SQL (Structured Query Language)
A standard language for querying and manipulating relational databases, including those with spatial extensions.
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What does SQL (Structured Query Language)L mean?
A standardized computer language called SQL (Structured Query Language) is used to manage, modify, and query data kept in relational databases. SQL is frequently used in GIS (Geographic Information Systems) to extract, sort, and filter both spatial and non-spatial data from spatial databases and attribute tables.
Selecting particular records from a dataset (such as cities with a population of one million or more) is one of SQL's primary GIS functions.
Connect tables using shared variables (e.g., connecting district boundaries to population data).
Modify geometry fields or characteristics.
Use spatial SQL extensions, such as PostGIS, to execute spatial queries.
Basic SQL Example:
SELECT * FROM parcels WHERE landuse = 'residential';
This command retrieves all parcels where the land use is residential.
Related Keywords
Spatial and attribute data stored in databases can be queried, filtered, and altered using SQL in GIS data analysis. It facilitates the extraction of significant insights from huge geographic datasets by enabling users to execute buffer analysis, data aggregation, and spatial joins.
GIS users can manage and analyse geographic data directly in databases by using spatial SQL queries. To carry out operations like determining intersections, determining distances, verifying containment, and executing spatial joins, they add spatial functions to normal SQL. This enables effective querying, filtering, and analysis of big geographic datasets for planning, decision-making, and mapping.
By adding support for geographic objects, PostGIS is a potent addition for PostgreSQL that enables spatial data to be stored, queried, and analysed directly in a database. By utilizing ordinary SQL statements, you may manage geometries, locate intersections, and calculate distances with PostGIS. For activities like mapping, geographical analysis, and location-based services, it is extensively utilized in GIS applications.
Locating junctions, calculating distances, and verifying geographical relationships directly in databases are just a few examples of the geographic data querying and analysis made possible by SQL spatial functions in GIS.