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Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data

Department of Environmental Sciences, University of Virginia, 291 McCormick Road, Charlottesville, VA 22903, USA
Author to whom correspondence should be addressed.
Academic Editors: Sangram Ganguly, Compton Tucker, Randolph H. Wynne and Prasad S. Thenkabail
Remote Sens. 2015, 7(12), 16588-16606;
Received: 25 September 2015 / Revised: 24 November 2015 / Accepted: 27 November 2015 / Published: 8 December 2015
(This article belongs to the Special Issue Remote Sensing of Vegetation Structure and Dynamics)
Abandoned agricultural fields have recently become more abundant in the U.S. and remain susceptible to species invasions after cultivation disturbance. As invasive species become more widespread with increases in anthropogenic activities, we need more effective ways to use limited resources for conservation of native ecosystems. Remote sensing can help us monitor the spread and effects of invasive species, and thus determine the species and locations to target for conservation. To examine this potential, we studied plant communities dominated by exotic invasive plant species in secondary successional fields in northern Virginia using ground-level hyperspectral data. Within these communities, ordination analyses of vegetation surveys revealed differences in species compositions among plots and fields. These differences among communities were also observed in the spectral data. Stepwise multiple linear regression analyses to determine which species influenced the ordination axes revealed that many of the influential species are considered invasive, again underscoring the influence of invasive species on community properties. Stepwise regression analyses also revealed that the most influential wavelengths for discrimination were distributed along the spectral profile from the visible to the near-infrared regions. A discriminant analysis using wavelengths selected with a principal components analysis demonstrated that different plant communities were separable using spectral data. These spectrally observable differences suggest that we can use hyperspectral data to distinguish among invasive-dominated successional plant communities in this region. View Full-Text
Keywords: hyperspectral data; invasive species; successional fields hyperspectral data; invasive species; successional fields
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MDPI and ACS Style

Aneece, I.; Epstein, H. Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data. Remote Sens. 2015, 7, 16588-16606.

AMA Style

Aneece I, Epstein H. Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data. Remote Sensing. 2015; 7(12):16588-16606.

Chicago/Turabian Style

Aneece, Itiya, and Howard Epstein. 2015. "Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data" Remote Sensing 7, no. 12: 16588-16606.

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