An Accuracy Evaluation Method for Multi-source Data Based on Hexagonal Global Discrete Grids

As a new form of data management, the global discrete grid can describe and exchange geographic information in a standardized way on a global scale, which can be used for efficient storage and application of large-scale global spatial data, and it is a digital multi-resolution geo-reference model, which helps to establish a new data model and is expected to make up for the deficiencies of the existing spatial data in the aspects of organization, processing and application. The representation of vector data based on hexagonal isoproduct projection of global discrete grids fundamentally solves the problems of data redundancy, geometric deformation, and data discontinuity that occur when multi-vector data are represented in grids. In this paper, different gridded methods are proposed for different types of vector data and remote sensing data to achieve efficient gridded processing of multi-source data. For the gridded vector data, a quantifiable accuracy evaluation index system is established to evaluate the accuracy of the gridded vector data in terms of geographic deviation, geometrical features and topological relationships, and for the gridded remote sensing data, a Kyoto evaluation index system is constructed based on the levels of information, image structure, and texture features, which further proves the usability of the hexagonal gridded vector-based and remotely sensed data. The evaluation method is generally applicable to all gridded vector and remote sensing data based on hexagonal grids and can be used to evaluate the usability of hexagonal grid data.