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Seasonal NDVI trajectories in response to disturbance: toward a spectral-temporal mixing model for tallgrass prairie

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2 Author(s)
Goodin, D.G. ; Dept. of Geogr., Kansas State Univ., Manhattan, KS, USA ; Henebry, G.

Natural and anthropogenic disturbance in tallgrass prairie communities can induce changes in plant species composition, including shifts in abundance of C3 vs. C4 lifeforms. The asynchronous seasonalities in greenness that C3 and C4 species exhibit should enable monitoring of their relative abundance using sensor derived vegetation indices, such as NDVI. The authors used close-range measurements made over 22 experimental. Plots at the Konza Prairie Research Natural Area (KPRNA) to evaluate seasonal trajectories in canopy greenness as a function of C3/C4 ratio. NDVI data were collected from each plot at approximately ten day intervals throughout the 1995 growing season. Temporal trajectories were used to develop discriminant functions to model relative C3/C4 abundances. The discriminant model yielded values of Kendall's τb and Cohen's κ statistic of 0.794 and 0.781, indicating strong agreement between classes and an overall classification significantly better than random assignment. Results suggest the possibility of applying spectral-temporal mixture models derived from close-range sensing to larger scale monitoring of tallgrass prairie

Published in:

Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International  (Volume:1 )

Date of Conference:

27-31 May 1996