GEOG8702 Image Analysis in Remote Sensing GE

2018

4.5

1 x 2-hour lecture weekly
1 x 2-hour computer lab weekly

1 of GEOG2702, GEOG3015, GEOG8004 has been successfully completed

This topic will allow students to further specialise and develop skills in the use of remotely sensed imagery. It will build upon an introductory knowledge of remote sensing and furnish students with digital image analysis skills of vocational value that are fundamental to scientists in all areas. The topic will consider the elements of image interpretation; radiometric, spatial and spectral enhancement techniques; change detection analysis; and a range of classification approaches, including rule-based and Object-oriented Image Analysis for image classification and GIS modelling. Students will use ERDAS IMAGINE's image processing software to gain hands-on experience in all areas.

This topic allows students to further specialise and develop skills in remote sensing. The topic aims to provide students with a solid grounding in the fundamental principles of digital image processing and analysis techniques used to extract information from remotely sensed multi-spectral imagery. The topic will furnish students with skills and knowledge of vocational value applicable to areas such as Archeology, Biodiversity Conservation, Earth Sciences, Geography, and Environmental Monitoring and Mapping.

At the completion of the topic students are expected to be able to:

1. Discuss multispectral image interpretation and analysis principles that are fundamental to scientists across all areas, including the integration of digital image information with Geographic Information Systems (GIS)
2. Optimise multispectral image content and visualisation through a range of geometric and radiometric enhancement techniques, image arithmetic and data fusion
3. Extract useful information from remotely sensed data through a range of multispectral transformations, and classification methodologies
4. Discuss a rules-based approach to image classification and GIS modelling
5. Contribute to the successful design and implementation of a remote sensing project, including problem solving through customised application modelling using remotely sensed and GIS data
6. Demonstrate the use of professional image processing software ERDAS IMAGINE for visualisation, inquiry and analysis of remotely sensed data
7. Produce written work in accordance with good scholarly practice