PostGIS and SQL for Geospatial Processing

PostGIS is an extension to the PostgreSQL database that enables advanced geospatial processing by adding support for geographic objects. PostGIS extends the standard SQL language with powerful spatial functions, allowing users to perform complex geographic queries and analysis directly within the database.

This note explores how SQL is extended in PostGIS for geospatial processing and introduces the advanced functions and operations available.

Here’s the revised version of the PostGIS and SQL for Geospatial Processing introduction with the precision added:

What is PostGIS?

PostGIS is a spatial extension for PostgreSQL, making it a fully-featured spatial database that supports geographic objects such as points, lines, polygons, and raster data. It follows OGC (Open Geospatial Consortium) Simple Features standards, meaning it works seamlessly with other geospatial tools and formats.

PostGIS adds support for:

Spatial data types: Geometries (2D/3D) and Geography (curved-earth) types.
Spatial indexes: Efficient searching of spatial data using GiST and SP-GiST indexes.
Spatial functions: Over 500 functions for spatial operations, including distance calculations, intersections, buffering, and more.

Extending SQL into the Spatial Domain

PostGIS extends standard SQL into the spatial domain by adding spatial functions that operate on the spatial relationships between the rows (or tuples) of tables. These functions allow you to perform complex spatial queries based on the geographic objects stored in the database.

For instance, in traditional SQL, you might filter rows based on attributes (e.g., Population > 100000). In spatial SQL, you can filter rows based on spatial relationships, such as finding whether a point is within a polygon or if two geometries intersect.

Spatial functions like:

ST_Intersects: to check if geometries overlap,
ST_DWithin: to find geometries within a specified distance of another,
ST_Buffer: to create buffer zones around geometries,

allow users to directly query geographic data and analyze spatial interactions, making PostGIS an essential tool for geospatial processing within a relational database system.

Spatial SQL in PostGIS

PostGIS extends SQL with spatial data types and functions, allowing users to manipulate and query geographic objects directly in SQL. Here are the key concepts and functions for geospatial processing in PostGIS.

Spatial Data Types

PostGIS introduces two key spatial data types:

Geometry: This type is used for flat-Earth (2D Cartesian) projections, such as UTM (Universal Transverse Mercator).
Geography: This type is used for round-Earth (latitude/longitude) calculations, ideal for working with global coordinates.

For example, when creating a table with a spatial column, you can specify the geometry type:

CREATE TABLE Towns (
  TownID SERIAL PRIMARY KEY,
  TownName VARCHAR(255),
  Population INT,
  geom GEOMETRY(Point, 4326) -- EPSG:4326 for WGS84 (lat/lon)
);

In this example, geom is a spatial column of type GEOMETRY for storing point data in the EPSG:4326 coordinate system (WGS84).

Spatial Functions

PostGIS provides an extensive set of functions that allow users to perform spatial operations. Some of the most commonly used functions include:

ST_Intersects: Returns true if two geometries share any portion of space.

SELECT *
FROM Towns
WHERE ST_Intersects(Towns.geom, ST_GeomFromText('POLYGON((...))'));

ST_Distance: Computes the shortest distance between two geometries.

SELECT ST_Distance(geom, ST_GeomFromText('POINT(12.5683 55.6761)', 4326))
FROM Towns
WHERE TownName = 'Copenhagen';

ST_Buffer: Creates a buffer around a geometry, often used in proximity analysis.
```
SELECT ST_Buffer(geom, 1000)
FROM Towns
WHERE TownName = 'Copenhagen';
```

ST_Within: Returns true if one geometry is entirely within another.

SELECT TownName
FROM Towns
WHERE ST_Within(geom, ST_GeomFromText('POLYGON((...))'));

ST_Union: Merges two or more geometries into a single geometry.

Spatial Indexing

To make queries faster, PostGIS uses spatial indexing through GiST (Generalized Search Tree) or SP-GiST indexes. Creating a spatial index on a geometry column improves the performance of spatial queries like ST_Intersects or ST_Within:

CREATE INDEX idx_towns_geom
ON Towns
USING GIST (geom);

This index allows PostGIS to quickly search for spatial relationships, dramatically improving query performance for large datasets.

Example: Finding Nearby Towns

Let’s say you want to find all towns within 50 kilometers of Aarhus. You can use ST_DWithin, which checks whether geometries are within a specified distance:

SELECT TownName
FROM Towns
WHERE ST_DWithin(geom, ST_GeomFromText('POINT(10.2039 56.1629)', 4326), 50000);

This query finds towns within 50 kilometers of the point representing Aarhus.

Result:

TownName
Aarhus
Odense

Example: Buffering and Intersection

You can combine spatial functions to perform more complex queries. For instance, you can find all towns that intersect a buffer zone around a specific point:

SELECT TownName
FROM Towns
WHERE ST_Intersects(geom, ST_Buffer(ST_GeomFromText('POINT(12.5683 55.6761)', 4326), 5000));

This query selects towns that intersect a 5-kilometer buffer around a point near Copenhagen.

Example: Spatial Joins

PostGIS allows you to perform spatial joins, where you join two tables based on the spatial relationship between their geometries. For example, if you have a table of LandUsePlans and want to find which towns intersect specific land-use plans:

SELECT Towns.TownName, LandUsePlans.PlanType
FROM Towns
JOIN LandUsePlans ON ST_Intersects(Towns.geom, LandUsePlans.geom);

This query returns the town names and the land-use plans that spatially intersect each other.

Result:

TownName	PlanType
Copenhagen	Residential
Aarhus	Commercial

Advanced Spatial Functions

PostGIS supports a wide range of advanced spatial functions that extend beyond simple queries. Here are a few:

ST_Transform: Transforms the geometry into a different coordinate system.

SELECT ST_Transform(geom, 3857)
FROM Towns
WHERE TownName = 'Aarhus';

ST_ConvexHull: Returns the convex hull of a geometry (the smallest polygon that can enclose the geometry).
```
SELECT ST_ConvexHull(ST_Collect(geom))
FROM Towns;
```

ST_Rasterize: Converts vector geometries into raster format for analysis.

SELECT ST_AsRaster(geom, 10, 10)
FROM Towns
WHERE TownName = 'Odense';

PostGIS and OGC Simple Features

PostGIS is compliant with the OGC Simple Features specification, which defines how geospatial data should be handled. This ensures that PostGIS can interoperate with other OGC-compliant systems, such as desktop GIS applications (e.g., QGIS) and spatial data formats (e.g., GeoJSON, WKT, and Shapefiles).

Linking to Other Notes

For a broader understanding of how spatial SQL integrates with various geospatial workflows, refer to the following notes:

[Spatial SQL in QGIS and GeoPackage]: Discusses how spatial SQL can be used in QGIS with GeoPackage databases.
[Working with QGIS for Spatial Analysis]: Explores how to leverage QGIS for spatial analysis using both native tools and SQL-based workflows.

This note provides an overview of how PostGIS extends SQL for geospatial processing, with practical examples and advanced functions. Let me know if you need further additions or clarifications!

🪴 GIS garden

Explorer

PostGIS