Earth　Observation　(EO)　technology　plays　an　essential　role　in　monitoring　environmental　challenges　and　assessing　the　impact　of　human　activities.　As　the　field　of　Earth　observation　enters　the　era　of　big　data,　the　exponential　growth　in　data　volume　presents　new　challenges　for　data　management　and　storage.　To　enhance　the　efficiency　of　data　sharing　and　analysis,　effectively　subdividing　and　managing　these　vast　datasets　becomes　crucial.　This　study　proposes　an　innovative　tiling　method　for　three-dimensional　EO　data　cubes,　organizing　the　spatial　dimension　according　to　the　BeiDou　grid　and　subdividing　the　third　dimension　into　regular　or　irregular　segments　based　on　specific　requirements.　By　segmenting　the　data　into　manageable　chunks,　this　method　allows　users　to　select　appropriate　data　for　particular　application　scenarios,　reducing　data　redundancy　and　improving　processing　efficiency　through　smaller　data　volumes,　thereby　significantly　enhancing　the　accessibility　and　utility　of　the　data.　This　not　only　simplifies　the　process　of　utilizing　EO　data　but　also　greatly　facilitates　the　effective　application　of　Earth　observation　information.