Earth Observation

Aim of the course: 

To get knowledge, understanding and practical skills of different remote sensing data and techniques to map and monitor the Earth.

Topics: 

A: Basic knowledge and theories

1) EM radiation and atmospheric properties

2) Different satellite systems and platform

3) Introduction to multi-spectral imageries

4) Introduction to Radar theories (SAR and InSAR)

B: Digital Image processing

5) Pre-processing techniques

6) Image enhancement

7) Image classification techniques

C: Applications

8) Visual image interpretation

9) Vegetation indices and time series analysis

10) Hot-spot identification

11) Mapping natural hazardous events

12) Mapping of fire events

13) SAR and InSAR applications: Topographic and 3D objects

Learning outcomes:

1. Knowledge and understanding

• Understanding multispectral images, spectral and time resolutions.
• Understanding critical pre-processing and enhancement techniques, and different classification techniques
• Knowledge of synthetic aperture radar, understanding the frequencies used in receiving radar signals.
• Knowledge of some common application techniques to map and identify natural hazards such as: soil erosion, landslide etc.
• Knowledge of some common applications of SAR and InSAR in terrain and 3D object mapping.

2. Competences and skills

• Skills in working with digital RS images and classification techniques.
• General skills in working with Radar images.
• Competence in interpreting vegetation indices
• Ability to identify different land surface features and processes using medium-high resolution satellite imagery.

3. Judgements and evaluations

• Critical understanding of how the atmosphere affects and impacts satellite sensor measurements and EO images.
• Judgement about limitations and advantages of mapping and classification techniques.
• Critical judgement of precision of geodata i.e. raster cell sizes and polygon boundaries.

Prerequisites:

General knowledge of GIS equal to 5 ECTS

Instructors:

Lecturers from the Cadeo Project, affiliated with Lund University (Sweden); Hanoi University of Mining and Geology and Hue University (Vietnam)