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This course provides an introduction to remote sensing data for geospatial analysis. Students will develop skills for the acquisition of data from unmanned aerial vehicles (UAVs) and satellites. Practical work focuses on the preparation of data for use in a Geographic information system (GIS), while laboratory exercises will introduce a range of analytic software that can be used to prepare and examine remotely sensed data.
Remote Sensing data from satellite and airborne platforms is among the most important resources to obtain geospatial information in earth, biological, and social sciences. How can we make best use of this data? What are effective ways to access satellite data from data providers, and how can we effectively acquire our own data by using drones? Which kind of data from large to small scale should we acquire and use in various applications?This lecture programme introduces fundamental characteristics of remote sensing data and techniques to handle data streams for deriving geospatial information. Lectures in the first term focusing on satellite methods are accompanied by weekly labs. The focus of the second term is about hands-on experience in using drones for deriving individual 3D maps. The result will be published in a GIS story map.
Awareness of a range of remote sensing data from earth orbiting satellites and UAV sensors;Understand fundamental characteristics of remote sensing data with relevance to GIS users;Develop skills for remote sensing data analysis and the online publication of results;
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.
Any 30 points of 100-level Science, Engineering or Commerce
Students must attend one activity from each section.
• Gao, J. (2009). Digital analysis of remotely sensed imagery. • Richards, J.A. (2006). Remote sensing digital image analysis: an introduction.• Campbell, J.B. (2011) Introduction to Remote Sensing (5th edition).• Lillesand, T.M. & Kiefer, R.W. (2000) Remote sensing and image interpretation, 4th edition
Domestic fee $916.00
International fee $4,750.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
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