Incorporating Applied Undergraduate Research in Senior to Graduate Level Remote Sensing Courses

Autor/inn/en	Henley, Richard B.; Unger, Daniel R.; Kulhavy, David L.; Hung, I-Kuai
Titel	Incorporating Applied Undergraduate Research in Senior to Graduate Level Remote Sensing Courses
Quelle	In: International Journal of Higher Education, 5 (2016) 1, S.232-248 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1927-6044
Schlagwörter	Student Research; College Seniors; Agricultural Education; Visual Aids; Satellites (Aerospace); Classification; Land Use; Research Projects; Geographic Information Systems; Natural Resources; Maps; Texas + Suchen Sie Ihr Suchwort? Studentenforschung; College; Colleges; Senior; Hochschule; Fachhochschule; Agriculture; Education; Landwirtschaftliche Ausbildung; Landwirtschaft; Ausbildung; Anschauungsmaterial; Satellit; Classification system; Klassifikation; Klassifikationssystem; Bodennutzung; Forschungsvorhaben; Natural Ressource; Natürliche Ressource; Map; Karte
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01