Category: Time series and analysis
Time Series
A time series is a sequence of observations over time for the same location, used for monitoring and change detection.
Also known as: timeseries, temporal stack
Expanded definition
In Earth observation, time series typically means repeated images or measurements for the same area. The goal is to detect trends, seasonal patterns, or abrupt changes.
Good time series analysis depends on consistent preprocessing: stable radiometry, reliable masks, and clear handling of missing data. If preprocessing changes across time, you can get false trends.
Time series are used for phenology, crop monitoring, deforestation alerts, drought assessment, and infrastructure change. In many applications, regular delivery and consistent quality matter more than occasional perfect scenes.
Related terms
Temporal Resolution
Temporal resolution describes how often a location is observed, such as a 5-day revisit.
Cadence
Cadence is how often a processed product is delivered, which can differ from sensor revisit time.
Change Detection
Change detection identifies meaningful differences between dates, such as harvest, flooding, deforestation, or construction.
Gap Filling
Gap filling estimates missing values in time series caused by clouds, shadows, or data dropouts.
Harmonization
Harmonization reduces differences between scenes or sensors so values are more comparable across time.