Grasslands Discriminant Analysis Using Landsat TM Single and Multitemporal Data
2003
Guo, Xulin | Price, Kevin P. | Stiles, James
<p><i>Grassland management practices influence many bio- and geophysical processes. The ability to discriminate among different land-use practices is critical to an improved understanding of agro-ecosystem dynamics in the tallgrass prairies of the Central Great Plains. The overall objective of this study was to assess the spectral separability of three land-use practices on warm-season (C4 dominated) and cool-season (C3 dominated) grasslands using data obtained from multitemporal Landsat Thematic Mapper (TM) imagery. Results showed that cool- and warm-season grasslands could be discriminated with a high level of accuracy (91.5 percent). When grasslands were categorized by three common management practices (Conservation Reserve Program [CRP], grazing and haying), they could be discriminated with a moderately high level of accuracy (70.4 percent). Grassland management practices within warm- and cool-season grasslands (six types) were spectrally discriminated with a moderate level of accuracy (67.6 percent overall). The use of a three-date Landsat TM image dataset spanning the spring-summer-fall seasons significantly improved classification accuracy over the use of a single-date TM approach.</i></p>
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