There are many sources of geographic big data,and most of them come from heterogeneous environments.The data sources obtained in this case contain attribute information of different spatial scales,different time scale...There are many sources of geographic big data,and most of them come from heterogeneous environments.The data sources obtained in this case contain attribute information of different spatial scales,different time scales and different complexity levels.It is worth noting that the emergence of new high-dimensional trajectory data types and the increasing number of details are becoming more difficult.In this case,visualizing high-dimensional spatiotemporal trajectory data is extremely challenging.Therefore,i-tStar and its extension i-tStar(3D)proposed,a trajectory behavior feature formoving objects that are integrated into a view with less effort to display and extract spatiotemporal conditions,and evaluate our approach through case studies of an open-pit mine truck dataset.The experimental results show that this method is easier to mine the interaction behavior of multi-attribute trajectory data and the correlation and influence of various indicators of moving objects.展开更多
基金Beijing Key Laboratory of Urban Spatial Information Engineering,Grant No.20220105Ningxia Natural Science Foundation,No.2021AAC03060。
文摘There are many sources of geographic big data,and most of them come from heterogeneous environments.The data sources obtained in this case contain attribute information of different spatial scales,different time scales and different complexity levels.It is worth noting that the emergence of new high-dimensional trajectory data types and the increasing number of details are becoming more difficult.In this case,visualizing high-dimensional spatiotemporal trajectory data is extremely challenging.Therefore,i-tStar and its extension i-tStar(3D)proposed,a trajectory behavior feature formoving objects that are integrated into a view with less effort to display and extract spatiotemporal conditions,and evaluate our approach through case studies of an open-pit mine truck dataset.The experimental results show that this method is easier to mine the interaction behavior of multi-attribute trajectory data and the correlation and influence of various indicators of moving objects.