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作 者:王浩宇 吴昊 孔博 WANG Haoyu;WU Hao;KONG Bo(School of Resources and Environmental Sciences,Wuhan University,Wuhan,Hubei 430079,China)
机构地区:[1]武汉大学资源与环境科学学院,湖北武汉430079
出 处:《北京测绘》2025年第3期270-274,共5页Beijing Surveying and Mapping
基 金:国家自然科学基金(42071450)。
摘 要:地理实体建模是当前新型测绘的重要任务之一,其中实体间关系信息的构建是一个关键环节。为了高效存储关系信息并实施关系推理,本文将图数据库引入,以图数据库(Neo4J)为例构建实体间的多阶领域关系表达,探索图结构在多维空间关系分析中的应用。相比依赖关系数据库的传统方法,图数据库在实体联系表达上更直接。本文将地理实体抽象为图节点,通过约束德洛内(Delaunay)三角网构建建筑物邻接关系,基于邻域关系的传递建立了K阶邻域关系表达。以火灾风险分析为例探讨了K阶邻域关系的推理应用,从距离和方位双参量分析揭示了火灾在不同着火点的扩散趋势,同时考虑风向对火灾传播的影响。研究表明,图结构不仅能处理空间距离,还能结合建筑物布局与环境因素,为火灾风险评估提供更全面的策略。Geographic entity modeling is one of the important tasks in current new surveying and mapping,and the construction of inter-entity relationship information is a key link.In order to efficiently store relationship information and implement relationship inference,this paper introduced graph databases and constructed a multi-order neighborhood relationship expression between entities using a graph database(Neo4J)as an example and explored the application of graph structures in multidimensional spatial relationship analysis.Compared to traditional methods of dependency databases,graph databases are more direct in expressing entity relationships.This paper abstracted geographic entities as graph nodes,constructed building adjacency relationships by constraining Delaunay triangulation,and established K-order neighborhood relationship expressions based on neighborhood relationship propagation.Based on fire risk analysis,this paper explored the inference application of K-order neighborhood relationships,revealing the diffusion trend of fires at different ignition points through distance and orientation parameter analysis while considering the influence of wind direction on fire propagation.Research has shown that graph structures can not only handle spatial distance but also provide a more comprehensive strategy for fire risk assessment by combining building layout and environmental factors.
分 类 号:P208[天文地球—地图制图学与地理信息工程]
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