Offering Information
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Course Team
Kithsiri Perera
Armando Apan
Summary
Remote sensing is an important technology for land resource mapping, monitoring and modelling. Remotely sensed images provide an invaluable source of current and archival information about the geographical distribution of natural and cultural features. The use of digital images in various applications is aiding planners and decision-makers at various project… For more content click the Read More button below.
SynopsisThis course is designed to provide students with the basic and intermediate knowledge and skills in the digital processing of remotely sensed images. Topics include: basic principles of remote sensing; image processing systems; pre-processing of remotely-sensed data; image enhancement techniques; image transformation and filtering techniques; unsupervised classification; supervised classification; post classification and accuracy assessment including field investigations; integration with GIS; and applications and case studies. Various imagery products will be studied, such as panchromatic, multispectral and hyperspectral data. Image processing software will be used to demonstrate and reinforce the concepts and principles involved.
Offerings
Trimester 1
OL-TWMBA-TR1
Learning Outcomes
Upon completion of this course, graduates will be able to:
1.
Evaluate the importance and role of remote sensing and digital image processing in land resource mapping, monitoring and modelling
2.
Demonstrate knowledge of the concepts and techniques involved in digital image processing of remotely sensed data
3.
Choose and apply appropriate image processing technique(s) for a specific requirement
4.
Evaluate the accuracy of image classification output
5.
Compare with the traditional and recent applications of image processing techniques
6.
Use image processing software to analyse temporal, spectral and spatial differences.
Topics
1. Basic principles of remote sensing
2. Remote sensing platforms and sensors
3. Image processing systems
4. Pre-processing of remotely sensed data
5. Image enhancement, transformation and filtering techniques
6. Image classification
7. Integration with GIS
8. Applications and advanced topics
Assessments
Assessment due dates (as listed in Week Due) are indicative until finalised by the end of Week 1 for each Study Period (Offering). After Week 1, Assessment due dates may change with the approval of the Dean (Academic) or Delegate in limited circumstances. All Assessment due date changes approved after Week 1 will be communicated to students accordingly via Handbook and StudyDesk.