EM336 Remote Sensing and Image Analysis

UNE has cancelled in-person, paper-based exams for Trimester 2. Instead, all exams will either be transferred to other modes of assessment, or offered online. There may be some discrepancies to published unit information while we work through the University processes to approve the changes and reflect them through publication. Information about online exams is available on UNE's Online Supervised Exams page.

Updated: 22 April 2020
Credit Points 6
Location Teaching Period Mode of Study
Armidale Trimester 1 Online
Armidale Trimester 1 On Campus
Intensive School(s) None
Supervised Exam There is no supervised examination.
Pre-requisites 48cp or candidature in a postgraduate award
Co-requisites None
Restrictions EM432 or EM436 or EM532 or EM536
Notes None
Combined Units EM436 - Remote Sensing and Image Analysis
EM536 - Remote Sensing and Image Analysis
Coordinator(s) Ross Jenkins (rjenkins@une.edu.au)
Unit Description

Introduction to advanced aspects of using remote sensing and image processing for resource management. The subject will cover aspects of: digital image display and enhancement; image ratios; principal components analysis; image classification and image rectification. Case studies examining the combination of remote sensing and GIS for natural resource management will be examined. Students should be computer literate and access to the Internet is highly desirable.

Prescribed Material


Note: Students are expected to purchase prescribed material. Please note that textbook requirements may vary from one teaching period to the next.

Introductory Digital Image Processing: A Remote Sensing Perspective

ISBN: 9780134058160
Jensen, J.R., Pearson 4th ed. 2015

Note: This version is a Hard Cover. The eBook is much cheaper (ISBN: 9780134395166).

Text refers to: Trimester 1, On Campus and Online

Disclaimer Unit information may be subject to change prior to commencement of the teaching period.
Title Exam Length Weight Mode No. Words
Compulsory Practical Activity 20%
Relates to Learning Outcomes (LO)

LO: 1-4

Compulsory Report 20% 1500
Relates to Learning Outcomes (LO)

LO: 1-4

Compulsory Take Home Exam 40% 2000
Relates to Learning Outcomes (LO)

LO: 1-4

Compulsory Unit Quiz 20% 1200
Relates to Learning Outcomes (LO)

LO: 1-4

Learning Outcomes (LO) Upon completion of this unit, students will be able to:
  1. apply theoretical and technical knowledge of remote sensing and image analysis to process satellite images to identify different vegetation and objects;
  2. demonstrate a broad and coherent understanding of image enhancement techniques; analyse and evaluate how these can be used to extract information from digital imagery;
  3. analyse and evaluate image data and generate solutions to simple problems involving the use of the spatial processing toolbox and its application to real-world problems; and
  4. demonstrate autonomy, well developed judgement, adaptability and responsibility as a practitioner using the spatial processing toolbox for a specified task.