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303919 (v.2) Digital Image Interpretation 482
Area: | Department of Spatial Sciences |
Credits: | 25.0 |
Contact Hours: | 4.0 |
Tutorial: | 1 x 2 Hours Weekly |
Laboratory: | 1 x 2 Hours Weekly |
Syllabus: | Directed study and research. Analysis and interpretation of remotely sensed imagery, particularly from Landsat and SPOT satellites. Spectral and spatial enhancement - histogram transformation, PCA, edge and line detection, filtering. Feature extraction -supervised and unsupervised classification, clustering, image segmentation. Analysis of multitemporal (time varying) data. Selected case studies. |
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Unit Outcomes: | On completion of this unit students will have - Applied advanced image processing techniques, analysed and interpreted a wide range of commercial satellite and airborne imagery, demonstrated an understanding of the basic principles of remote sensing and the behaviour of different objects (e.g. water, vegetation, soils, urban) in different regions of the electromagnetic spectrum, understood the importance of spatial, temporal, radiometric and spectral resolution and their impact on the detection of changes in soil and vegetation, learnt how to Implement advanced image processing techniques such as Bayes' theorem and maximum likelihood classification, fuzzy signature development and classification, knowledge of the advantages and limitations of image transformation techniques - image ratioing, vegetation indices, principal component analysis, appreciated the importance of undertaking accuracy assessment for evaluation of classification results, critically assessed the adequacy of data generated by a wide range of sensors for different applications related to the mapping of natural resources, the ability to design, implement and present the results of a practical project, in a way that would be acceptable for a scholarly refereed journal or conference. |
Texts and references listed below are for your information only and current as of September 30, 2003. Some units taught offshore are modified at selected locations. Please check with the unit coordinator for up-to-date information and approved offshore variations to unit information before finalising study and textbook purchases. |
Unit References: | Lillesand T.M., (2000), Remote sensing and image interpretation, 4th ed, Wiley and Sons. Stein A, van der Meer F and Gorte B, (eds)., (1999), Spatial Statistics for Remote Sensing, Kluwer Academic Publishers. Jensen J.R., (1996), Digital Image Processing- A remote Sensing Perspective, 2nd ed, Prentice Hall. Star J, Estes J and McGwire K, (eds), Integration of Geographic Information Systems and Remote Sensing, Cambridge University Press. Sabins, Floyd F., (1996), Remote sensing, principles and interpretation, 3rd ed, W.H. Freeman & Co. Richards J. A., (1993), Remote sensing digital image analysis - an introduction, 2nd rev and enlarged ed, Springer-Verlag. Frohn R., (1998), Remote sensing for landscape ecology - new metric indicators for monitoring, modelling, and assessment of ecosystems. Lunetta R., (2000) Remote sensing change detection. Environmental monitoring methods and applications, Taylor & Francis. |
Unit Texts: | No Prescribed Texts. |
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Unit Assessment Breakdown: | Exam 20%, Lectures 30%, Project 20%, Tutorials 30%. This is by grade/mark assessment. |
Field of Education: | 31100 Geomatic Engineering (Narrow Grouping) | HECS Band (if applicable): | 2 |
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Extent to which this unit or thesis utilises online information: | Informational | Result Type: | Grade/Mark |
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Availability
| Year | Location | Period | Internal | Area External | Central External | | 2004 | Bentley Campus | Semester 2 | Y | | |
Area
External | refers to external course/units run by the School or Department, offered online or through Web CT, or offered by research. |
Central
External | refers to external course/units run through the Curtin Bentley-based Distance Education Area |
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