STEM8003 Remote Sensing for all Disciplines GE

2020

4.5

1 x 2-hour lecture weekly
1 x 2-hour computer lab weekly
1 x 1-day excursion per semester

1 ^ STEM8002 - Introduction to Geographical Information Systems GE
2 1 of STEM1002, GEOG1003, GEOG2700, GEOG8700, GIST1201
Must Satisfy: ((1) or (2))

1 of GEOG2701, GEOG8701, STEM2001 has been successfully completed

Report(s), Test(s)

This topic introduces students to the theory and application of remote sensing to a wide range of disciplines. Topic material includes the nature of electromagnetic radiation, its interaction with the atmosphere and Earth surface features; sensors and data sources; the treatment of distortion in remotely sensed imagery, image classification and classification accuracy assessment. Professional image processing software is used to provide students with hands-on experience of a range of digital image analysis techniques that are used to extract useful Earth resource information from satellite data.

To educate students in the theory and application of remote sensing, with an emphasis on satellite remote sensing. Students will gain experience in the use of remote sensing software and data that will be applicable to a range of areas such as Archaeology, Biodiversity Conservation, Earth Sciences, Geography and Environmental Monitoring and Mapping.

On completion of this topic, students will be expected to be able to:

1. Identify the fundamental characteristics of electromagnetic radiation and how this energy interacts with the atmosphere and Earth materials such as vegetation, soil and water

2. Identify how electromagnetic energy reflected or emitted from these materials is recorded using a variety of remote sensing instruments

3. Extract fundamental land-cover information from satellite remotely sensed data and describe the nature of computer classification methodology of remotely sensed imagery

4. Demonstrate the use of professional image processing software for visualisation, geometric correction and classification of satellite remotely sensed data

5. Successfully communicate the results of applying image processing to satellite remotely sensed data

6. Explain appropriate classification accuracy assessment techniques to assist in image analysis.