Abstract

In this study, we set up the framework of vector spatial data conflation in multi-source vector space and discuss the flow of the special conflation of attribute data and geometry data. The constraints in map conflation are first derived and the coordinates displacements of the conflated objects are then obtained by topological correlation computation. The results of the map conflation test show that the proposed conflation model and algorithm are effective and has a high precision and better ability to maintain the characteristics of the conflated objects compared with the exist methods.

Keywords:

Adjusting, attributes transfer, geometric matching, multi-scale, vector data conflation,

References

Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.