GEOG2702 Image Analysis in Remote Sensing

2014

4.5

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

1 of GEOG2701, GEOG3014

1 of GEOG3015, GEOG8004, GEOG8702, WARM8798 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 knowledge acquired through the Introduction to Remote Sensing topic and furnish students with skills of vocational value. The topic will consider the elements of image interpretation; radiometric, spatial and spectral enhancement techniques; change detection analysis; the exploration of supervised and unsupervised classification, including rule-based and Object-oriented Image Analysis for image classification and GIS modelling. Students will use ERDAS IMAGINE's image processing software before completing a remote sensing project.

The aim of this topic is to allow students to further specialise and develop skills in the use of remotely sensed imagery. It will build upon knowledge acquired through GIS and Remote Sensing topics and furnish students with skills of vocational value. The topic will consider the elements of image interpretation; radiometric, spatial and spectral enhancement techniques; the use of high-resolution satellite imagery; change detection analysis; the exploration of both supervised and unsupervised classification, including the use of an expert rules-based approach to image classification and GIS modelling. Students will use ERDAS IMAGINE's image processing software before completing a remote sensing project.

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