Course Title: Spatial Information Science Analytics
Part A: Course Overview
Course Title: Spatial Information Science Analytics
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
GEOM1057 |
City Campus |
Undergraduate |
145H Mathematical & Geospatial Sciences |
Face-to-Face |
Sem 2 2007, Sem 2 2008, Sem 2 2009, Sem 2 2010, Sem 2 2011, Sem 2 2012, Sem 1 2013, Sem 1 2014, Sem 1 2015, Sem 1 2016 |
GEOM1057 |
City Campus |
Undergraduate |
171H School of Science |
Face-to-Face |
Sem 1 2017, Sem 1 2018, Sem 1 2019, Sem 1 2020, Sem 1 2021, Sem 1 2022, Sem 1 2023 |
GEOM2133 |
City Campus |
Postgraduate |
145H Mathematical & Geospatial Sciences |
Face-to-Face |
Sem 2 2009, Sem 2 2010, Sem 2 2011, Sem 2 2012, Sem 1 2013, Sem 1 2014, Sem 1 2015, Sem 1 2016 |
GEOM2133 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
Sem 1 2017, Sem 1 2018, Sem 1 2019 |
Course Coordinator: Dr Gang-Jun Liu
Course Coordinator Phone: +61 3 9925 2425
Course Coordinator Email: gang-jun.liu@rmit.edu.au
Course Coordinator Location: 12.12.17
Course Coordinator Availability: by appointment
Pre-requisite Courses and Assumed Knowledge and Capabilities
Required Prior Study
You should have satisfactorily completed following course/s before you commence this course.
Alternatively, you may be able to demonstrate the required skills and knowledge before you start this course.
Contact your course coordinator if you think you may be eligible for recognition of prior learning.
Course Description
This course extends your understanding of geographic information science and focuses on quantitative methods of spatial pattern analytics applicable to different types of geographical data (points, lines, areas, and surfaces). It emphasises spatial statistical and numerical techniques for describing, analysing, and comparing spatial patterns so that spatial relationships among relevant geographical phenomena can be characterised, modelled, predicted, or optimised. Topics covered in this course include: statistical measures and GIS-based methods for spatial interpolation, spatial pattern analysis and regression analysis using spatial data.
Objectives/Learning Outcomes/Capability Development
This course contributes to the development of the following Program Learning Outcomes in 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 geospatial science.
2.1 Apply standard and advanced techniques to solve a range of measurement and data management problems.
3.3 Apply critical and analytical skills in a scientific and professional manner
On successful completion of this course, you should be able to:
- Define the geographical concepts of distance, adjacency, interaction, and neighbourhood, show how these can be recorded using matrix representations and demonstrate improved understanding of these concepts in the context of spatial data analytics;
- Identify and outline problems in the statistical analysis of spatial data associated with spatial autocorrelation, modifiable areal units, scale, and non-uniformity of geographical space;
- Select and apply suitable statistical /quantitative / numerical measures / methods for describing spatial patterns, quantifying spatial relationships, and identifying spatial clusters, and perform GIS-based operations for spatial data analysis to complete set tasks of spatial interpolation, spatial pattern and cluster analysis, and regression analysis using spatial data;
- Demonstrate improved understanding of spatial information science principles that underpin GIS-based spatial visualisation and analytical techniques for describing spatial patterns, identifying spatial clusters, and quantifying spatial relationships using spatial data;
- Demonstrate improved capability in design and implement suitable GIS-based spatial analytical and visualisation techniques and workflows for solving specific real-world geographical problems.
Overview of Learning Activities
The learning activities you will be involved in are:
- studying course materials, where syllabus material including key concepts and procedures will be presented, explained, investigated, and illustrated with examples;
- conducting lab-based practical / project works, where practical tutorials and projects will be demonstrated and discussed and feedback on your progress will be provided, guiding you to develop competencies in applying GIS operations critically and solving practical problems creatively;
- participating group-lecture consultation / feedback sessions, group discussions, and class presentation;
- timely completing written assignments (lab and project reports, class practical exercises) consisting of problem-solving tasks requiring integrated understanding and application of the subject matter.
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: Project Proposal
Weighting 10%
This assessment task supports CLOs 2 & 3
Assessment Task 2: Lab Practical Reports (3)
Weighting 30%
This assessment task supports CLOs 3 & 4
Assessment Task 3: Final Timed Tests (3)
Weighting 30%
This assessment task supports CLOs 1, 3 & 4
Assessment Task 4: Project Consultation and Submissions (Project Report, Project Database, Project Journal)
Weighting 30%
This assessment task supports CLOs 4 & 5
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.