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Research and Application of National Spatial Data Model Concerning Multiple Classification and Granularity Division(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2024年01期
Page:
53-62
Research Field:
测绘科学与技术
Publishing date:

Info

Title:
Research and Application of National Spatial Data Model Concerning Multiple Classification and Granularity Division
Author(s):
Zhou Haiyang1; Wang Yang1; Lan Xin2; Zhou Liangchen2; 3; 4
(1.Nanjing Land and Resources Information Center,Nanjing 210005,China)
(2.School of Geography,Nanjing Normal University,Nanjing 210023,China)
(3.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing Normal University,Nanjing 210023,China)
(4.Key Laboratory of Virtual Geographic Environment,Naning Normal University,Nanjing 210023,China)
Keywords:
National spatial data model; multiple classifications; multiple granularity divisions; directed hypergraph
PACS:
P208
DOI:
10.3969/j.issn.1672-1292.2024.01.008
Abstract:
The national spatial data exhibits complex relationships in terms of classification,hierarchical structure,and process evolution. These relationships involve high-order attributes such as classification,interdependence,composition,and temporal sequence. Existing data models like layers,object-oriented,and data cubes struggle to fully capture all these relationships. This paper introduces a national spatial data model based on directed hypergraphs,which takes into account multiple classifications and granularity divisions. A relational matrix is used for logical description,and a hypergraph database is employed for the physical model implementation and spatiotemporal analysis of national spatial evolution processes. This model effectively addresses the challenge of expressing multiple classifications and granularity divisions for nationwide,all-element,and entire space national spatial data. The proposed approach has been validated through application on the Nanjing City National Spatial Basic Information Platform. It enhances the platform's operational efficiency in handling complex relationships,enables aggregation of multidimensional relational data,and establishes the foundation for the platform to achieve automatic data categorization and intelligent targeted information dissemination.

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Last Update: 2024-03-15