PostGIS for dummies – How PostGIS works? 

PostGIS is an open-source extension for the PostgreSQL database management system that adds spatial functionality for working with geographic data. It allows you to store, index, and query spatial data in a PostgreSQL database, and perform spatial operations such as distance calculations, spatial joins, and geometry processing.

PostGIS stores spatial data in a special data type called geometry, which is a binary representation of a geometric shape. The geometry data type can represent points, lines, and polygons, as well as more complex shapes such as multi-points, multi-lines, and multi-polygons.

PostGIS also includes a set of spatial indexing functions that allow you to efficiently query and manipulate spatial data. These functions include spatial predicates, such as “contains” and “intersects”, and spatial operators, such as “distance” and “area”.

One of the main advantages of PostGIS is that it allows you to perform spatial operations in SQL, which makes it easy to integrate spatial functionality into your application. Additionally, it provides a rich set of spatial functions and operators, which allows you to perform advanced spatial analysis and data manipulation tasks.

PostGIS also supports several geographic data formats, including Well-Known Text (WKT) and Well-Known Binary (WKB) and the widely used shapefiles format.

It can be used in a variety of applications, including geographic information systems (GIS), location-based services, and spatial analytics. It is also popular in the field of GIScience, and is used in many spatial data infrastructures.

How PostGIS indexes works?

PostGIS uses spatial indexes to improve the performance of spatial queries. The most commonly used spatial index in PostGIS is the R-Tree index, which is based on the R-Tree data structure.

An R-Tree index organizes the spatial data into a hierarchical tree structure, where each node in the tree represents a rectangular bounding box that encloses a set of spatial objects. The tree is built so that the bounding boxes at the higher levels of the tree are larger and enclose the bounding boxes at the lower levels.

When a spatial query is executed, the R-Tree index is used to quickly narrow down the search to the relevant parts of the tree, rather than having to search the entire dataset. This greatly improves the performance of the query, especially for large datasets.

Additionally, PostGIS also supports other types of spatial indexes, including:

• GiST (Generalized Search Tree) index: This is a more general-purpose index that can be used for spatial data of any dimension.
• SP-GiST (Space-Partitioned Generalized Search Tree) index: This is similar to the GiST index, but it is more efficient for large datasets and allows for more advanced spatial queries.
• K-D Tree index: This is an index that organizes the data into a k-dimensional tree, where k is the number of dimensions in the data.

The choice of index type depends on the type of spatial data you have, the nature of your queries and the size of your dataset.

You can create indexes on columns of the geometry data type by using the `CREATE INDEX