Welcome to the Geospatial Data Cookbook!
The first step to getting started with any geospatial application or analysis is finding suitable data. Open Source Data is a good option for this, as it is freely and easily available online, if one knows where to look for it. In this cookbook you will learn how to download open source spatial data from OSM, work with a provided GTFS transit feed for the same Vienna area, and then pre-process the OSM data as groundwork for applications like GeoAI or Geospatial Analysis.
Overview and Structure¶
Introduction and Fundamental Concepts: This chapter introduces the topic and explains the key theoretical concepts needed to understand it.
Data Acquisition: This notebook demonstrates how to download data from OpenStreetMap using the Overpass Turbo API.
Working with GTFS: After acquiring OSM data, this notebook introduces GTFS as another open geospatial source for the same bounding box: loading a provided Vienna feed, inspecting its structure, and mapping stops.
Feature Engineering: Engineer features in parallel from OSM (street intersections) and GTFS (stop-level attributes).
Grids and Segmentation: Divide the area into regular cells and aggregate both OSM and GTFS features on the same grids.
Visualisation: Interactive maps and statistical plots illustrated with both OSM and GTFS examples.
Prerequisites:¶
In order to be able to follow the contents of this cookbook properly, you should have at least a basic understanding of Python programming.