| Semester 2, 2022 Online | |
| Units : | 1 |
| Faculty or Section : | Faculty of Health, Engineering and Sciences |
| School or Department : | School of Surveying & Built Environment |
| Grading basis : | Graded |
| Course fee schedule : | /current-students/administration/fees/fee-schedules |
Staffing
Examiner:
Overview
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 stages and operational scales. It is essential and advantageous for GIS, surveying, and other professionals to be familiar with the concepts, techniques, and applications, involved in the digital processing of remotely sensed images.
This 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.
Course learning outcomes
The course objectives define the student learning outcomes for a course. On completion of this course, students should be able to:
- evaluate the importance and role of remote sensing and digital image processing in land resource mapping, monitoring and modelling;
- demonstrate knowledge of the concepts and techniques involved in digital image processing of remotely sensed data;
- choose and apply appropriate image processing technique(s) for a specific requirement;
- evaluate the accuracy of image classification output;
- compare with the traditional and recent applications of image processing techniques;
- use image processing software to analyse temporal, spectral and spatial differences.
Topics
| Description | Weighting(%) | |
|---|---|---|
| 1. | Basic principles of remote sensing | 10.00 |
| 2. | Remote sensing platforms and sensors | 10.00 |
| 3. | Image processing systems | 8.00 |
| 4. | Pre-processing of remotely sensed data | 12.00 |
| 5. | Image enhancement, transformation and filtering techniques | 18.00 |
| 6. | Image classification | 20.00 |
| 7. | Integration with GIS | 10.00 |
| 8. | Applications and advanced topics | 12.00 |
Text and materials required to be purchased or accessed
Student workload expectations
To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.
Assessment details
| Description | Group Assessment |
Weighting (%) | Course learning outcomes |
|---|---|---|---|
| Problem Solving 1 | No | 20 | 1,2,3,4 |
| Problem Solving 2 | No | 30 | 3,4,6 |
| Take home examination | No | 50 | 1,2,3,4,5,6 |