SS 19 - Image Processing for Remote Sensing

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Participants of this course will gain theoretical and practical knowledge on fundamental concepts and techniques for processing and analysis of remote sensing images acquired by Earth observation satellite and airborne systems.

This course will introduce fundamental concepts and techniques in the content of remote sensing and image processing for Earth observation from space. The course starts by introducing core concepts in remote sensing (describing the processes by which images are captured by sensors mounted on satellite and airborne platforms and key characteristics of the acquired images). Then, fundamental methodologies for processing, analyzing, and visualizing remotely sensed imagery are introduced. Topics include representation of highdimensional remote sensing images, time and frequency domain representations, filtering and enhancement. The final part of the course will introduce Google Earth Engine, a cloud-based remote sensing and image analysis platform. Students will explore basic image processing techniques with Google Earth Engine. Practical applications will be provided throughout the course.

The module consists of conventional frontal teaching in class and computer laboratory exercises designed to practically rehearse the theory taught in the lectures. The lab exercises introduce various remote sensing image processing topics, which will be examined in more detail in the homework assignments.