A spatialization method for production value of economic sector in Changsha, China

One of the most challenging tasks is analyzing the laws of economic development from the space perspective. To lay the foundation for the task, it needs the relatively accurate production value distribution in the space. For this destination, the method of Classification and Regression Tree (CART) is used to quantify the contribution rates that impact factors to the total output value, and then kernel density estimation (KDE) is employed to evaluate the spatial density based on the contribution rates and the counts of economic sectors in the space. According to the spatial density, the output value is assigned to the space grids. This article takes the total production value of the sector of post, communication, and transportation for instance, the results show the sequence from high to low that contribution rates of impact factors to the total output value is railway > road > communication > water transport > air transport > postal service; the final distribution of production value after the ratio correction displays the extremely imbalance pattern of the output value of this sector in Changsha.