Overview

In this lesson, we will continue to learn how to manipulate and analyse spatial data using Geopandas, Shapely and other relevant Python packages. First, we will learn how to geocode addresses, i.e. convert addresses into coodrinates. Next, we will focus on spatial queries and we will learn how to join data based on spatial information. Finally, we will conduct nearest neighbor analysis between a set of points.

Learning goals

After this weeks’ lesson you should be able to:

  • Geocode data, i.e. transform addresses into coordinates

  • Conduct point-in-polygon queries

  • Make spatial joins

  • Conduct nearest neighbour analysis (finding the closest point).

Sources

Lesson materials are partly based on documentation of Geopandas, geopy, Pandas, Shapely, and Lawhead, J. (2013), Chapters I and V.

Lesson videos

Lesson 3.1 - Geocoding

Håvard Wallin Aagesen, University of Helsinki @ AutoGIS channel on Youtube.

Lesson 3.2 - Spatial queries and spatial joins

Håvard Wallin Aagesen, University of Helsinki @ AutoGIS channel on Youtube.

Lesson 3.3 - Nearest neighbour analysis

Håvard Wallin Aagesen, University of Helsinki @ AutoGIS channel on Youtube.

Lesson 3.4 - Exercise 3

Håvard Wallin Aagesen, University of Helsinki @ AutoGIS channel on Youtube.