This unit builds on the theory and skills of KGG103 Remote Sensing: observing the Earth from above, and focuses on advanced aspects of remotely sensed image analysis that turn raw remote sensing data into valuable information. These additional remote sensing analysis skills are highly valued by employers in the geospatial industry. The unit will provide you with practical skills in image analysis techniques, such as geometric and atmospheric image correction, image filters, texture measures, image enhancements and transformations, classification algorithms, object-based image analysis, change detection, and accuracy assessment. The theory is illustrated with a range of real-world applications using optical, multispectral, hyperspectral, and LiDAR data. Computer practicals and an independent project (in pairs) promote practical remote sensing skills using the latest image processing tools. The unit is likely to be of interest to students in geography, environmental studies, earth sciences, plant science, zoology, agricultural science, computing and information systems, archaeology, and engineering who want to enhance their remote sensing knowledge and professional skills.
|Unit name||Remote Sensing: From Data to Information|
|College/School||College of Sciences and Engineering
School of Geography, Planning, and Spatial Sciences
|Discipline||Geography, Planning, and Spatial Sciences|
|Coordinator||Doctor Steve Harwin|
|Available as an elective?||Yes|
|Delivered By||University of Tasmania|
|Location||Study period||Attendance options||Available to|
- International students
- Domestic students
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|Study Period||Start date||Census date||WW date||End date|
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2024 are indicative and subject to change. Finalised census dates for 2024 will be available from the 1st October 2023. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
- Explain image analysis techniques to inform the interpretation and enhancement of remote sensing datasets.
- Apply analysis techniques on remote sensing datasets to solve environmental and social problems that require spatial solutions
- Operate remote sensing software to produce enhanced spatial information from basic datasets
|Field of Education||Commencing Student Contribution 1,3||Grandfathered Student Contribution 1,3||Approved Pathway Course Student Contribution 2,3||Domestic Full Fee 4|
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
13 x 2-hr seminars, 13 x 3-hr practicals, per semester, delivered weekly. Seminars and practical introductions will be simultaneously offered on campus and on Zoom and recorded and made available on MyLO.
|Assessment||Assignment 1: Practicals 1 - 4 (20%)|Assignment 2: Practicals 5 - 7 (20%)|Assignment 4: Quizzes and Case Study (25%)|Assignment 3: Project (35%)|
|Timetable||View the lecture timetable | View the full unit timetable|
Required readings will be listed in the unit outline prior to the start of classes.
Jensen, J.R., 2014. Remote Sensing of the Environment: An Earth Resource Perspective, 2nd edition. Prentice Hall. https://www.booktopia.com.au/remote-sensing-of-the-environment-john-r-jensen/book/9781292021706.html
|Links||Booktopia textbook finder|
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