Research on multi-source geographic data matching method considering time characteristics

Tianjia Zhang

doi:10.1117/12.3020955

23 January 2024 Research on multi-source geographic data matching method considering time characteristics

Tianjia Zhang

Proceedings Volume 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023); 129782R (2024) https://doi.org/10.1117/12.3020955
Event: 2023 4th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2023), 2023, wuhan, China

Abstract

At present, feature matching and ontology matching are often used in the matching and fusion of multi-source geographic data, but the temporal characteristics of multi-source geographic data are less considered in feature matching. Therefore, according to the spatial, temporal and semantic correlation of multi-source geographic data, this paper proposes a multi feature semantic correlation calculation model of multi-source geographic data. Firstly, six kinds of similarity are extracted: spatial similarity, temporal similarity, literal similarity, speech similarity, word bag similarity and category similarity. Secondly, the six kinds of similarity are combined by multi-layer perceptron. Finally, the accurate matching judgment of multi-source geographic data is realized based on weighted multi feature fusion matching algorithm. The results show that the model realizes the accurate matching of multi-source geographic data on the basis of considering the time characteristics.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tianjia Zhang "Research on multi-source geographic data matching method considering time characteristics", Proc. SPIE 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023), 129782R (23 January 2024); https://doi.org/10.1117/12.3020955

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