Road network data automatic quality inspection method based on high-resolution remote sensing image

Abstract

The invention discloses a road network data automatic quality inspection method based on a high-resolution remote sensing image, and the method automatically achieves the quantitative quality inspection of a road track, and assists the updating and optimization of road data. The method comprises the following steps: 1) according to road morphological characteristics, breaking at road characteristic points to generate a simple road section structure; 2) constructing a universal road cross section model according to the road section structure characteristics; and 3) acquiring image data block data corresponding to the road section structure. And 4) establishing an image block coordinate system, and carrying out template matching between the road cross section model and the image to obtain aroad matching point. And 5) after RANSAC least square curve fitting error calculation, obtaining an actual road extraction result in the image. 6) matching the actual road extraction result with the road section structure similarity, and 7) performing comprehensive evaluation in combination with the similarity matching result of the road section structure in each road to screen out a'problem road'for road data quality evaluation and further data modification and updating.

Description

technical field [0001] The invention relates to the technical field of high-resolution remote sensing images, in particular to an automatic quality inspection method for road network data based on high-resolution remote sensing images. Background technique [0002] Highway is the artery and booster of economic development. As an important part of transportation infrastructure, the road network is directly related to the accuracy and comprehensiveness of the data. etc. are of great significance and value. Due to the long cycle of road network data acquisition based on traditional measurement in the early stage, it often cannot reflect the latest real information of roads in time, resulting in inaccurate base numbers of some historical road network data, inestimable data quality, and inconsistencies between old and new data. To a certain extent, it affects the analysis, decision-making and data update of data users. [0003] Remote sensing images have the characteristics of ...

AI Technical Summary

Problems solved by technology

In the existing technical solutions, on the one hand, the implementation mode of the traditional remote sensing image road extraction method is difficult to apply to the quality inspection and update based on existing data; research, but it is more widely used in surface feature maps, and there are certain limitations in the detection of road linear trajectories

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