A sea area performance evaluation method and system based on geospatial analysis technology

CN122198328BActive Publication Date: 2026-10-16SOUTH CHINA SEA PLANNING & ENVIRONMENT RES INST SOA
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Patent Information

Application Number
CN202610253265.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-03-03
Publication Date
2026-10-16
Estimated Expiration
2046-03-03

AI Technical Summary

Technical Problem

[0003]本发明提出一种基于地理空间分析技术的海域效能评估方法,用于解决现有技术忽略了各评估单元之间空间相互作用与关联性,难以识别关键区域及潜在问题,从而影响了评估结果的科学性和决策支持的有效性的问题,包括:

Benefits of technology

本发明通过深度融合空间异质性与空间自相关性,提升了海域效能评估的科学性与精确度。利用空间基尼系数与局部信息熵,对灰色关联分析中的分辨系数进行初次修正,使所述系数能够反映指标在空间分布上的不均衡性及各评估单元自身的信息复杂度。通过构建非对称处理函数,对评估单元偏离邻域均值的负向偏差予以放大,增强了模型对风险短板的识别能力。利用局部莫兰指数识别空间聚类模式,并据此对分辨系数进行二次修正,使评估结果能够充分体现空间集聚效应对单元效能的影响。得到的效能评估结果表示了效能的空间格局与相互作用,为海洋空间管理提供了更为可靠的决策根据。

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Abstract

The application provides a sea area efficiency evaluation method and system based on geospatial analysis technology, which comprises the following steps: acquiring multi-source evaluation indexes of each unit, calculating first-order statistical moments, calculating spatial Gini coefficients and local information entropy of each index domain, correcting a preset resolution coefficient by using the local information entropy when the Gini coefficient exceeds a threshold, calculating deviation sequences of each unit index value and neighborhood first-order statistical moments, setting an asymmetric processing function according to the local information entropy, amplifying the absolute value of a negative deviation by using an exponential function, and compressing the value of a positive deviation by using a logarithmic function, wherein the local information entropy is positively correlated with the base number of the function, calculating an initial efficiency value based on the processed deviation sequences and the corrected resolution coefficient by using a comprehensive grey correlation degree, calculating a local Moran index based on the initial efficiency value to determine a spatial clustering type, correcting the resolution coefficient twice according to the spatial clustering type, recalculating the comprehensive grey correlation degree, and obtaining a sea area efficiency evaluation result.
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