Introduction

Beyond being a spatial database with the capacity to store and query spatial data, PostGIS is a very powerful analytical tool. What this means to the user is a tremendous capacity to expose and encapsulate deep spatial analyses right within a PostgreSQL database.

The recipes in this chapter can roughly be divided into four main sections:

• Highly optimized queries:
  • Improving proximity filtering with KNN
  • Improving proximity filtering with KNN – advanced
• Using the database to create and modify geometries:
  • Rotating geometries
  • Improving ST_Polygonize
  • Translating, scaling, and rotating geometries – advanced
  • Getting detailed building footprints from LiDAR
• Creating a fixed number of clusters from a set of points:
  • Using the PostGIS function, ST_ClusterKMeans, to create K clusters from a set of points
  • Using a minimum bounding circle to visually represent the clusters with the ST_ MinimumBoundingCircle function
• Calculating a Voronoi diagram:
  • Using the ST_VoronoiPolygon function in order to calculate...