Abstract: In this paper, we design and implement a vector data contour adsorption algorithm considering shape of node association edges and similarity of proximity links to address the inconsistency between current mapping-intensive production and future holographic mapping data construction framework data and production data. The adsorption rationality generalization and efficiency stability of the algorithm are verified by random frame node displacement perturbation experiments and data partitioning incremental experiments. The algorithm effectively avoids repeated spatial query operations by establishing a point and line coordinate sorting index dictionary and many other methods, designe fast same-first-tail link extraction based on bi-directional link table and link direction approximation principle, get rid of fixed distance threshold limitation by link similarity function, established fields of nodes and links move, a fully automated vector data contour adsorption algorithm with symbiosis of node morphological adsorption and similar link adsorption is developed finally which contains high application value and application prospects.

Key words: vector data contour adsorption, vector topology, automation of mapping production, intelligent mapping