An Arthur Temple College of Forestry and Agriculture (ATCOFA) senior spatial science undergraduate student engaged in a multi-course undergraduate research project to expand his expertise in remote sensing and assess the applied instruction methodology employed within ATCOFA. The project consisted of performing a change detection land-use/land-cover classification for Nacogdoches and Angelina counties in Texas using satellite imagery. The dates for the imagery were spaced approximately ten years apart and consisted of four different acquisitions between 1984 and 2013. The classification procedure followed and expanded upon a series of concrete theoretical remote sensing principles, transforming the four remotely sensed raster images into corresponding classified vector maps. The progression of the research project is layed out in a step-by-step process identifying settings and addressing issues that may commonly be encountered. The results indicate that the digital imagery acquired by the Landsat 8 sensor may have resulted in more precise and consistent spectral recognition of the image pixels, and distributed them more accurately in their clusters. The results from the study validate the applied instruction methodology employed in the remote sensing curriculums and reinforce ATCOFA's mission by guiding and empowering undergraduate students with the capability of employing sophisticated remote sensing technology to accurately quantify, qualify, map, and monitor natural resources.