|| EAM1720 |
|| ADVANCED TECHNIQUES IN REMOTE SENSING |
|| 2007/2008 |
|| Professor Richard M Lucas |
|| Semester 2 |
|| Dr Aled P Rowlands, Mr Peter Bunting |
|| EAM1320 |
| Course delivery
|| 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 Exam||3 Hours Examination. Practical-based examination (3 hours). ||50%|
|Semester Assessment|| Coursework. Fieldwork report based on planning, acquisition, interpretation and presentation of remote sensing data obtained from the Cambrian Mountains (4000 words). ||50%|
|Supplementary Exam||3 Hours Resit No resit available if student failed to attend the fieldtrip without documented and approved special circumstances. ||50%|
|Supplementary Assessment|| Resubmission Resubmit failed elements of coursework. ||50%|
Learning outcomesOn 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
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)
Field trip (2 days)
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.
|| Computer programming and development of skills in remote sensing (e.g., generation of digital elevation models). |
|| 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. |
|| 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. |
|| Fieldwork will be undertaken in groups who collectively will be involved in the experimental design. |
|| 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. |
|Subject Specific Skills
|| Use of imaging processing software.
** Recommended 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.
Dubayah, R. and Drake, J.B. (2000) Journal of Forestry Lidar remote sensing for forestry applications
Vol 98: pp. 44-46..
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.
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..
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.
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.
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.
This module is at CQFW Level 7