5: Microwave and Hyperspectral Remote Sensing Course Structure: Lectures: 2 /
Labs: 1 Credit Hours: 3 Prerequisites: Digital Image Processing Objectives: This course introduces students about the new and advanced
developments that are taking place especially in microwave and hyper
spectral remote sensing. This unit focuses on the basic concepts, data
acquisition, working mechanism, Spectral and spatial characteristics of
microwave and hyper spectral data sets. Data compression and
construction techniques, Radar and hyper spectral image processing
techniques, Active and passive remotely sensed devices data fusion
techniques, Applications of Radar and hyper spectral data sets.
Course Outline: Types, History, Advantages and Disadvantages of Active
Remote sensing,Sensor and Platform Types (RADAR, SAR, AIRSAR,
SLAR etc.), Working Mechanism, Spectral Characteristics of Microwave
Images, Key Concepts, RADAR Image Geometry and interferometry, Data
Compression and Reconstruction, RADAR Image Pre-processing and
Classification, Field Verification, Data Fusion Techniques, Microwave
Applications, Hyperspectral Remote Sensing Channels and Spectral
Libraries Sensors (AIS, AIVIS etc.), Application of Hyperspectral data.
