Skip to main content
Unit outline_

ENVX3001: Environmental GIS

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

This unit is designed to impart knowledge and skills in spatial analysis and geographical information science (GISc) for decision-making in an environmental context. The lecture material will present several themes: principles of GISc, geospatial data sources and acquisition methods, processing of geospatial data and spatial statistics. Practical exercises will focus on learning geographical information systems (GIS) and how to apply them to land resource assessment, including digital terrain modelling, land-cover assessment, sub-catchment modelling, ecological applications, and soil quality assessment for decisions regarding sustainable land use and management. A three day field excursion during the mid-semester break will involve visiting Canberra to hear from various government agencies which research and maintain GIS coverages for Australia. By the end of this unit, students should be able to: differentiate between spatial data and spatial information; source geospatial data from government and private agencies; apply conceptual models of spatial phenomena for practical decision-making in an environmental context; apply critical analysis of situations to apply the concepts of spatial analysis to solving environmental and land resource problems; communicate effectively results of GIS investigations through various means- oral, written and essay formats; and use a major GIS software package such as ArcGIS.

Unit details and rules

Academic unit Life and Environmental Sciences Academic Operations
Credit points 6
Prerequisites
? 
6cp from (ENVI1003 or AGEN1002) or 6cp from GEOS1XXX or 6cp from BIOL1XXX or GEOS2X11
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Aaron Greenville, aaron.greenville@sydney.edu.au
Demonstrator(s) James Moloney, james.moloney@sydney.edu.au
Andree Nenkam Mentho, andree.nenkam@sydney.edu.au
Lecturer(s) Eleanor Bruce, eleanor.bruce@sydney.edu.au
Thomas Bishop, thomas.bishop@sydney.edu.au
Bree Morgan, bree.morgan@sydney.edu.au
Aaron Greenville, aaron.greenville@sydney.edu.au
Type Description Weight Due Length
Final exam (Open book) Type C final exam Final exam
Written examination
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO8 LO9
Skills-based evaluation Module 1 Lab work
Lab skills assessment based on Module 1
10% Week 03 Variable
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8
Skills-based evaluation Module 2 Lab work
Lab skills assessment based on Module 2.
10% Week 06 Variable
Outcomes assessed: LO3 LO5 LO6 LO7 LO8 LO9
Skills-based evaluation Module 3 Lab work
Lab skills based on Module 3
10% Week 09 Variable
Outcomes assessed: LO3 LO4 LO5 LO6 LO7 LO8 LO9
Assignment group assignment Research report and presentation
Report and presentation
30% Week 12 10-12 pages, 5 minutes
Outcomes assessed: LO3 LO5 LO7 LO8 LO9
group assignment = group assignment ?
Type C final exam = Type C final exam ?

Assessment summary

  • Practical reports: Fortnightly practical exercises using GIS software.
  • Research report and presentation: In groups, students will answer an environmental or social question using geospatial data.
  • Final exam: The final written exam will test students’ knowledge gained from all lectures and practicals.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an exceptional standard as defined by grade descriptors or exemplars established by the faculty.

Distinction

75 - 84

To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a very high standard as defined by grade descriptors or exemplars established by the faculty.

Credit

65 - 74

To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a good standard as defined by grade descriptors or exemplars established by the faculty.

Pass

50 - 64

o be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an acceptable standard as defined by grade descriptors or exemplars established by the faculty

Fail

0 - 49

To be awarded to students who, in their performance in assessment tasks, fail to demonstrate the learning outcomes for the unit at an acceptable standard established by the faculty.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 GIS: Introduction to unit of study and GIS Lecture (1 hr) LO1 LO2
GIS: Types of geospatial data Lecture (1 hr) LO1 LO5 LO9
Introduction to ArcGIS Practical (3 hr) LO1 LO2 LO5 LO9
Week 02 GIS: Raster data Lecture (1 hr) LO1 LO2
GIS operations - querying multiple layers Lecture (1 hr) LO1 LO2 LO7
Working with vectors and rasters Practical (3 hr) LO1 LO2 LO5 LO6 LO7 LO8 LO9
Week 03 GIS: Co-ordinate systems and map projections Lecture (1 hr) LO1 LO2
GIS: Introduction to GPS Lecture (1 hr) LO1 LO2 LO3 LO4
Mapping citizen science data\ Terrain modelling Practical (3 hr) LO1 LO2 LO3 LO4
Week 04 Spatial modelling: multi-criteria decision analysis in GIS Lecture (1 hr) LO1 LO2 LO3 LO4 LO5
Spatial modelling: representing complex environmental systems Lecture (1 hr) LO1 LO2 LO3 LO4
Application of raster principles to marine spatial planning Practical (3 hr) LO1 LO2 LO3 LO4 LO6 LO7 LO8 LO9
Week 05 Spatial modelling concepts Lecture (1 hr) LO1 LO2 LO3 LO4 LO5 LO7
Spatial modelling applications Lecture (1 hr) LO1 LO2 LO3 LO4 LO7
Spatial modelling and prediction Practical (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Week 06 Spatial data uncertainty: is it the achilles heal of GIS? Lecture (1 hr) LO1 LO2 LO3 LO4 LO5 LO7
Misleading maps Lecture (1 hr) LO1 LO2 LO3 LO4 LO5 LO7 LO8
The role of field based validation Practical (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Week 07 Remote sensing: principles Lecture (1 hr) LO1 LO2 LO3 LO4 LO5
Remote sensing: environmental analysis Lecture (1 hr) LO1 LO2 LO3 LO4 LO5
Remote sensing: introduction Practical (3 hr) LO1 LO2 LO3 LO4 LO5
Week 08 Remote sensing: indices Lecture (1 hr) LO1 LO2 LO3 LO4 LO5
Remote sensing: indices Lecture (1 hr) LO1 LO2 LO3 LO4 LO5
Remote sensing: indices Practical (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Week 09 Remote sensing: classification Lecture (1 hr) LO1 LO2 LO3 LO6
Remote sensing: classification Lecture (1 hr) LO1 LO2 LO4 LO5
Remote sensing: classification Practical (3 hr) LO3 LO5 LO6 LO7 LO8 LO9
Week 10 Applications: Sound management requires good science Lecture (1 hr) LO1 LO3 LO5 LO7 LO8 LO9
Applications: Guest speaker Lecture (1 hr) LO1 LO3 LO7 LO8 LO9
Practical time for group projects Practical (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Week 11 Applications: Natural processes that build our coasts/catchments Lecture (1 hr) LO1 LO3 LO5 LO7 LO8 LO9
Applications: Guest speaker Lecture (1 hr) LO1 LO3 LO5 LO6 LO7 LO8 LO9
Practical time for group projects Practical (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Week 12 Applications: Human induced perturbations causing pollution Lecture (1 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Applications: Guest speaker Lecture (1 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Group presentations Practical (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9

Attendance and class requirements

To successfully complete this Unit, you are required to attend 80% of it.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. define the basic terms associated with geographic information science, including technologies, systems and studies
  • LO2. differentiate between spatial data and spatial information
  • LO3. source geospatial data from government and private agencies
  • LO4. decipher various air-borne and space-borne sensors and their carriers
  • LO5. apply geo-image analytical techniques for land resources assessment and management
  • LO6. build spatial databases of geographical entities for data querying and retrieval
  • LO7. apply conceptual models of spatial phenomena for practical decision-making in, for example, land management and land use planning, etc
  • LO8. apply critical analysis of situations to apply the concepts of spatial phenomena to solve environmental and land resource problems
  • LO9. communicate results of scientific investigations effectively through various means such as oral, written and essay formats, use major GIS and remote sensing software packages, e.g. ArcGIS™.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

Update final exam info

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.
 

General laboratory safety rules

  • No eating or drinking is allowed in any laboratory under any circumstances 
  • A laboratory coat and closed-toe shoes are mandatory 
  • Follow safety instructions in your manual and posted in laboratories 
  • In case of fire, follow instructions posted outside the laboratory door 
  • First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory 

As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.