An Automated Method for Constructing Multi-Scale Dynamic Spatiotemporal Geographic Maps Based on Vector Data

CN122309626APending Publication Date: 2026-06-30MOGANSHAN DIXIN LABORATORY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
MOGANSHAN DIXIN LABORATORY
Filing Date
2026-05-12
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing technologies for constructing geographic knowledge graphs have low levels of automation, insufficient dynamic spatiotemporal analysis capabilities, distorted spatial relationship representations, and difficulty in supporting high-precision decision analysis.

Method used

An automated construction method for multi-scale dynamic spatiotemporal geographic maps based on vector data is adopted. Through spatial indexing and progressive calculation, a dual ID system of basic identifiers and time version identifiers, and the combination of large model cognition and deterministic calculation, end-to-end automated construction is achieved.

Benefits of technology

It achieves fully automated construction, improves construction efficiency, endows geographic maps with dynamic spatiotemporal analysis capabilities, provides real and quantifiable spatial relationships, and supports complex intelligent reasoning and high-precision decision-making.

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Abstract

This invention belongs to the field of geospatial intelligent analysis methods, specifically a method for automatically constructing multi-scale dynamic spatiotemporal geographic maps based on vector data. It includes the following steps: S1, data standardization and basic spatial relationship calculation; S2, spatiotemporal integrated geographic entity modeling and map updating; S3, road network-enhanced spatial relationship modeling, integration, and map updating; S4, automatic construction of multi-scale geographic hierarchical systems and map updating; S5, map output. The execution of steps S1 to S4 is driven by an intelligent agent module, which dynamically adjusts the execution order and parameters of each step. This invention achieves end-to-end automated construction of geographic knowledge maps with dynamic spatiotemporal reasoning capabilities from multi-source, multi-period vector data, supports full lifecycle tracking of geographic objects, upgrades traditional geometric relationships to real and quantifiable path semantic relationships, and realizes cross-level spatial cognition and reasoning functions.
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