Ruumiandmeid

Ruumiandmeid, commonly translated as spatial data, refers to information that describes the location, shape, attributes, and relationships of real-world features in space. It is used to model geographic phenomena and to support analysis, visualization, and decision making. Spatial data can represent features as points, lines, and polygons (vector data) or as continuous surfaces (raster data).

Data sources and collection: official mapping agencies, remote sensing satellites, airborne surveys, field measurements, and crowdsourced observations. Metadata and quality frameworks ensure traceability and reliability. Common standards include ISO 19115 for metadata and Open Geospatial Consortium (OGC) standards such as Web Map Service (WMS) and Web Feature Service (WFS). Formats: Shapefile, GeoJSON, GeoTIFF, GML, KML, and GeoPackage.

Applications: urban planning, transportation and logistics, environmental monitoring, public health, disaster response, and market analysis. Spatial analysis methods include buffering, overlay, spatial joins, and interpolation.

Considerations: data quality (accuracy, precision, completeness), temporal validity, and uncertainty. Privacy and ethics are important when data include individuals or sensitive locations. Licensing and access rights affect data sharing; interoperability relies on common schemas and coordinate reference systems.