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Cell-based representation and analysis of social-economic data in grid-city constructing

机译:基于细胞的网格城构建社会经济数据的代表与分析

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Grid-city management currently attracts a wider audience globally. Socio-economic data is an essential part of grid-city management system. Social-economic data of an urban is characterized by discrete, time-varying, statistical, distributed and complicated. Most of data are with no exactly spatial location or from various statistical units. There is obvious gap while matching social-economic data with existing grid map of natural geographical elements emerges. It may cause many difficulties in data input, organization, processing and analysis while the grid system constructing and executing. The issue of how to allocate and integrate the huge social-economic data into each grid effectively is crucial for grid-city construction. In this paper, we discussed the characteristics of social-economic data in a grid-city systematically, thereafter a cell-based model for social-economic data representing and analyzing is presented in this paper. The kernel issues of the cell-based model establishment include cell size determining, cell capabilities developing for multi-dimension representation and evaluation, and cell dynamic simulation functions designing. The cell-based model supplements the methods system of spatial data mining, and is also promising in application to the spatialization of statistical data obtained from other researches including environmental monitoring, hydrological and meteorological observation.
机译:网格城市管理目前在全球吸引更广泛的受众。社会经济数据是网格城市管理系统的重要组成部分。城市的社会经济数据以离散,时变,统计,分布式和复杂的特点为特征。大多数数据都没有恰好空间位置或来自各种统计单元。存在明显的差距,同时将社会经济数据与自然地理元素的现有网格图匹配出现。它可能在数据输入,组织,处理和分析中引起许多困难,而网格系统构造和执行。如何将巨大的社会经济数据分配和整合到每个网格中的巨大融合,这对网格城市建设至关重要。在本文中,我们系统地讨论了各种社会经济数据的特征,此后本文提出了一种基于细胞的社会经济数据模型。基于小区的模型建立的内核问题包括用于多维表示和评估的小区尺寸确定,小区能力,以及设计的小区动态仿真功能。基于细胞的模型补充了空间数据挖掘方法系统,并且在应用于从其他研究中获得的统计数据的空间化,包括环境监测,水文和气象观察。

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