Vector Data / Vector Data Model
A fundamental GIS data structure that represents geographic features as discrete points, lines (polylines), and polygons, each defined by coordinates and associated attributes. Vector data is ideal for mapping boundaries, networks, and discrete features.
How is Vector Data / Vector Data Model defined?
Points, lines, and polygons are used to represent real-world spatial elements in vector data, also known as the Vector Data Model in GIS. It is perfect for storing and analysing discrete characteristics like roads, rivers, buildings, and boundaries. It is one of the two main data models in GIS, the other being raster.
Single locations, like a tree or well, are represented by points.
Roads, rivers, and other linear characteristics are represented by lines.
Area elements, such as lakes and property parcels, are represented by polygons.
An attribute table containing descriptive data, like name, type, or measurements, is linked to each vector feature. The vector model is appropriate for network analysis, cadastral mapping, and other geographical investigations needing accuracy and detail because it provides high precision, effective storage, and support for topological relationships.
Related Keywords
Features are represented by points, lines, and polygons in GIS vector data. Shapefile (SHP), GeoJSON, KML/KMZ, GeoPackage (GPKG), and File Geodatabase (FGDB) are common formats with different storage, compatibility, and usage requirements.
The vector data model in GIS uses polygons, lines, and points to depict geographic elements. Polygons display areas (like lakes or land parcels), lines show linear features (like highways or rivers), and points show distinct locations (like wells). This model saves spatial coordinates and attribute data for analysis, is accurate, and is perfect for mapping networks and borders.
Among its many benefits, vector data is perfect for in-depth mapping and analysis since it offers great precision by representing features as points, lines, and polygons. It supports sophisticated spatial searches, makes it simple to store attribute information, and preserves data quality at any scale without sacrificing accuracy. Vector data is also effective for overlay operations, network analysis, and creating readable, eye-catching maps.
Vector data is perfect for accurate mapping of discrete features like roads, boundaries, or landmarks since it uses points, lines, and polygons to represent geographic characteristics in GIS. In contrast, raster data represents continuous phenomena like elevation, temperature, or satellite imagery using a grid of cells or pixels. Raster data is superior for examining patterns and spatial fluctuations throughout a region, but vector data is superior for precision and attribute detail.