/GISC-422

Course materials for GISC 422 Spatial Analysis and Modelling

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GISC 422 T1 2021

GISC 422 Spatial Analysis and Modelling

This class introduces key concepts and methods of spatial analysis. Practical deployment in the R statistical analysis software package is emphasised, although other tools will be surveyed.

COVID Alert level changes

If COVID alert levels change, the class will continue as follows:

  • Level 1 Class as normal. Attendance in person preferred, streamed content will be available at the link posted on Blackboard. Stay home if you are unwell.
  • Level 2 Room entry must be recorded using COVID app and/or the sign-in sheet. Sanitise hands on entry and exit from the lab. Wipe down your workstation (keyboard, mouse) with wipes provided at start and end of session. And, since the sessions are 3 hours long, wear a mask. As at other levels class will be streamed and recorded for those unwilling or unable to attend. Above all stay home if you are unwell.
  • Level 3 or Level 4 Class will be conducted solely over zoom with recordings available later for review.

Link to related video content

A consolidated list of relevant video content for this class is available on this page.

Important dates

Item Dates
Trimester 22 February to 19 June 2021
Teaching period 22 February to 28 May 2021
Mid-trimester break 5 April to 16 April 2021
Last assessment item due (in this class) 4 June 2021
Study period NA
Examination period NA
Withdrawal dates See Course additions and withdrawals

If you cannot complete an assignment or sit a test or examination, refer to Aegrotats

Lecture and lab schedule

Lectures are in Cotton 110 at 9AM on Mondays and will be followed immediately by related lab sessions in the same location. The combined session will last up to three hours, finishing before noon.

Contact details

Lecturer/coordinator

Prof. David O'Sullivan Office CO227 Extn. 6492 Office hours preferably by appointment click here but direct message me on the Slack and we can arrange contact. The office phone system is not a good way to reach me.

GIS Technician

Andrew Rae Office CO502 Office hours 1-3PM Mondays

Lab and lecture timetable

Here's the trimester schedule we will aim to follow. Bolded labs have an associated assignment that must be submitted and contributes the indicated percentage of the course credit. General instructions for the labs are here. Relevant materials (lecture slides, lab scripts and datasets) are linked below, when available.

Week# Date Lecture Lab Notes Videos
1 22 Feb Course overview R and RStudio computing environment and Markdown documents Practical
2 1 Mar Why ‘spatial is special’ Making maps in R Lecture
Practical
3 8 Mar Spatial processes Introducing spatstat Lecture
Practical
4 15 Mar Point pattern analysis Point pattern analysis (15%) Due 19 April Lecture
Practical
5 22 Mar Measuring spatial autocorrelation Moran's I (15%) Due 3 May Lecture
Practical
6 29 Mar Spatial interpolation 'Simple' interpolation in R Lecture
SEMESTER BREAK NO TEACHING
7 19 Apr Geostatistics Interpolation (15%) Due 10 May Lecture
8 26 Apr NO CLASS ANZAC Day
9 3 May Multivariate methods Geodemographics (15%) Due 24 May Lecture
10 10 May Overlay, regression models and related methods Lab content
11 17 May Cluster detection TBD
12 24 May Network analysis Tools for network analysis

Lectures

Lectures will generally consist of around an hour of presented material, followed by time for Q&A and discussion based on the materials and any related reading students have completed ahead of class.

Readings

Details of any required readings will be provided ahead of class and where possible either publicly available, or linked from Blackboard. Most readings will be from one or the other of

The first of these is freely available as a full PDF download from the library, so where possible I will emphasise materials in that book. I wrote the second book and will provide pre-publication manuscript chapters where needed.

A third book:

is more recent and is reasonably affordable, so you might consider purchasing it as a general reference and reminder of topics covered in the class.

There are also many useful online resources that cover topics that are the subject of this class. For example:

For the final assignment you will need to do your own research and assemble materials concerning how spatial analysis has been applied in specific areas of study.

Labs

Lab sessions follow the lecture sessions and will cover related practical topics. Lab materials will generally be found here. Only four sessions have an associated assessed assignment, but you should attend all labs and particpate fully to broaden your knowledge of GIScience methods and tools as any of the approaches covered may prove useful for you in other parts of the program. (Note also that a portion of the course credit is for participation in all aspects of the course.)

Software

Most of the lab work will be completed in the R programming language for statistical computing, using various packages tailored to spatial analysis work. R

We will use R from the RStudio environment which makes managing work more straightforward.

Both R and RStudio are available on the lab computers. Both are freely downloadable for use on your own computer (they work on all three major platforms). We can take a look if you are having issues with your installation, but are likely to suggest that you uninstall and reinstall. In some cases problems might arise from different versions of key packages, in which case you will have to work with the lab machine versions as we can't support multiple versions across different platforms.

Course learning objectives (CLOs)

  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

Assessment

This course is 100% internally assessed. Assessment is based on four lab assignments worth 15% of overall course credit each, and a final assignment worth 30% of course credit which is due in the exam period.

Assessment item Credit Due date CLOs
Point pattern analysis 15% 19 April 2 3 4
Spatial autocorrelation 15% 3 May 2 3 4
Spatial interpolation 15% 10 May 2 3 4
Geodemographic analysis 15% 24 May 2 3 4
Written report on application of spatial analysis in a particular topic area 30% 4 June 1
Participation (including non-assessed labs) 10% NA 1 2 3 4

Some guidance on the written report assignment expectations is provided here.

Assessments are submitted electronically via dropbox on Blackboard. I will aim to return coursework within 3 weeks. Extensions should be requested from the SGEES administration office. If you anticipate problems come and talk to me.

Late submission penalties

All assignments must be handed in by their due dates. Non-submission by the required date will result in a 5% penalty off your grade for that assignment for each day or part thereof that the coursework is late. No submissions will be accepted more than 5 days after the due date.

Computer crash or similar excuses are not acceptable. Save your material and make sure you have something to submit by the due date.

Non-assessed lab work

Note that there are also non-assessed lab sessions. These will be important for your ability to complete the final assignment effectively and to your all-around training in GIScience, so it is vital that you take them seriously as part of the course.

Additional information

The primary mode of communication for the course will be via Blackboard, so please ensure that your contact details there are up to date and are regularly checked (note that Blackboard defaults to your myvuw email address).

Class representatives

A volunteer is need to act as class representative. If you are interested let me know. Further information about the role is available here.

Other useful resources