Year
2019
Units
4.5
Contact
1 x 2-hour lecture weekly
1 x 2-hour computer lab weekly
1 x 1-day excursion per semester
Prerequisites
^ = may be enrolled concurrently
1 ^ STEM1002 - Introduction to Geographical Information Systems
1a GIST1201 - Geospatial Information Systems PW
2 1 of GEOG1003, GEOG2700, GEOG8700
Must Satisfy: (((1 or 1a)) or (2))
Enrolment not permitted
1 of GEOG2701, GEOG8701, STEM8003 has been successfully completed
Assessment
Report, Test(s)
Topic description
This topic will introduce students to the theory and application of remote sensing. The topic is designed for students across 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 field training and testing. Hexagon’s professional image processing software (M.Apps and Geospatial) is used to provide students with hands-on experience. Students will also be introduced to a range of digital image analysis techniques that are used to extract useful Earth resource information from imagery.
Educational aims
The topic aims to introduce students to the theory and application of remote sensing while also providing experience in the use of remote sensing software that will furnish students with skills of vocational value applicable to a range of areas such as Archaeology, Biodiversity Conservation, Earth Sciences, Geography and Environmental Monitoring and Mapping.
Expected learning outcomes
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, including the nature of a range of satellite platforms, sensors, classification methods and data availability for earth resource mapping and monitoring, and the treatment of error and distortion in remotely sensed imagery

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

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

  5. Produce written work in accordance with good scholarly practice.