The vector data model is best for modeling discrete objects which have clearly defined boundaries and can be counted
Examples of vector features:
Vector data come in three spatial forms: point, line and polygon. Each vector feature can have multiple attributes
This example contains a single line made from 4 vertices
This example contains a single polygon made from 9 vertices
If you’ve followed the instructions to import your own dataset from a text file, you’ve created vector data - points, which can be connected into lines and or polygons. You can also add other field observations as attribute information
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