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GEOGY228-23A (HAM)
Introduction to Geographical Information Systems and Big Data
15 Points
Staff
Convenor(s)
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Lars Brabyn
9170
I.2.13
lars.brabyn@waikato.ac.nz
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What this paper is about
Knowledge in the use of GIS and data analysis are now fundamental skills required for many jobs in a wide range of industries and government agencies. This is particularly the case in local and regional councils, police, health, engineering, transport and logistics, landuse planning and consultancy, and primary industry. The information age we live in, where data is being recorded on a huge scale, means that people confident in data analysis are highly employable.
The purpose of this paper is to teach students the fundamentals of GIS and data analysis skills that can be applied to a wide range of geographical applications. This paper starts at a basic level and is designed to help students build confidence in the use of computers and data analysis. Students will learn about the big geographical data sets that are in common usage, and there will be opportunities to use cloud computer to access satellite archives. Although it is not practical to use big datasets in many of the lab exercises, the skills taught in this paper will be useful for analysing big data and the lab exercises will use subsets of big data.
How this paper will be taught
This Flexi paper runs for one semester, and involves a final test. Most teaching weeks will involve lectures, online videos, a quiz, and a computer lab exercise. You are expected to work in your own time experimenting with the GIS software, reading, and reviewing notes.
The labs are in KB.04 and it is optional for you to use these lab times, but if you need assistance then attending a lab is recommended. The lab times are are shown below. The labs are like a drop in session – you can come and go as you please.
There is also the option of a virtual lab session using Zoom. The timing and details for this Zoom session will be available on the Moodle page.
The lectures and lab content for the whole course is available through Moodle and Google Drive and students are welcome to complete the paper ahead of the scheduled assessment deadlines.
Working in pairs or threes for the labs is encouraged as people learn from each other. You will need to arrange your own groups.
Learning Outcomes
Students who successfully complete the course should be able to:
Assessments
How you will be assessed
The final grade might be scaled to ensure that the distribution of the class grades is reasonably consistent with other papers.
Details associated with each assessment, including marking guides, will be available through Moodle.
All assessment must be submitted online through Moodle. Marks and feedback will also be provided through Moodle.
The seven labs (5% each) are due by the Friday (midnight) of the next teaching week that follows the day of the scheduled labs. The lab prior to the mid semester recess will not be due until the Friday after the teaching recess.
The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam.