Skip to content

A repo of teaching resources for Geographic / Spatial Data Science, GIS and Statistics

Notifications You must be signed in to change notification settings

GDSL-UL/Teaching_Links

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

58 Commits
 
 
 
 

Repository files navigation

The GDSL Big List of Teaching Links

Table of Contents

In this repo we have aimed to provide links to useful teaching resources for teaching Geographic / Spatial Data Science, GIS and Statistics.

With the spread of COVID-19 and the ongoing international response efforts, it is looking like a lot of the academic community will be delivering teaching remotely and online. This might be a problem for some. As such, we have decided to create a living document containing useful teaching resources. Some of these are from the lab, and others are from people who we have reached out to while compiling this.

We do not claim that any of the resources are fully fledged online courses, or that these are a comprehensive list of what is out there, but we think that these might be helpful to the community to list and share.

If you have anything that you think is useful then send us a tweet @geodatascience or issue a PR to this repository!

Urban Analytics

This provides 15 practicals in R with Slides - associated with (but independent from the book) https://github.com/alexsingleton/urban_analytics ; topics include R, SQL, Descriptive Statistics, Charts and Graphs, Mapping Areas, Mapping Points, Web Mapping, Mapping Flows, Geodemographics, Indices, Spatial Relationships, Regression, Agent Based Models and Network Analysis.

Geographic Data Science (Python)

DOI

Material and website for the course Geographic Data Science'19, taught at the University of Liverpool. The course was open to last year undergraduate and master students and uses Python.

GRANOLARR is a geogGRaphic dAta scieNce, reprOducibLe teAching resouRce in R

This repository contains reproducible materials to teach geographic information and data science in R.

Open Education Resources Hosted by Penn State’s College of EMS

OPEN.ED@PSU offers high-quality learning materials written by Penn State faculty. These materials are freely available for you to use, reuse, revise, remix, and redistribute under a creative commons license.

Geographic Information Systems and Science (CASA; CASA0005)

All the practical instructions and data for the CASA, UCL module - Geographic Information Systems and Science.

Spatial Analysis and Modelling

This is a nice module written by David O' Sullivan with the objectives of 1) Articulate the theoretical and practical considerations in the application of spatial analysis methods and spatial modelling; 2) Prepare, manipulate, analyse, and display spatial data; 3) Apply existing tools to derive meaningful spatial models; 4) Identify and perform appropriate spatial analysis

Geographic Data Science with PySAL and the PyData, the book (WIP)

This is an upcoming book being developed in the open to cover an introduction to Geographic Data Science using PySAL and the rest of the Python stack for data science.

Geo-Python

An introduction to programming in Python for geography and geology BSc/MSc students from the University of Helsinki. Introduced basic Python programming concepts (variables, data structures, loops, conditional statements, data analysis with Pandas, basic data visualization) assuming no prior coding experience. Also introduces use of git and GitHub.com, and has lecture videos available. Part of the forthcoming book Introduction to Python for Geographic Data Analysis.

Automating GIS processes

Teaches you how to do different GIS-related tasks in the Python programming language. Each lesson is a tutorial with specific topic(s) where the aim is to learn how to solve common GIS-related problems and tasks using Python tools. We are using only publicly available data which can be used and downloaded by anyone anywhere. We also provide a computing environment which allows you to instantly start programming and trying out the materials yourself, directly in your browser (no installations needed). Also part of the forthcoming book Introduction to Python for Geographic Data Analysis.

Geographical Analysis

A set of video lectures from a course on Geographical Analysis delivered by Dr. Steven Farber at the University of Utah

Geocomputation with R

This book is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization and geospatial capabilities. The book is open source and has been used as the basis of many courses.

Spatial Data Analysis in R

This is a book in progress used for the MSc-level course Spatial Analysis taught at the University of Liverpool, part of the MSc in Geographic Data Science programme.

Data, Evidence, and Communication for the Public Good

This course provides you with a toolkit for telling stories with urban data. It will introduce basic code, stats, and reasoning with evidence. The course takes a computational social science approach to working with data. It uses Python and Jupyter notebooks to introduce coding and statistical methods that students can reproduce and experiment with in real-time in the classroom. We start the semester with the basics of coding, then move on to data loading and analysis, then on to basic statistics, then hypotheses and the scientific method, and finally a critical assessment of smart cities and urban informatics.

Emerging Topics in GIScience: Geographical Computing

Recent years have seen the (re)emergence of programmatic approaches to geographical information science and the de-emphasis of established desktop 'GIS' packages, both in research settings and in the commercial world. This class introduces the Python programming language and the Python geospatial ecosystem to prepare students for conducting research in this new context.

An Introduction to Spatial Data Analysis and Visualisation in R

This tutorial series is designed to provide an accessible introduction to techniques for handling, analysing and visualising spatial data in R. 12 Practicals including basic descriptive statistics, making maps (or various sorts), Geographically Weighted Regression, point pattern analysis and some help with loops.

Spatial Data Science

A set of online lectures alongside tutorials on Geoda and Spatial R from the Centre for Spatial Data Science at the University of Chicago

Data Analysis & Visualization

A nice intro course in Python....

Applied Spatial Data Analysis with R

Opengeohub summer school 2019

Course materials, Jupyter notebooks, tutorials, guides, and demos for a Python-based urban data science course.

Short Course / Practical Labs

Creating a Geodemographic Classification Using K-means Clustering in R

This tutorial provides you with the basic skills to build your own geodemographic classification using R.

Kings College London Geocomputation

Lots of content is available here - https://github.com/kingsgeocomp ; but some highlights include:

Classifying Satellite Imagery in R

A nice set of R materials for looking at satellite data...

Introduction to GIS

These are some really nice resources from Monica Stephens for teaching very elementary GIS to students (first-year undergrads with little math/computer skills); including concepts without computers.

Introduction to QGIS: Understanding and Presenting Spatial Data

An introduction to QGIS and spatial data, no previous knowledge required

Introduction to Spatial Data & Using R as a GIS

An introduction to using R as a GIS, with no previous experience of coding or programming required.

Friendly Cities Lab Practicals

Some practicals form the Friendly Cities Lab at Georgia Tech

University of Bristol Topics in Advanced Spatial Modelling

This is a short course being taught over the next 2 weeks on advanced spatial modelling. The course is open for remote attendance by the links detailed in the website below:

UCL Teaching Materials

Here's a near full, and a bit unstructured, set of materials used to teach spatial data with R at UCL both to geographers and those enrolled on the Q-Step programme. https://jamescheshire.github.io/learningR/intro-to-r.html. Materials are taken from the CDRC tutorials too and the links to data may be broken due to a recent upgrade. Full data available here: https://dataviz.spatial.ly/worksheets/

ESRI Learn

This resource has over 200 lessons and paths (groups of lessons) on lotsof topics including some R / Data Science. In the gallery you can filter by product - e.g. Arcgis Pro, topic, etc.

Spatial Data Science with PySAL

This repository contains the materials and instructions for the PySAL workshop that was delivered at SciPy 2020.

Past Scientific Python Conferences on Spatial Data Science

Two past Scientific Python Conferences have been recorded and put on Youtube, alongside instructional materials for the course. These are approximately 3-hour long tutorials in how to do spatial data analysis in Python.

Resources for Teaching with and about GIS Using Online Data, Tools, and Other Information

Given the current challenge of moving your GIS courses to a fully online environment, Joseph Kerski has put together these great materials: https://github.com/GDSL-UL/Teaching_Links/blob/master/ESRI_Links.md

30 Days of R

This comes from the Leeds Data Society (based in University of Leeds), plus lots of other useful resources

Leeds Geocomputation

A variety of materials have been put online from the University of Leeds including

Programming for Geographical Information Analysis

A slightly older course on Programming in Java for Social Scientists

GIS, Geocomputation and Geoplanning - practicals in NetLogo (ABM)

Lots of additional resources free online can be found under each chapter for the ABM and GIS book by Crooks et al. - https://www.abmgis.org

A 6 week free online course in fundamental cartography. If you take the course 'live' you get access to exercises, data, videos, forums, software etc. Alternatively, you can download just the data and exercises, and see links to the videos from the download link. Resources cna be used in your own work and courses.

Sign up to take the next course offering:

Go to the basic resource download:

Videos...

Other Bits...

This Body of Knowledge documents the domain of geographic information science and its associated technologies (GIS&T). By providing this content in a new digital format, UCGIS aims to continue supporting the GIS&T higher education community and its connections with the practitioners.

The University of Manchester has a spatial skills portal that features screencast tutorials on some of the common features of ArcMap and IDRISI and the new Urban Design Toolkit.

Coursera

Coursera are providing free access to impacted universities: https://blog.coursera.org/helping-universities-and-colleges-go-fully-online-in-response-to-the-coronavirus/ - There is a lot of GIS content.

Microsoft

Some useful guidance here about how to use Teams for remote learning: https://docs.microsoft.com/en-us/MicrosoftTeams/remote-learning-edu

Carto

Carto do a lot of great things with their platform - students and educators can free accounts here: https://carto.com/help/getting-started/student-accounts/ - also don't forget their new Kepler.gl link.

Stuck with streaming and screen recording....?

Alasdair Rae's Tweet is excellent - https://twitter.com/undertheraedar/status/1238735124524675072?s=20

Earth Data Science

Open tutorials and course materials covering topics including data integration, GIS and data intensive science. Uses Python and/or R.

Thanks...

Thanks to Jon Reades, Alex Singleton, Stephano De Sabbata, James Cheshire, Mike Gould, Steve Farber, Joseph Kerski, Robin Lovelace, Francisco Rowe, Dani Arribas-Bel, Adam Dennett, Anthony Robinson, Richard Kingston, Andrew Maclachlan, Alasdair Rae, Monica Stephens, Sergio Rey, Ed Manley, Alison Heppenstall, Ken Steif, Andrew Crooks, Luc Anselin, Marynia Kolak, Clio Andris, Angela Li, Kevin Credit, Roger Bivand, David O'Sulivan, Eli Knaap, Henrikki Tenkanen, David Whipp, Kyle Walker, Kenneth Field, Geoff Boeing, Levi Wolf, Nick Bearman who have all supplied content for this list.... plus anyone we have forgotten!

About

A repo of teaching resources for Geographic / Spatial Data Science, GIS and Statistics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published