网格化时空数据关联分析方法

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中图分类号：TP393.028 文献标志码：A DOI：10.3969/j. issn.1673-3819.2025.05.008

Abstract：With therapid development of informationperception methods，thevolumeof multi-source heterogeneous data has increasedexplosively.Traditional methodsexhibitobviouslimitations inhanding inconsistent spatio-temporal scalesandinformationredundancy.Inthis paper，the principles of spatiotemporal grid codinganditsapplicationareintroducedandan innovativeunfied spatiotemporal gridbaseddataassociationanalysis method is proposed toconduceresearchonspatio-temporalinformationextraction，nifiedencodingandidentificationofspatio-temporal giddata，crossscalespati-temporaldata sharingand dynamic corelation analysis.Our method constructs aspatio-temporal grid framework forunified alignmentof heterogeneous multi-soucedataspatialcordinates，temporalbaselinesynchronization，andatributecorelation withbehaviors.Inadition，aspatio-temporal gridframeworkisconstructedtoalignspatialcoordinatesofmulti-source heterogeneous data，synchronize temporalbaseline，andcorrelateatributebehaviors.Theresultof simulationof typicallow-altitudeairspaceplanning for Unmanned Aerial Vehicles verifies thatour proposed method is enable to efectivelyenhance the managementandutilizationefciencyinclasification，integration，andcorrlationanalysisofmulti-source heterogeneous data.

Key words： spatio-temporal grid; cross-scale data sharing；dynamic correlation association

随着信息感知手段与方式的快速发展，现有数据处理分析方法存在计算效率低、有效信息提取难等问题，难以满足数据有效管理运用等需求。（剩余6916字）