Remote Sensing Image Acquisition, Analysis and Applications

Module 1 provides an introduction to remote sensing, covering topics such as the atmosphere, imaging platforms, image recording, and image interpretation. The module also includes a week 1 quiz to assess understanding.

Module 2 focuses on distortions in recorded images and their correction, including topics such as geometric distortion, resampling, and image registration examples. It concludes with a week 2 quiz.

Module 3 delves into correcting geometric distortion using mapping functions, resampling, image interpretation, and enhancing image contrast. The module also includes a week 3 quiz to assess comprehension.

Module 4 introduces quantitative analysis and classification, covering topics such as correlation, covariance, and the principal components transform. The module concludes with a week 4 quiz.

Module 5 provides a worked example of the principal components transform, real-life examples, and applications. It also includes a week 5 quiz and a module 1 test to evaluate knowledge.

Module 6 introduces fundamentals of image analysis and machine learning, including topics such as the maximum likelihood classifier, minimum distance classifier, and end-of-lecture quiz solutions.

Module 7 covers training linear classifiers, support vector machines, and includes an example of the support vector machine. The module concludes with a week 7 quiz.

Module 8 delves into the neural network as a classifier, training the neural network, and provides examples. The module concludes with a week 8 quiz.

Module 9 explores deep learning and the convolutional neural network, including examples in remote sensing, and a comparison of classifiers. It concludes with a week 9 quiz.

Module 10 covers unsupervised classification and clustering, including examples of k means clustering and other clustering methods. The module concludes with a week 10 quiz and a module 2 test.

Module 11 introduces feature reduction, exploiting the structure of the covariance matrix, and feature reduction by transformation. The module concludes with a week 11 quiz.

Module 12 assesses classifier performance, map errors, classification methodologies, and other interpretation methods. The module concludes with a week 12 quiz.

Module 13 delves into the fundamentals of radar imaging, including SAR and its practical implications, scattering coefficient, speckle, and scattering mechanisms. The module concludes with a week 13 quiz.

Module 14 covers radar scattering from the earth's surface, sub-surface imaging, scattering from hard targets, and other radar remote sensing considerations. The module concludes with a week 14 quiz.

Module 15 explores geometric distortions in radar imagery, radar interferometry, change detection, and concludes with a course review. The module includes a week 15 quiz and a module 3 test.