基于多源数据的自然保护地规划报告编制方法及系统
By constructing a knowledge graph of nature reserves based on multi-source data and Monte Carlo simulation, the uncertainty of implicit ecological relationships and environmental changes is quantified, and a conservation value expectation map and confidence interval map are generated. This solves the problem of lack of risk foresight in planning schemes in existing technologies and realizes robust nature reserve planning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING QINGYUAN ECOLOGICAL ENVIRONMENT CO LTD
- Filing Date
- 2025-12-02
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for planning nature reserves cannot effectively quantify the uncertainties of implicit ecological relationships and external environmental changes, resulting in a lack of risk foresight and decision-making robustness in planning schemes.
By constructing a knowledge graph of nature reserves based on multi-source data, using a graph neural network model to infer the confidence scores of implicit ecological relationships, and combining Monte Carlo simulation sampling, a conservation value expectation map and a confidence interval map are generated. The optimal planning scheme is then selected based on a multi-objective optimization algorithm.
It has enabled the quantification of the spatial distribution uncertainty of ecosystem service value, generated nature reserve planning reports with strong risk early warning capabilities, and supported decision-making under long-term uncertainty.
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Figure CN121598905B_ABST
Abstract
Citation Information
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