- Professor Daniel Donoghue (Professor - Durham University)
|Delivery Type||Delivery length / details|
|Lecture||5 x 2 Hour Lectures|
|Practical||11 x 2 Hour Practicals|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||Coursework. fieldwork report based on analysis of remote sensing data (3000 words)||50%|
|Semester Exam||3 hours practical-based examination||50%|
|Supplementary Assessment||Resubmission of failed assignment||50%|
|Supplementary Exam||3 Hours Supplementary Exam To be scheduled in F4, due to nature of computers used for exam.||50%|
On successful completion of this module students should be able to:
- Identify, for particular applications, the most appropriate remote sensing datasets.
- Independently using remote sensing software for the analysis of multispectral, hyperspectral, lidar and radar data.
- Implement approaches to the derivation of products from remote sensing data (e.g., vegetation indices and digital elevation models).
- Undertake field studies to support the interpretation and analysis of remote sensing data.
- Be able to apply an object oriented classification of remote sensing imagery
The module is intended to provide students with a background in advanced processing and analysis of a range of remote sensing data for applications in physical geography, biology, computer science and physics. The module also includes a field visit within the local area, during which insight into the interpretation of remote sensing data acquired by a range of sensors will be obtained.
- Object-orientated image analysis and classification
- Techniques for change detection between datasets
- Hyperspectral data analysis
- Laser scanning
- Radar data anaylsis
- Thermal remote sensing data analysis
|Skills Type||Skills details|
|Application of Number||Problem solving assignment|
|Communication||Skills report writing and submission of a discussion paper. Discussion groups within the Blackboard teaching and learning environment|
|Improving own Learning and Performance||Library and web-based referencing; literature review and discussions with scientists|
|Information Technology||Use of commercial and open sources software for practical applications. Specific skills in programming and statistical analysis.|
|Personal Development and Career planning||Awareness of scientific literature, functionality of software and programming. Provision of advice and information for careers.|
|Problem solving||Image classification through programming and development of skills in remote sensing data interpretation; awareness of scientific literature and future directions for research.|
|Research skills||Basic strategies relating to remote sensing data sources and acquisition strategies, data integration and processing within the framework of a GIS and effective analysis and interpretation of remote sensing data, field data collection to support interpretation of remote sensing data. Reviewing literature.|
|Subject Specific Skills||As above|
|Team work||Fieldwork will be undertaken in groups who will be involved in decisions relating to data collection and image analysis and interpretation|
This module is at CQFW Level 7