Comprehensive indices and methods for estimating the quality of the depth generalization in chart cartography

Shuaidong Jia; Zhicheng Liang; Lihua Zhang; Zeyuan Dai; Hongcheng Wei

doi:10.1117/12.2627440

2 March 2022 Comprehensive indices and methods for estimating the quality of the depth generalization in chart cartography

Shuaidong Jia, Zhicheng Liang, Lihua Zhang, Zeyuan Dai, Hongcheng Wei

Author Affiliations +

Proceedings Volume 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021); 1215803 (2022) https://doi.org/10.1117/12.2627440
Event: 2021 International Conference on Computer Vision and Pattern Analysis, 2021, Guangzhou, China

Abstract

In view of the current situation that the method for estimating the quality of the depth generalization in chart cartography is simple and extensive, a series of the quality quantitative indices and evaluation methods are proposed for evaluating the quality of the depth generalization. On the basis of “Specification for Chinese Nautical Charts”, three kinds of the quality indices, including the probability of adequate depth, the representativeness of depth and the distribution of depth, are proposed and designed for respectively evaluating the ship’s navigational safety, the available navigation resource and the arrangement of charted depth. Correspondingly, the quantitative evaluation methods of the comprehensive quality of nautical chart are proposed. The experimental results demonstrate that: (1) compared with the traditional method, the proposed method can accurately analyze and evaluate the quality of each depth for ensuring the navigational safety; (2) compared with the accuracy assessment method, the proposed method can accurately calculate the depth for representing the navigable resource such as in the sea channel, narrow channel; (3) compared with the average spacing method, the proposed method can quantitatively evaluate the location distribution of each depth annotation expressed on the chart, and accurately determine whether the distribution of each depth point is clear and reasonable.

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Shuaidong Jia, Zhicheng Liang, Lihua Zhang, Zeyuan Dai, and Hongcheng Wei "Comprehensive indices and methods for estimating the quality of the depth generalization in chart cartography", Proc. SPIE 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021), 1215803 (2 March 2022); https://doi.org/10.1117/12.2627440

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KEYWORDS

Safety

Cartography

Lithium

Data modeling

Error analysis

Clouds

Data processing

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