NEW!: You can optionally read these materials from a new website. Go to https://automating-gis-processes.github.io/2016/.

• Mondays 9-12, A113-A114, Physicum (31.10 - 12.12)
• Work sessions on Thursdays 8-10, A111-112, Physicum (03.11 - 15.12)

• Henrikki Tenkanen
  • Office: A120, Physicum
  • Email: [email protected]
  • Phone: +358 50 4484436

• Vuokko Heikinheimo
  • Office: A120, Physicum
  • Email: [email protected]
  • Phone: +358 2941 50760

• Course sites for Period I (Introduction to Python programming):

  • Main course site: https://github.com/Python-for-geo-people
  • Pouta Blueprints site: https://pb.geo.helsinki.fi

• Automating GIS processes (Period II)

  • Moodle page: https://moodle.helsinki.fi/course/view.php?id=18331

• There are no required textbooks for this course. This course uses a wide range of sources for course information and the main textbooks are given below.
• Recommended textbooks (in order of relevance):
  • Zelle, J. (2010) Python Programming: An Introduction to Computer Science, Second edition. Franklin, Beedle & Associates.
  • Lawhead, J. (2015) Learning Geospatial Analysis with Python: An effective guide to geographic information systems and remote sensing analysis using Python 3, Second edition. Packt Publishing.
  • McKinney, W. (2012) Python for Data Analysis: Data wrangling with Pandas, NumPy and iPython, First edition. O´Reilly Media.
• Optional textbooks:
  • Westra, E. (2016) Python Geospatial Development: Develop sophisticated mapping applications from scratch using Python 3 tools for geospatial development, Third edition. Packt Publishing.
  • Zandbergen, P. (2013) Python Scripting for ArcGIS, Alternate edition. ESRI press. (Available from the library)
  • Diener, M. (2015) Python Geospatial Analysis Cookbook: Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python. Packt Publishing.

The majority of this course will be spent in front of a computer learning to program in the Python language and working on exercises. During Teaching Period I, the Automating GIS processes and Introduction to Quantitative Geology courses will meet together and focus on learning to program in Python. Previously, both these courses lacked sufficient time for students to properly learn the basic concepts of programming in Python.

The computer exercises will focus on developing basic programming skills using the Python language and applying those skills to various GIS related problems. Typical exercises will involve a brief introduction followed by topical computer-based tasks. At the end of the exercises, you may be asked to submit answers to relevant questions, some related plots, and/or Python codes you have written or used. You are encouraged to discuss and work together with other students on the laboratory exercises, however the laboratory summary write-ups that you submit must be completed individually and must clearly reflect your own work.

Lesson content, readings and due dates are subject to change

Period I

See: https://github.com/Python-for-geo-people/Course-information

Period II

links to lectures and exercises will be updated before each session

31.10 - GIS in Python; Spatial Data Model, Geometric Objects, Shapely

• Lesson - Lesson 1: Introduction to Python GIS
• Assignment - Exercise 1: Working with Geometric Objects
• Readings - Lawhead, Chapter 4: Shapely & Shapely documentation

7.11 - Working with (Geo)DataFrames

• Lesson - Lesson 2: Working with Geo-DataFrames in Pandas and Geopandas
• Assignment - Exercise 2: Creating Geometries in Geopandas
• Readings - Lawhead, Chapter 4 & GeoPandas documentation

14.11 - Geometric operations and geocoding

• Lesson - Lesson 3: Geocoding & Spatial Queries
• Assignment - Exercise 3: Geocoding and Spatial Join
• Readings -

21.11 - Spatial queries

• Lesson - Lesson 4: Classification and Overlay Analysis
• Assignment - Exercise 4
• Readings -

28.11 - Visualization: static and interactive maps

• Lesson - Lesson 5: Visualization

• Assignment - Exercise 5: Visualization

• Introduction to the final assignment will be sent via email!

5.12 - NO LECTURE ON MONDAY!

• Demo on thurdsay 8.12: Using ArcGIS trough Python
• Readings -

12.12 - Raster data processing in Python

• Lesson - Lesson 7: Basics of raster data processing with Python and Gdal
• Assignment - Exercise 7: Delineating forest areas from canopy cover data
• Readings - Lawhead pp. 158-161, Chapter 6 & Chapter 8

6.1.2017 - Deadline for the final assignment