大数据环境下地理空间拓扑判定与分析策略的研究

Research on Geospatial Topology Decision and Analysis Strategies in Big Data Environment

本文首先阐述了大数据环境下作为信息载体的数据表现出来的特点,随后详细分析了在大数据环境下地理空间拓扑分析相对于传统的地理空间拓扑分析的不同之处.为了给地理空间大数据分析与应用提供一些有益的借鉴和参考,文章结合多个大数据拓扑分析实例分别就大数据拓扑分析中最常见的点与点、点与线、点与面3种情况,探讨了如何设定拓扑判定规则和分析策略,如设置阈值做近似模糊处理、抽象简化空间对象改变拓扑分析的对象、依据行业规则或流程过滤脏数据、减少计算量以提高分析处理的时效性.

The paper first describes the characteristics of data as an information carrier in the big data environment.Then the differences between the geospatial topological analysis in big data environment and the traditional topological analysis are discussed in detail.Finally,this paper combines several big data topology analysis examples to discuss how to set topology decision rules and analysis strategies in three common cases of big data topology analysis.It includes some methods such as setting threshold value to do approximate processing,abstracting and simplifying spatial objects to change objects of topological analysis,filtering dirty data with business rules and processes,and reducing calculation workload to improve the timeliness of analysis and processing.It attempts to provide some useful references for big data analysis and application based on geospatial data.