基于四叉树的不同尺度综合信息元动态划分方法与实现

A Quadtree Based Method for Dynamic Partitioning Integrated Information Units with Different Scales and its Implementation

综合信息元是地理信息系统空间数据采集、存储、管理和进行空间模型分析的基本单元。针对不同研究目的,综合信息元具有相对稳定的大小;不同空间尺度的综合信息元中的起主导作用的因子会有所变化,因此根据不同尺度动态划分信息单元是数据高效集成和模型计算的关键。本文探讨了在ARC/INFO环境下,基于四叉树的不同尺度下综合信息元的动态划分方法及其程序实现,同时和其它单元划分方法进行了对比。结果表明,由于其动态性和自动性,这种方法能够有效地进行不同尺度地理信息的集成管理,并可应用于分布式模型计算时进行网格划分。

Integrated Information Unit ( ⅡU) is the basic unit used in Geographical Information System (GIS) to collect, store, manage and model analysis spatial data. Varying with the study objectives and given scales, ⅡUs have relative stable sizes, uniformed attributes and legible boundaries. Different scales are frequently encountered in model analysis with GIS that brings about complicated and tedious scale transformation. Multiple source data integration often entails fusing data of different scales. Therefore a data representation method for different scale both in spatial and attribute is needed. The concept of ⅡU provides a good base for developing such a method. The dominating attributes within an ⅡU changes with the scale considered. Therefore dynamically partitioning ⅡUs is crucial for data integration with high efficiency and model calculation. A quadtree based method for dynamic partitioning ⅡUs with different scales was propounded in this paper and compared to the other popular methods. The method was also implemented under ARC/INFO environment. And the results revealed that the propounded method can be used to effectively integrate spatial data with different scales and paved a base for distributed model calculation.