This lab exercise introduces students to two useful data transformation techniques used in remote sensing: the HSI transform and Principal Component Analysis (PCA). Additionally, we explore the use of spatial-domain filters for noise reduction (smoothing) and for edge-feature mapping.

The following materials, combined with your textbook, can be used as background materials and to help in answering the assignment questions.

• Lindsay, J.B. 2019. The WhiteboxTools User Manual

IMPORTANT INFORMATION: You will need to download a fresh copy of the latest version of the WhiteboxTools library before you begin this assignment. Changes have been made to the library since you completed Lab 2 and use of an older version will likely result in incorrect results. In addition, you will need to download the data associated with this lab assignment from the GEOG*3420 CourseLink site. These data, as usual, are quite large and you will need to consider data storage solutions (e.g. a dedicated USB memory stick for the course).

You will hand in a printed report summarizing the answer to each of the questions in the following exercise along with the necessary colour images. Notice that you will need to have paid your lab fee to have printing privileges in the Hutt building computer labs.