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Remote Sensing in Environmental Sciences

 

 ECTS credits: 3 ECTS

 Course parameters:

Language: English

Level of course: PhD course

Time of year: 5 December till 9 December 2016

No. of contact hours/hours in total incl. preparation: 40/40                                                                            

Capacity limits: 15

 Objectives of the course:
The objective of the course is to give the participants the tools and insight needed to get started with advanced image analyses of remotely sensed data. Specifically, the course will introduce the students to: (1) image processing in the ENVI software, (2) pixel-based classification methods in ENVI, (3) image segmentation and object-based classification approaches in the eCognition software, (4) change detection techniques, (5) LiDAR and UAV image data methods, and (6) data download and handling in Google Earth Engine. The course will alternate between lectures, where the students are introduced to the different methods, and exercises, where the students will apply the methods to various image data sets.

 Learning outcomes and competences:
At the end of the course, the students should be able to:

- Understand the basic principles of remote sensing and its applications in environmental science

- Explain how fundamental image processing operations work for extracting thematic and biophysical information from remotely sensed data

- Be able to locate, download and order commercially available remote sensing data sets and understand their strengths and weaknesses

- Start conducting advanced pixel-based and object-based analyses

- Understand the basic principles of LIDAR data and change detection techniques

- Plan and execute a remote sensing project, including appropriate image data acquisition, pre-processing and data integration, data analysis, integration of field and image data, error assessment, and general reporting requirements

 Compulsory programme:
Preparation and active participation

 Course contents:
Lectures and computer exercises. Students need to bring their own computers.

 Prerequisites:
None

 Course organiser:
Signe Normand & Peder Klith Bøcher

 Name of lecturers:
Kasper Johansen (http://www.gpem.uq.edu.au/kasper-johansen)

Gary Richard Watmough (Aarhus University)

Urs Treier (Aarhus University)

 Literature:
Information on obligatory material to be read before the course will be send out at the latest 14 days before the course start.

 Course homepage:
None

 Course assessment:
Active participation

 Provider:
Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University

 Time:
9 am – 5 pm 5 December till 9 December 2016

 Place:
Building 1540 room 324, Ecoinformatics and Biodiversity, Ny Munkegade 114, 8000 Aarhus C

 Registration:
Deadline for registration is 16 November.

PhD students from Science and Technology at Aarhus University have preference.

If you have any questions, please contact Urs Treier e-mail: urs.treier@bios.au.dk.

 PLEASE NOTE
Deadline for registration is 16 November.

If you have any questions concerning the course content, please contact Urs Treier e-mail: urs.treier@bios.au.dk

Comments on content: 
Revised 31.10.2016