realize the upgrading industrial rank location and visualization of its information. The upgrading industrial rank location value can simply illustrate the relative condition of the region studied, helping related departments to rapidly know the situation. The visualization of its information helps policy makers know the situation in a macro and lay the informational foundation for formulating the next scheme.