A method and apparatus for storing ecological vulnerability data

CN122547792APending Publication Date: 2026-08-11JILIN NORMAL UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-13
Publication Date
2026-08-11

AI Technical Summary

Technical Problem

[0003]现有技术中，生态脆弱性数据的存储存在诸多缺陷：其一，位置数据普遍采用经纬度坐标形式存储，经纬度为字符串或浮点型多参数数据，在数据库检索、写入时需进行多字段匹配运算，导致数据读写与检索效率低下，无法适配大规模生态脆弱性数据的快速调用需求；其二，生态属性数据如土壤类型、植被覆盖度、气候条件等缺乏统一的封装结构，各类属性参数杂乱存储，易出现数据关联混乱、冗余存储的问题，增加了数据管理与解析的难度；其三，脆弱性特征数据与位置、属性数据的拼接无统一规则，数据耦合性差，且栅格数据作为生态脆弱性空间分布的重要载体，未进行针对性的格式优化与压缩处理，造成存储资源的大量浪费；其四，现有数据存储方案未对生态脆弱性多维度数据进行一体化整合设计，各类型数据独立存储，需通过额外字段建立关联，进一步降低了数据的访问与处理效率

Benefits of technology

[0048]本发明提供的生态脆弱性数据的储存方法及装置，本申请采用地理区块化和唯一数值标识替代传统经纬度坐标存储位置数据，将多参数浮点/字符串位置信息简化为单一连续非负整数编码，大幅降低数据库匹配与运算开销，位置检索速度、数据写入效率显著提升，可适配大规模生态脆弱性数据的快速调用需求。本发明采用父区块编码为前缀、子区块编码为后缀的顺序拼接方式生成唯一标识码，编码规则统一、层级清晰，支持按前缀快速范围检索与空间邻近查询，进一步提升基于位置的数据访问效率。本发明根据生态脆弱度等级与监测点密度加权融合动态确定划分次数，而非固定层级划分，实现高脆弱区、高密度区自动细粒度划分，稳定区、低密度区自动粗粒度划分，在保证关键生态区域评估精度的同时，减少非关键区域的区块数量与存储冗余，实现生态脆弱性数据的高效、规范存储与管理。

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Abstract

This invention provides a method and apparatus for storing ecological vulnerability data, relating to the field of ecological environment data processing and storage. The method includes: acquiring core storage items of ecological vulnerability data in a target geographic space; dividing the target geographic space into blocks to obtain several continuous and non-overlapping geographic blocks, assigning a unique numerical identifier to each geographic block; structurally encapsulating attribute data to obtain a chain structure of attribute data; standardizing the ecological vulnerability data to obtain standardized vulnerability feature data; pre-compressing the raster data to obtain pre-compressed raster data; and concatenating and integrating the unique numerical identifier, the chain structure of attribute data, the standardized vulnerability feature data, and the pre-compressed raster data according to preset rules, and then compressing the overall data after concatenation and integration. This application enables efficient and standardized storage and management of ecological vulnerability data.
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