SPA442 Remote Sensing 2: Image Processing and Analysis (8)

This subject develops knowledge and practical skills regarding the appropriate use of remote sensing image processing and analysis techniques. Topics include radiometric and geometric correction, vegetation analysis, image transformations, principle components analysis, unsupervised and supervised image classification techniques and image classification accuracy assessment. Image processing software is utilised to develop intermediate level practical skills in remote sensing image analysis; a basic working knowledge of remote sensing image analysis software is assumed.

Subject Outlines
Current CSU students can view Subject Outlines for recent sessions. Please note that Subject Outlines and assessment tasks are updated each session.

No offerings have been identified for this subject in 2018.

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

Assumed Knowledge

SPA217 OR SPA417 OR SPA441

Incompatible Subjects


Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to apply and compare methods for geometric and radiometric correction of remote sensing data
  • be able to apply and compare remote sensing vegetation analysis methods
  • be able to apply and compare techniques for remote sensing image classification
  • be able to apply and describe methods for accuracy assessment and error analysis in remote sensing image classification outputs
  • be able to evaluate remote sensing image analysis techniques using published literature


This subject will cover the following topics:
  • Radiometric and geometric correction of remote sensing imagery
  • Remote sensing vegetation analysis
  • Methods for remote sensing image transformations: raster math and band ratios
  • Principle components analysis of remote sensing imagery
  • Methods for remote sensing image classification: supervised and unsupervised techniques
  • Accuracy assessment and error analysis of remote sensing image classification results

Special Resources

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


Current Students

For any enquiries about subject selection or course structure please contact Student Central or or phone on 1800 275 278.

Prospective Students

For further information about Charles Sturt University, or this course offering, please contact info.csu on 1800 275 278 (free call within Australia) or enquire online.

The information contained in the 2018 CSU Handbook was accurate at the date of publication: August 2018. The University reserves the right to vary the information at any time without notice.