Course Title: GIS Fundamentals

Part A: Course Overview

Course Title: GIS Fundamentals

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

GEOM1159

City Campus

Postgraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006,
Sem 2 2006,
Sem 1 2007,
Sem 2 2007,
Sem 2 2008,
Sem 1 2009,
Sem 2 2009,
Sem 1 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

GEOM1159

City Campus

Postgraduate

171H School of Science

Face-to-Face

Sem 1 2017,
Sem 2 2017,
Sem 1 2018,
Sem 2 2018,
Sem 1 2019,
Sem 2 2019,
Sem 1 2020,
Sem 2 2020,
Sem 1 2021,
Sem 2 2022,
Sem 1 2023

GEOM1161

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006,
Sem 1 2009

GEOM2041

City Campus

Research

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2016

Course Coordinator: Dr Alan Both

Course Coordinator Phone: +61 3 9925

Course Coordinator Email: alan.both@rmit.edu.au

Course Coordinator Availability: By appointment or by email


Pre-requisite Courses and Assumed Knowledge and Capabilities

None


Course Description

This course introduces students to the key facets of geographic information science (GIScience).  The course commences by reviewing definitions for GIS including the distinction between GISystem, GIScience, components of GIS and a brief history of GIS.  The special characteristics of spatial, or geographic, data are then reviewed.  Scale, orientation and projection are introduced.  Digital models of spatial data are then reviewed.  Methods for acquiring, transforming and manipulating spatial data are discussed.  The two models for spatial data storage, manipulation and presentation, raster and vector, are discussed.  Reasons for using either or both of these data structures are reviewed as part of this discussion.  Topological relationships between spatial objects will also form part of this discussion. 

In addition to spatial data, attribute, or textual, data are an important item in any GIS.  We will discuss how attribute data can be stored and analysed within GIS.  The relational database model will be discussed as a convenient method for the storage of this attribute information.  Entity-relationship modelling will be discussed as a method for conceptualising the storage of attribute data. The remaining lecture program will be comprised of case studies, where spatial information and the application of GIS has been an integral component. 


Objectives/Learning Outcomes/Capability Development

This course contributes to the program learning outcomes for GC187 Graduate Certificate in Geospatial Science and MC265 Master of Geospatial Science: 

1.1  Describe the fundamental and applied scientific knowledge that underpins  the geospatial sciences. 
1.2  Demonstrate in-depth understanding of the spatial models and mathematical methods used in contemporary practice. 
1.3  Identify and elaborate specialist bodies of knowledge in geospatial science. 
1.4  Discern research directions and advances within geospatial science. 
2.1  Apply standard and advanced techniques to solve a range of measurement and data management problems. 
2.2/2.3  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. 

For more information on the program learning outcomes for your program, please see the program guide.  


On completion of this course you should be able to: 

  1. Synthesise complex knowledge of geographical information science and principles of spatial data analysis using GIS 
  2. Research and apply GIS-based spatial data analysis procedures for set tasks of vector and raster data analysis.
  3. Research and apply GIS-based spatial data analysis procedures for set tasks of network analysis; and 
  4. Research and apply GIS-based spatial data analysis procedures for set tasks of suitability analysis.   


Overview of Learning Activities

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both.

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Assessment Tasks

Assessment Task 1: Practical Assignments (5)
Weighting 30% 
This assessment task supports CLOs 2 & 3   

Assessment Task 2: In-class Tests (2)
Weighting 30% 
This assessment task supports CLOs 1, 2 & 3 

Assessment Task 3: Scientific Communication Task (1)
Weighting 40% 
This assessment task supports CLOs 1 & 4 

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.