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Proceedings Paper

Cell-based representation and analysis of social-economic data in grid-city construction
Author(s): Xiangnan Liu; Fang Huang; Ping Wang
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Paper Abstract

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.

Paper Details

Date Published: 3 August 2007
PDF: 10 pages
Proc. SPIE 6751, Geoinformatics 2007: Cartographic Theory and Models, 675105 (3 August 2007); doi: 10.1117/12.759477
Show Author Affiliations
Xiangnan Liu, China Univ. of Geosciences (China)
Fang Huang, Northeast Normal Univ. (China)
Ping Wang, Northeast Normal Univ. (China)

Published in SPIE Proceedings Vol. 6751:
Geoinformatics 2007: Cartographic Theory and Models
Manchun Li; Jiechen Wang, Editor(s)

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