Introduction to SQL and Geospatial Data Processing: Reference

There are many different ways to explore the same dataset

Databases offer a highly structured framework for storing and rapidly manipulating data

Setting up this structure takes some time

Advantages include the ability to investigate complex relationships between data using a simple query language

dBeaver provides a simple interface for viewing database tables and testing SQL queries

SQL provides a simple yet powerful set of tools for performing anaylis on your data

All geospatial analysis requires a knowledge of reference frames and coordinate systems

Be sure to use the correct coordinate system to match your analysis, otherwise you can get unexpected results

many databases have extensions that encode geospatial information (e.g. PostGIS)

PostGIS functions provide a wide range of tools to incorporate spatial analysis into your workflow

GIS software provides a graphical user interface for running geospatial queries and making maps of the results

QGIS is a particularly good software for interfacing with PostGIS

All database functionality can be accessed through Python or R scripts

This is an important way to ensure reproducibility and transferability of our work