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Workshop Submission : Geospatial analysis using python 101

Contributors :

  1. Krishna Lodha

Short Description

This tutorial is an introduction to Geospatial Domain and it's analysis using python. Since almost all industries are more or less connected to Location and mapping, it is important to spread awareness and literate developers to understand different aspects of the GIS (Geographic Information System) industry. This series focuses on geospatial analysis with python. Users will first practice working with some core GIS functionalities using GDAL and OGR on the terminal (and later in python). After this, users will be familiarised with most widely used geospatial python libraries such as pandas, geopandas, fiona, shapely, matplotlib, PySAL, rasterio .

Complete Series is divided into following subtopics :

  1. Introduction and Installation of all Geospatial libraries in computer and in python environment
  2. Working with GDAL and OGR capabilities
  3. Spatial Operations and Relationships
  4. Vector data analysis and visualisation
  5. Raster Data analysis and visualisation
  6. Working with Interactive Map in python notebook

Long Description

This tutorial will be helpful to every python developer looking forward to work in a niche field, applications and business logics are getting complex everyday and with huge chunks of data flowing in everyday, geospatial analysis using python will allow developers to automate things pretty easily using spatial techniques This series will be a brief introduction to the domain as well as advancement of domain in python. Users will learn various libraries such as pandas, geopandas, fiona, shapely, matplotlib, PySAL, rasterio.

Prerequisite for this workshop:

  1. Basic knowledge of python
  2. Basic knowledge of GIS and GIS Data formats

The series will cover following topics, each of them can either be re-created on Jupyter notebook or in a python file as well, the data used in the workshop will be freely available to download and use.

1. Setting up the Environment

Attendees will need to download some installable softwares beforehand, links to which will be provided priorly along with how-to-do video. Apart from this, attendees can create an env using the environment.yml file provided in the repository.

2. Working with GDAL and OGR capabilities

Here, we start coding, but still not in python ! We'll spend some time getting comfortable with using command-line / terminal to perform some basic GIS operations. This section will be a huge time saver for developers in the future where they want to perform some quick actions on data, such as , converting data to different formats, changing Coordinate Systems, Getting information about data, etc.

3. Spatial Operation and Relations

Real application of GIS is to enable users to perform queries or establish relations between different data sets based on location information. In this section, we'll have overview about different geospatial operations like :

  1. Buffer, Overlaps
  2. Contains, Within, Touches
  3. Point in Polygon, Intersection, Crosses Once attendees understand the logic behind these operations in theory, we'll jump in the python

4. Vector data analysis and visualisation

Vector data is like normal data (JSON, CSV, XML, etc) coupled with location information. In this series attendees will see how spatial analysis operations can be performed on such data using various libraries like geopandas,shapely,pySAL, and many more. We can see the data not only in just tabular format but also in picture by visualising this vector data on map. This topic will cover how to visualize the data with advanced options as well.

5. Raster data analysis and visualisation

This is a very important skill to have as mostly raster files are huge in size. To perform some basic operations such as getting pixel values, fetching metadata, conversion of files libraries like GDAL,Rasterio,Georaster are used .

6. Interactive map visualisation in python

Attendees will be able to create Interactive maps with additional data, ability to pan, etc. inside the notebook directly, this skill comes in handy when you want to test your geospatial results directly in python.

In the above outline, both theoretical and hands-on exercises will be covered to make attendees aware of the domain and make them familiarize with the existing libraries for GIS in python. Attendees will get complete gitHub repo of all notebooks, slides and data used during training.

Setup

Softwares, Libraries, Data used throughout the tutorial are available for all major operating systems. Attendees can use :

  • Linux (Ubuntu x64)
  • Windows 10 (x64)
  • Mac OS X (x64)

Softwares to be used :

Libraries to be used :

  • geopandas
  • pySal
  • rasterio
  • georasters
  • matplotlib
  • shapely
  • fiona