Spatial classification is a particular type of classification that introduces space or geographical context into the statistical framework of a classification to assign an object to a class in a set of categories.

Although spatial classification can be done to some extent through traditional classification algorithms based on spatial feature engineering, its main task and focus is to provide unique classification algorithms considering spatial dependence or spatial heterogeneity.

The following describes a few use cases where you can apply spatial classification to predict emergency responses and help in the decision-making process:

• Analyzing and predicting the crime rate based on zones and related demographic data
• Analyzing and predicting the severity of air pollution based on industrialization status and population density across a geographic region

The following three spatial classification algorithms are supported:

• SLX Classifier
• GWR Classifier
• Geographical Classifier