Polygon-based main road selection method of urban road network

Abstract

The invention provides a polygon-based main road selection method of an urban road network. The polygon-based main road selection method comprises the following steps: firstly, taking OSM map data as a data source and processing to generate area elements; forming a four-dimensional vector by utilizing four shape descriptors including compactness, width, complexity and circularity, and describing polygons in road network data of the generated area element; marking particle polygons and extracting; classifying the obtained four-dimensional vectors by utilizing a non-linear SVM (Support Vector Machine) classification method, and extracting the corresponding polygons after classification; and combining the extracted particle polygons with the polygons obtained by SVM classification to form seed polygons. The invention provides the shape descriptors capable of relatively effectively describing the polygons of a main road, and the polygons with different shape characteristics of the main rod are processed respectively; and finally, based on topological characteristics among the polygons of the road network, the seed polygons extracted by a support vector machine are further processed to obtain the final main road polygons.

Description

technical field [0001] The invention relates to a method for selecting a main road of an urban road network based on polygons, which combines artificial intelligence, automatic synthesis of road network mapping, and selection of urban main roads, and belongs to the field of geographic information science. Background technique [0002] The automatic cartographic generalization of spatial data in digital environment is one of the core problems of modern cartography research. It is often a time-consuming and labor-intensive process to use large-scale digital map data to produce small-scale maps and to express multi-scale spatial data in geographic information systems. How to use automatic cartographic generalization methods to realize automatic conversion of data under different scales is the subject of extensive research today. In road network selection, the more common methods are link-based and road mesh-based. But these methods perform unsatisfactorily in the case of low ...

AI Technical Summary

Problems solved by technology

However, the current polygon-based method also has some shortcomings: some polygon shape descriptors are less feasible in practical applications; the processing of different main road polygons is not processed separately, which brings difficulties to the noise reduction of seed polygons; The method of denoising the seed polygon is more cumbersome

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