Outline

Overview

The critical role of geospatial science in major disturbance events, such as bushfires, coastal erosion and mapping spatio-temporal trends in NSW COVID-19 cases, has placed GIScience at the forefront of policy agendas, information sharing and community engagement. The disruptive nature of this field is clear and demand for expertise in GIS, Earth observation, spatial data analytics and location intelligence has grown. However, this expertise needs to be backed by an understanding of the science, conceptual principles and ethics that underpin these enabling technologies. We will incorporate the transformative potential of GIScience driven technologies demonstrated by disturbance events. This unit content will expose you to a breadth of analytical capabilities within GIS, various applications to complex environmental and coastal issues and ethical considerations in using and disseminating geographical information and knowledge. The fundamentals of GIS, spatial modelling and Earth observation will be introduced in the context of environmental and coastal management. You will build on these foundational concepts through problem-based learning in which GIS methods will be applied to address issues relating to fire and biodiversity, acid sulphate soils, coastal processes and water security. This unit is co-taught with GEOS3014/3914. GIScience, spatial reasoning and Earth observation in the context of environmental and coastal science and management is core to the learning objectives of both units.

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 ?	GEOS3X14
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Aaron Greenville, aaron.greenville@sydney.edu.au
Demonstrator(s)	Elise Verhoeven, elise.verhoeven@sydney.edu.au
Demonstrator(s)	Alex Jones, alexandra.jones1@sydney.edu.au
Lecturer(s)	Patrick Filippi, patrick.filippi@sydney.edu.au
	Aaron Greenville, aaron.greenville@sydney.edu.au
	Eleanor Bruce, eleanor.bruce@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Take-home short release)	Final exam Written examination	40%	Formal exam period	2 hours
Outcomes assessed:
Skills-based evaluation	Module 1 Lab work Lab skills assessment based on Module 1	10%	Week 03	Variable
Outcomes assessed:
Skills-based evaluation	Module 2 Lab work Lab skills assessment based on Module 2.	10%	Week 06	Variable
Outcomes assessed:
Skills-based evaluation	Module 3 Lab work Lab skills based on Module 3	10%	Week 09	Variable
Outcomes assessed:
Assignment	Research report and presentation Report and presentation	30%	Week 13	10-12 pages, 5 minutes
Outcomes assessed:
= group assignment ? = Type D 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. This assessment is compulsory and failure to attend, attempt, or submit will result in the award of an AF grade. If a second replacement exam is required, this exam may be delivered via an alternative assessment method, such as a viva voce (oral exam). The alternative assessment will meet the same learning outcomes as the original exam. The format of the alternative assessment will be determined by the unit coordinator.

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.

Learning support

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	GIS: Introduction to GIS	Lecture (2 hr)
Week 01	Introduction to ArcGIS	Computer laboratory (3 hr)
Week 02	GIS: Vector and raster data	Lecture (2 hr)
Week 02	Impact of the megafires on species: working with vectors and rasters	Computer laboratory (3 hr)
Week 03	GIS: Co-ordinate systems and map projections	Lecture (2 hr)
Week 03	Mapping citizen science data	Computer laboratory (3 hr)
Week 04	Remote sensing: principles	Lecture (2 hr)
Week 04	Remote sensing: introduction	Computer laboratory (3 hr)
Week 05	Remote sensing: indices	Lecture (2 hr)
Week 05	Remote sensing: indices	Computer laboratory (3 hr)
Week 06	Remote sensing: classification	Lecture (2 hr)
Week 06	Remote sensing: classification	Computer laboratory (3 hr)
Week 07	Spatial modelling: multi-criteria decision analysis in GIS	Lecture (2 hr)
Week 07	Application of raster principles to marine spatial planning	Computer laboratory (3 hr)
Week 08	Spatial modelling concepts	Lecture (2 hr)
Week 08	Spatial modelling and prediction	Computer laboratory (3 hr)
Week 09	Spatial data uncertainty: is it the achilles heal of GIS?	Lecture (2 hr)
Week 09	The role of field based validation	Computer laboratory (3 hr)
Week 10	Applications	Lecture (2 hr)
Week 10	GIS project	Computer laboratory (3 hr)
Week 11	Applications	Lecture (2 hr)
Week 11	GIS projects	Computer laboratory (3 hr)
Week 12	Applications	Lecture (2 hr)
Week 12	GIS projects	Computer laboratory (3 hr)
Week 13	Applications	Lecture (2 hr)
Week 13	GIS project presentations	Computer laboratory (3 hr)

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

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.

Outcomes
Graduate qualities

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
Learning outcomes

Responding to student feedback

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

Change in order of modules and update for 2022

Additional information

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

ENVX3001: Environmental GIS

Semester 2, 2022 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect