Spectral resampling based on user-defined inter-band correlation filter: C3 and C4 grass species classification

31Citations
Citations of this article
30Readers
Mendeley users who have this article in their library.

Abstract

In this paper, a user-defined inter-band correlation filter function was used to resample hyperspectral data and thereby mitigate the problem of multicollinearity in classification analysis. The proposed resampling technique convolves the spectral dependence information between a chosen band-centre and its shorter and longer wavelength neighbours. Weighting threshold of inter-band correlation (WTC, Pearson's r) was calculated, whereby r = 1 at the band-centre. Various WTC (r = 0.99, r = 0.95 and r = 0.90) were assessed, and bands with coefficients beyond a chosen threshold were assigned r = 0. The resultant data were used in the random forest analysis to classify in situ C3 and C4 grass canopy reflectance. The respective WTC datasets yielded improved classification accuracies (kappa = 0.82, 0.79 and 0.76) with less correlated wavebands when compared to resampled Hyperion bands (kappa = 0.76). Overall, the results obtained from this study suggested that resampling of hyperspectral data should account for the spectral dependence information to improve overall classification accuracy as well as reducing the problem of multicollinearity. © 2012 Elsevier B.V.

Cite

CITATION STYLE

APA

Adjorlolo, C., Mutanga, O., Cho, M. A., & Ismail, R. (2012). Spectral resampling based on user-defined inter-band correlation filter: C3 and C4 grass species classification. International Journal of Applied Earth Observation and Geoinformation, 21(1), 535–544. https://doi.org/10.1016/j.jag.2012.07.011

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free