Intergrating field experiences with remote sensing for understanding vegetation indices

TitleIntergrating field experiences with remote sensing for understanding vegetation indices
Publication TypeBook Chapter
Year of Publication1989
AuthorsNellis, MD
EditorNellis, MD, Lougeay, R, Lulla, K
Book TitleCurrent Trends in Remote Sensing Education
Pagination93 -100
PublisherGeocarto International Centre
CityHong Kong
Accession NumberKNZ00248
Abstract

Students of the geographic field research techniques course at Kansas State University were presented with the problem of integrating data collected from field experiences with Landsat MSS digital data to better understand the influence of physical and cultural factors on the condition of vegetation. As part of a National Science Foundation sponsored program, Konza Prairie Natural Area in the Kansas Flint Hills, has developed a diversity of rangeland management strategies based on watershed units. During the summer of 1987, students were asked to gather information at the Konza site on field conditions along transects for selected watersheds. Students noted dominant vegetation types, density of vegatitive cover, and relative vegetetive greenness. Landsat MSS digital data sets for a date similat to the field data were then analyzed by the students using a microcomputer-based digital image processing system. Mean brightness values for each MSS band by selected watersheds were calculated and entered into two algorithms that estimated soil brightness and green vegetation index. Students then compared field data with the derived soil brightness and green vegetation indices, and determined reasons for variation in indices between watersheds