|Delivery Type||Delivery length / details|
|Lecture||10 x 1 hours|
|Practical||10 x 1 hours|
|Other||Field study visit (2 x 8 hours)|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||Coursework. Fieldwork report based on planning, acquisition, interpretation and presentation of remote sensing data obtained from the Cambrian Mountains (4000 words).||50%|
|Semester Exam||3 Hours Examination. Practical-based examination (3 hours).||50%|
|Supplementary Assessment||Resubmission Resubmit failed elements of coursework.||50%|
|Supplementary Exam||3 Hours Resit No resit available if student failed to attend the fieldtrip without documented and approved special circumstances.||50%|
On successful completion of this module students should be able to:
1. Identify, for particular applications, the most appropriate remote sensing datasets.
2. Independently use remote sensing software (including IDL and eCognition) for the analysis of multispectral, hyperspectral, LIDAR and radar and appropriately select tools for specific applications.
3. Derive digital elevation models from a range of remote sensing data.
4. Undertake field studies to support the interpretation and analysis of remote sensing data.
- Basic principles of eCognition
- Classification within eCognition
- Advanced procedures within eCognition
- Hyperspectral analysis (2)
- Introduction to radar
- Radar backscatter modelling
- SAR interferometry and terrain analysis
- Objected oriented segmentation and classification
- Hyperspectral analysis
- Introduction to programming in remote sensing
- DEM retrieval from photogrammetry and satellite sensors (focus on glaciers)
- LiDAR (including Terrestrial Laser Scanner) interpretation
- SAR interferometry (Gamma)
The module, which is applications focused, will provide students with a background in advanced processing and analysis of a range of remote sensing data for applications in physical geography. The module also includes a field visit to the Cambrian Mountains during which insight into the interpretation of remote sensing data acquired by different sensors will be obtained.
|Skills Type||Skills details|
|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.|
|Information Technology||Use of commercial remote sensing software (IDL ENVI, eCognition, SOCET SET, Gamma and Erdas imagine) software for practical applications. Specific skills in programming and statistical analyses.|
|Personal Development and Career planning||Provision of advice and information on careers.|
|Problem solving||Computer programming and development of skills in remote sensing (e.g., generation of digital elevation models).|
|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.|
|Subject Specific Skills||Use of imaging processing software.|
|Team work||Fieldwork will be undertaken in groups who collectively will be involved in the experimental design.|
Reading ListRecommended Text
Drake, J.B., Knox, R.G., Clark, D.B., Condit, R., Blair, J.B. and Hofton, M. (2003) Global Ecology & Biogeography Above -ground biomass estimation in closed canopy Neotropical forests using lidar remote sensing: factors affecting the generality of relationships. Vol 12: pp. 147-159 Primo search Dubayah, R. and Drake, J.B. (2000) Journal of Forestry Lidar remote sensing for forestry applications Vol 98: pp. 44-46. Primo search Imhoff, M. (1995) IEEE Transactions on Geoscience and Remote Sensing Radar backscatter and biomass saturation: ramifications for global biomass inventory 33, No 2, pp. 511-518 Primo search Justice, C.O., Townshend, J.R.G., Vermote, E.F., Masouoka, E., Wolfe, R.E., Saleous, N., Roy, D.P. and Morissete, J.T. (2002) Remote Sensing of the Environment An overview of MODIS land data processing and product status Vol 83: pp. 3-15. Primo search Kasischke, E.S., Melack, J.M. and Dobson, M.C. (1997) Remote Sensing of the Environment The Use of Imaging Radars for Ecological Applications - A Review 59, pp. 141-156 Primo search Martonchik, J., Diner, D., Pinty, B., Verstraete, M., Myneni, R., Knyazikhin, Y., and Gordon, H. (1998) IEEE Transactions on Geoscience and Remote Sensing Determination of land and ocean refrective, radiative, and biophysical properties using multiangle imaging 36, No. 4, pp. 1266-1281 Primo search Means, J.E., Acker, S.A., Harding, D.A., Blair, B.J., Lefsky, M.A., Cohen, W.B., Harmon, M. and McKee, W.A. (1999) Remote Sensing of Environment Use of large footprint scanning airborne lidar to estimate forest stand characteristics in the western Cascades of Oregon 67, pp. 298-308 Primo search
This module is at CQFW Level 7