Course Title: Spatial Information Science Fundamentals

Part A: Course Overview

Course Title: Spatial Information Science Fundamentals

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 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 1 2017

Course Coordinator: Assoc. Prof. Colin Arrowsmith

Course Coordinator Phone: +61 3 9925 2042

Course Coordinator Email:

Pre-requisite Courses and Assumed Knowledge and Capabilities


Course Description

This course introduces you to the key facets of geographic information science. You will review definitions used in geographic information science, including the distinction between GISystem and GIScience components of geographic information system (GIS). A brief history of GIS is also included. You will learn about the special characteristics of spatial or geographic data, and recognise scale, orientation and projection.
Digital models of spatial data are then reviewed and methods for acquiring, transforming and manipulating spatial data are discussed. Two models for spatial data storage, manipulation and presentation, raster and vector are examined and evaluated.
Topological relationships between spatial objects will also form part of this discussion. You will examine how attribute, or textual, data can be stored and analysed within GIS. The relational database model and entity-relationship modelling will be assessed as  convenient methods for the storage of attribute information.
You will be actively involved in case studies, where spatial information and the application of GIS has been an integral component.

Objectives/Learning Outcomes/Capability Development

On completion of this course you should be able to:

1. Describe the broad concept and principles of GIS, recognising the distinction between GISytems and GIScience.
2. Identify the special characteristics of spatial data and define and contrast the two primary methods for storage, manipulation and analysis of spatial information
3. Identify and apply the various types of attribute data
4. Discuss the design and operation of the relational database management system model and its relationship to the geodatabase model.
5. Implement a basic scripting tool using ModelBuilder
6. Demonstrate how GIS can be applied to real-world applications.

This course contributes to the development of the following Program Learning Outcomes in BH116 (Bachelor of Applied Science (Surveying) and BH117 (Bachelor of Science (Geospatial Science):

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.
4.1  Communicate effectively by means of oral, written and graphical presentations to peers and a wider audience.
6.1  Be self-motivated and personally responsible for your actions and learning.

Overview of Learning Activities

In this course you will actively participate in a series of classroom lectures and practical classes. You will work on the practical component in fortnightly exercises. Practical components include: an introduction to data models used within GIS; detailed exercises using vector and raster data; constructing a geodatabase and editing input data; development of a basic ModelBuilder generated tool; and a 3D GIS development using web based resources. You can access online the course material which includes lecture summaries, video links and practical exercises.  Tutorial exercises will also be conducted online.

Two hours of lectures and two hours of practical exercise per week contact.  There are also six tutorial exercises online.  There will also be an assignment which is conducted as an individual exercise outside class time. You should expect to spend a minimum of four hours in independent study each week.

Overview of Learning Resources

As a student enrolled in this course at RMIT University you can access the extensive learning resources provided in the school and in the RMIT Library, such as books, journals and other course-related materials (electronic and paper-based) Our library offers extensive services and facilities, geared to assist you in completing your studies successfully. Furthermore we will recommend to you specific text books, websites covering course content plus recommendations for further readings, and engage you in discussion board. Computer Labs with the required software are also available for your study.
A library subject guide is available at:

Overview of Assessment

Assessment tasks

The assessment consists of two (2) class tests (50% of total result), one (1) assignment (20%) and practical exercises (30%). You will receive feedback on your progress throughout the course.

Early Assessment Task:  Practical exercise 1
Weighting 6%
This assessment task supports CLO 1, 2, 3, 4, and 6.

Assessment Task 2:  Practical exercise 2
Weighting 6%
This assessment task supports CLO 2, 3 and 6.

Assessment Task 3:  Class test 1
Weighting 25%
This assessment task supports CLO 1, 2, 3, 4 and 6.

Assessment Task 4: Practical exercise 3
Weighting 6%
This assessment task supports CLO 2, 3, 4 and 6

Assessment Task 5: Major Assignment
Weighting 20%
This assessment task supports CLO 2, 3, 4, 5 and 6.

Assessment Task 6: Practical exercise 4
Weighting 6%
This assessment task supports CLO 2, 3, 4, 5 and 6.

Assessment Task 7: Practical exercise 5
Weighting 6%
This assessment task supports CLO 3, 4 and 5.

Assessment Task 8: Class test 2
Weighting 25%
This assessment task supports CLO 2, 3, 4, 5 and 6.