Abstract:

Abstract Maps certainly plays a great way nowadays to represent spatial data. Growth of human population leads to changes in Business, environment and Society. Spatial and temporal data plays a main role to analyse and visualize current trends.  Encoding is a process of keeping a given sequence of characters and converting it into a specialized and secured  string format called Unicode to identify a given spatial temporal location. Different encoding techniques are used to convert data into Unicode format. This paper presents different encoding techniques performance measure with time and space complexity. It shows the results analysis of Base 32, Base 64, Elias gamma, Elias delta and Golomb codes with spatial temporal data. A comparative analysis has done among all codes and identified contingency analysis of encoding techniques. Base 64 is the the suitable and best encoding algorithm with respect to time and space on spatial and temporal data of a given point location in a trajectory data set.

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