Time Series Analysis – Geography – UGC NET – Notes

• Time series analysis in Geographic Information Systems (GIS) refers to the systematic examination of spatial data collected repeatedly over time in order to identify patterns, trends, cycles, and changes in geographic phenomena.
• Unlike traditional GIS analysis, which often focuses on spatial relationships at a single point in time, time series analysis integrates the temporal dimension as a core analytical component. This approach is essential for understanding dynamic Earth processes and human activities that evolve over days, seasons, years, or decades.

Concept

• A time series is a sequence of observations of the same variable taken at consistent or irregular time intervals. In a GIS context, each observation is spatially referenced, meaning that time series data are inherently spatiotemporal. Time series GIS analysis therefore operates at the intersection of three domains: space, time, and attributes.
• The fundamental objective is to analyze how geographic features or spatial patterns change over time while preserving their spatial context. This requires data models and analytical methods capable of handling both spatial autocorrelation (similarity across space) and temporal autocorrelation (similarity across time). GIS platforms provide the framework to store, visualize, and analyze such data, while statistical and computational methods are applied to extract meaningful temporal insights.