Chapter 8. Techniques to solve spatial problems

 

This chapter covers

  • Using joins with spatial functions
  • SQL aggregates and spatial aggregates
  • Proximity analysis
  • Common geometric processing

In prior chapters we looked at spatial functions separately and didn’t focus too much on how these functions could be combined to solve real-world problems. In this chapter we’ll combine several spatial and PostgreSQL functions and SQL join constructs to accomplish real-world objectives. No single chapter, let alone an entire book, can catalog all the different spatial challenges faced by the GIS analyst. Instead, we want you to focus on the techniques. The same technique can usually solve a whole range of problems.

We’ll tackle this chapter using prebuilt data combined with ad hoc generated data sets. If SQL is new to you, you may want to read appendix C, “SQL primer,” which discusses the fundamentals of SQL. The SQL primer demonstrates SQL constructs applicable to many relational databases.

8.1. Proximity analysis

8.2. Data tagging

8.3. Slicing and splicing linestrings

8.4. Slicing and splicing polygons

8.5. Translating, scaling, and rotating geometries

8.6. Summary