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Geospatial Analysis with SQL

You're reading from   Geospatial Analysis with SQL A hands-on guide to performing geospatial analysis by unlocking the syntax of spatial SQL

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781835083147
Length 234 pages
Edition 1st Edition
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Author (1):
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Bonny P McClain Bonny P McClain
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Bonny P McClain
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Table of Contents (13) Chapters Close

Preface 1. Section 1: Getting Started with Geospatial Analytics
2. Chapter 1: Introducing the Fundamentals of Geospatial Analytics FREE CHAPTER 3. Chapter 2: Conceptual Framework for SQL Spatial Data Science – Geometry Versus Geography 4. Chapter 3: Analyzing and Understanding Spatial Algorithms 5. Chapter 4: An Overview of Spatial Statistics 6. Section 2: SQL for Spatial Analytics
7. Chapter 5: Using SQL Functions – Spatial and Non-Spatial 8. Chapter 6: Building SQL Queries Visually in a Graphical Query Builder 9. Chapter 7: Exploring PostGIS for Geographic Analysis 10. Chapter 8: Integrating SQL with QGIS 11. Index 12. Other Books You May Enjoy

Differentiating polygons in OSM data

A reminder of the syntax used in SQL query language helps to clear our minds as we generate complex questions within and between datasets:

  • SELECT name_attribute: What is the attribute you are selecting from your dataset?
  • FROM name_table: What table are you selecting this attribute from?
  • WHERE: What conditions need to be met?
  • GROUP BY name_attribute: Should they be sorted by name, area, or ID for example?
  • HAVING: Additional criteria to be met, often a threshold value.

Try to recognize this template in queries you observe or create. There should be a story embedded in each query.

Spatial queries

How does PostGIS extract information from a database? Recall that we are querying coordinates, reference systems, and other dimensions from a wide variety of datasets of different geometries that include the length of a line, the area of a polygon, or even a point location. These are collected based on specific properties...

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