SPA443 Remote Sensing 3: Information Extraction (8)

In this subject students will develop knowledge and practical skills regarding the appropriate use of remote sensing image processing techniques to produce valuable spatial information. Topics include hyperspectral imagery, change detection methods, and remote sensing image processing techniques utilising artificial intelligence. Open source remote sensing data are also considered and evaluated. Image processing software is utilised to develop advanced level practical skills in remote sensing image analysis; a working knowledge of remote sensing image analysis software is assumed. Students who complete this subject will have advanced, specialised knowledge and skills in remote sensing.


Session 1 (30)
Albury-Wodonga Campus

Continuing students should consult the SAL for current offering details: SPA443. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System



One session


School of Environmental Sciences

Enrolment Restrictions

Postgraduate study only

Assumed Knowledge

Knowledge of remote sensing principles and a working knowledge of remote sensing image analysis software, equivalent to completion of SPA441 and SPA442, are assumed.

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to apply and compare remote sensing hyperspectral image analysis techniques
  • be able to apply and evaluate methods for thematic spatial data extraction from remotely sensed data
  • be able to apply and compare methods for change detection using remote sensing data
  • be able to apply and compare artificial intelligence techniques for the analysis of remote sensing data
  • be able to describe and evaluate open source remote sensing data


This subject will cover the following topics:
  • Characteristics of hyperspectral remote sensing data
  • Information extraction techniques using hyperspectral remote sensing data
  • Remote sensing change detection workflow
  • Remote sensing change detection algorithms
  • Remote sensing information extraction techniques using artificial intelligence
  • Open sources of remote sensing data

Indicative Assessment

The following table summarises the assessment tasks for the online offering of SPA443 in Session 1 2020. Please note this is a guide only. Assessment tasks are regularly updated and can also differ to suit the mode of study (online or on campus).

Item Number
Value %
Multi-temporal change analysis
Hyperspectral image classification
Remote sensing 3 take home exam

Special Resources

Image processing software (ENVI) is used in this subject. Software is supplied.

The information contained in the CSU Handbook was accurate at the date of publication: May 2021. The University reserves the right to vary the information at any time without notice.