Vector Data
Vector data represents geographic features as discrete points, lines, and polygons with associated attribute information. It is the primary data model for mapping and analyzing features with well-defined boundaries such as roads, buildings, and administrative areas.
Vector data is one of the two foundational data models in GISGISGeographic Information Systems (GIS) enable users to analyze and visualize spatial data to uncover patterns, relation..., representing geographic features as geometrically defined points, lines (polylines), and polygons. Each feature carries both spatial information describing its location and shape, and attribute information stored in a tabular format. This discrete representation makes vector data ideal for features with clear boundaries and distinct identities, from individual buildings and road centerlines to parcel boundaries and political jurisdictions.
Geometry Types
Vector data uses three fundamental geometry types to represent different kinds of features. Points represent discrete locations with no area or length, such as fire hydrants, GPSGPSThe Global Positioning System (GPS) is a satellite-based navigation system operated by the U.S. Space Force that prov... waypoints, or city center markers. Lines (polylines) represent linear features defined by ordered sequences of vertices, such as roads, rivers, pipelines, or power lines. Polygons represent enclosed areas defined by a closed ring of vertices, such as building footprints, lakes, census tracts, or national boundaries. Multi-part geometries allow a single feature to consist of multiple disconnected elements, such as a state with several islands represented as a single multi-polygon feature.
Applications
Vector data is the backbone of most cartographic and analytical GISGISGeographic Information Systems (GIS) enable users to analyze and visualize spatial data to uncover patterns, relation... workflows. Cadastral mappingCadastral MappingCadastral Mapping is the surveying and spatial recording of land parcel boundaries, ownership, and use rights. It pro... uses polygon features to represent land parcels with ownership attributes. Transportation planning relies on line features representing road networks with attributes for speed limits, lane counts, and surface conditions. Utility management maps infrastructure components as point and line features with detailed engineering attributes. Demographic analysisDemographic AnalysisDemographic analysis examines the statistical characteristics of populations—including age, income, education, househ... associates census attributes with polygon boundaries for thematic mapping and statistical analysis. Navigation systems use vector road networks for routing and turn-by-turn directions. Emergency services map incident locations as points and response zones as polygons.
Advantages
Vector data provides precise geometric representation of feature boundaries and locations without the resolution limitations of raster cells. It supports rich attribute information through linked database tables, enabling complex queries and classification. Vector files are typically more compact than raster equivalents for features with simple geometries. The data model supports topological relationships, enabling sophisticated spatial queries about adjacency, connectivity, and containment. Vector data scales cleanly across zoom levels without pixelation artifacts.
Challenges
Vector data is less suited for representing continuous phenomena like temperature gradients or elevation surfaces, which vary smoothly across space. Complex geometric operationsGeometric OperationsGeometric operations are spatial transformations applied to vector geometries, including union, intersection, differe... such as overlay and buffer analysisBuffer AnalysisBuffer analysis creates zones of specified distances around geographic features such as points, lines, or polygons. I... can be computationally intensive with intricate polygon boundaries. Data quality issues like gaps between polygons, overlapping features, and disconnected line segments require careful topologyTopologyTopology in GIS defines the spatial relationships between geographic features, including adjacency, connectivity, and... management. Digitization of features from imagery or paper maps can introduce positional errors.
Emerging Trends
Vector tileVector TileVector tiles package geographic vector data into a grid of small, efficiently encoded tiles that are transmitted to t... formats like MapboxMapboxMapbox is a robust platform that equips developers with tools to create highly customizable, interactive maps for web... Vector Tiles (MVT) are revolutionizing web mapping by streaming vector data to clients for dynamic styling and interaction. GeoParquet and FlatGeobuf are emerging as high-performance columnar formats for cloud-native vector data analysis. Real-time vector data from IoT devices and mobile sensors is enabling dynamic mapping applications. AI-powered feature extraction from imagery is automating the creation of vector datasets from raster sources.
Code-Beispiele
import geopandas as gpd
from shapely.geometry import Point
# Create vector data from coordinates
data = {
"city": ["Berlin", "Munich", "Hamburg"],
"lat": [52.52, 48.137, 53.551],
"lon": [13.405, 11.576, 9.994]
}
gdf = gpd.GeoDataFrame(
data,
geometry=[Point(xy) for xy in zip(
data["lon"], data["lat"]
)],
crs="EPSG:4326"
)
# Save as GeoPackage
gdf.to_file("cities.gpkg", driver="GPKG")Verwandte Mapular-Lösungen
Bereit?
Sehen Sie Mapular
in Aktion.
Buchen Sie eine kostenlose 30-minütige Demo. Wir zeigen Ihnen genau, wie die Plattform für Ihren Anwendungsfall funktioniert — kein generisches Foliendeck, keine Verpflichtung.