基于十六叉树-多尺度表达R树的TGIS时空数据索引算法

SPATIOTEMPROAL DATA INDEXING ALGORITHM FOR TGIS BASED ON HEX TREE AND MULTI-SCALE REPRESENTED R-TREE

对于多尺度表达R树的TGIS中多维、多分辨率时空数据索引的不足问题,提出基于四维十六叉树-多尺度表达R树的时空数据索引算法,分别实现多维、多分辨率目标节点和时空位置访问关系与多尺度时空目标对象索引;构建4DHMSR树时空索引创建算法以及动态插入和分裂算法,分别实现4DHMSR树索引创建过程和目标节点的选择与插入时空R树中的过程,利用MongoDB数据库技术,设计4DHMSR树索引存储结构。以某矿山部分采场区域内不同比例尺的运输道路数据为例,验证了4DHMSR树、MSR树和Octree树的时间索引和空间索引性能。实验结果表明,该方法能有效检索多维、多分辨率表达的时空数据,且检索效率明显提高。

Aimed at the problem that multi-dimension and multi-resolution spatiotemporal data of TGIS have not enough index in multi-scale represented R-tree,a spatiotemporal index algorithm is proposed based on 4D Hex tree and multi-scale represented R-tree(4DHMSR-tree),in order to achieve multi-dimensional multi-resolution goals node,spatiotemporal location access relationship,and multi-scale spatiotemporal target object index respectively.Index created algorithm and dynamic inserted and splitting algorithms of 4DHMSR tree were constructed,to realize the 4DHMSR tree indexing process and the process of target node selecting and inserting into spatiotemporal R tree respectively.The 4DHMSR tree index storage structure was devised by using MongoDB database technology.Taking different scale transportation road data in a certain mining area of a mine as an example,the time indexing and spatial indexing performance of the 4DHMSR tree,MR tree and Octree tree were verified.The results show that the multi-dimensional and multi-resolution spatiotemporal data can be effectively retrieved by this method,and the retrieval efficiency is significantly improved.