Sequential Spatio-Temporal Pattern Mining with Time Lag

Geographic Information Systems have a wide variety of applications and there are many datasets available which contain spatial and temporal information. These datasets can be mined and analyzed to enable knowledge discovery which help domain experts discover unknown and interesting spatial and temporal insights in the data. Different spatial datasets are mined for spatio-temporal patterns that are used to investigate and establish spatial and temporal relationships between the datasets. Machine learning techniques are used to make predictions using historical data based on the spatio-temporal patterns.