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An adaptive Voronoi diagrams Algorithm for matching multi-scale areal Residential Areas

Jianhua WuPeng DaiHU Lieyun

2021Environmental Science被引 1

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摘要

For the difficult problem of balanced control of the computational efficiency and boundary position accuracy of the existing Voronoi algorithms based on the idea of figure discretization, we proposed an adaptive Voronoi diagram algorithm for multi-scale areal residential area matching based on interpolation strategy according to neighbor pair type——AVARA. Firstly, it uses the Delaunay triangle network composed of the centroids of the residential areas to calculate the neighbor pairs of the residential areas. Secondly, it classifies neighbor pairs according to the size relationship between the minimum distance between the neighbor pairs and the minimum side length of their minimum area bounding rectangles. Then it adaptively interpolates points on the boundary of the residential area according to the neighbor pair type. Finally, it constructs the Voronoi diagram for residential areas based on the interpolated point set and the vertex set of the residential area. We conducted the experiments of creating Voronoi diagram by using the residential area dataset which map scale is 1:10,000 and 1:50,000. The results showed that:compared with the intervisibility point method, the 3m and 6m interval interpolation point method of 1:10,000 data, AVARA outperformed the local position accuracy and time performance, compared with the 30m interval interpolation point method of 1:50,000 data, AVARA achieved higher local position accuracy, and compared with the 15m interval interpolation point method of 1:50,000 data, AVARA time performance has been improved by 34.6%.The problem of balance control between computational efficiency and boundary position accuracy of Voronoi diagram was alleviated effectively.

引用本文(GB/T 7714)

Jianhua Wu, Peng Dai, HU Lieyun. An adaptive Voronoi diagrams Algorithm for matching multi-scale areal Residential Areas[J]. 未知来源, 2021.

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DOI:https://doi.org/10.13203/j.whugis20200324

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