Course Title: Spatial Information Science Principles

Part A: Course Overview

Course Title: Spatial Information Science Principles

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


145H Mathematical & Geospatial Sciences


Sem 1 2006,
Sem 2 2006,
Sem 1 2007,
Sem 2 2007,
Sem 1 2008,
Sem 2 2008,
Sem 1 2009,
Sem 2 2009,
Sem 1 2010,
Sem 2 2010,
Sem 1 2011,
Sem 2 2011,
Sem 1 2012,
Sem 2 2012,
Sem 1 2013,
Sem 2 2013,
Sem 1 2014,
Sem 2 2014,
Sem 1 2015,
Sem 1 2016,
Sem 2 2016


City Campus


171H School of Science


Sem 2 2017,
Sem 2 2018,
Sem 2 2019

Course Coordinator: Dr Gang-Jun Liu

Course Coordinator Phone: +61 3 9925 2425

Course Coordinator Email:

Course Coordinator Location: 012.12.17

Course Coordinator Availability: By appointment, by email

Pre-requisite Courses and Assumed Knowledge and Capabilities

Enforced Prerequisite:

GEOM1033 Spatial Information Science 1

Course Description

This course extends your prior knowledge of geographic information science, introduces you to principles of spatial data analysis using GIS and enriches your skills in performing GIS operations for spatial analysis with both vector and raster datasets. Topics covered in this course include: principles, procedures and operations for vector data analysis, raster data analysis, network analysis and suitability analysis.

Objectives/Learning Outcomes/Capability Development

This course contributes to the development of the following Program Learning Outcomes for BH117 Bachelor of Science (Geospatial Science) (Honours)


1.2 Demonstrate in-depth understanding of the spatial models and mathematical methods used in contemporary practice.
1.3 Understand specialist bodies of knowledge in surveying and geospatial science.
2.1 Apply standard and advanced techniques to solve a range of measurement and data management problems.
2.3 Be proficient in the recording, storage, management and reporting of spatial information.
3.2 Interpret and critically analyse results and make informed judgments on the appropriateness of solutions.
4.1 Communicate effectively by means of oral, written and graphical presentations to peers and a wider audience.
6.2 Work with others and contribute in a constructive manner to group and team activities.

On completion of this course you should be able to:

1. Demonstrate knowledge of geographical information science and principles of spatial data analysis using GIS
2. Select and apply suitable GIS operations for set tasks of vector data analysis;
3. Select and apply suitable GIS operations for set tasks of raster data analysis;
4. Design and implement suitable GIS-based spatial data analysis procedures for set tasks of network analysis; and
5. Design and implement suitable GIS-based spatial data analysis procedures for set tasks of suitability analysis.

Overview of Learning Activities

The learning activities you will be involved in are:

• Frequent participation in lectures, where syllabus material will be presented and explained and key concepts and procedures defined and illustrated with examples;
• Active engagement in laboratory sessions, where practical tutorials and projects will be demonstrated and discussed. Feedback on your progress will be provided, guiding you to develop competencies in applying GIS operations critically and solving practical problems creatively;
• Timely completion of written assignments consisting of problem solving tasks requiring integrated understanding of the subject matter.


Teacher Guided Hours: 46 per semester
Learner Directed Hours: 46 per semester

Overview of Learning Resources

You will be able to access course information and learning materials through electronic distribution (Canvas LMS) and will be provided with copies of additional materials in class. Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided. You will also be able to use supported GIS software and computer laboratories for practical tutorials and projects and written assignments.

A library subject guide is available at:

Overview of Assessment

The assessment for this course comprises written submissions to set tasks, a portfolio summarising assigned practical activities completed during the semester and written class tests. During the semester you will also be required to give class presentations on an assigned essay / project topic and act as a peer assessor of other students. Feedback on written assignments and presentations will enable you to assess your progress in the course during the semester.

Note that: This course has no hurdle requirements.

Assessment tasks:

Early assessment task 1: Class Test 1
Weighting 15%
This assessment task supports CLOs 1, 2 and 3


Assessment Task 2: Class Test 2
Weighting 15%
This assessment task supports CLOs 1, 4 and 5


Assessment Task 3: Portfolio of Laboratory Reports 1-4
Weighting 40%
This assessment task supports CLOs 2, 3, 4 and 5


Assessment Task 4: Project Submission
Weighting 30%
This assessment supports CLOs 1, 2, 3, 4 and 5