Discrimination of hoary cress and determination of its detection limits via hyperspectral image processing and accuracy assessment techniques

By Jacob T. Mundt, N. Glenn, K. Weber, T. Prather, L. Lass, Jeffrey Pettingill. 2005

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A meta-analysis of remote sensing research on supervised pixel-based land-cover image classification processes: General guidelines for practitioners and future research (2016, unknown): “, 2005; Fauvel, Benediktsson, Chanussot, & Sveinsson, 2008) andMinimum Noise Fraction (MNF) (Mundt et al., 2005; Yang, Everitt, & Johnson, 2009)were themost common techniques of dimensionality reduction observed in the reviewed articles.”
Habitat suitability modelling of an invasive plant with advanced remote sensing data (2009, background): “…Ge et al., 2006) and hyperspectral image data (e.g. Parker Williams & Hunt, 2002; Underwood et al., 2003; Asner & Vitousek, 2005; Lass et al., 2005; Mundt et al., 2005; Lawrence et al., 2006; Cheng et al., 2007; Hamada et al., 2007; Hestir et al., 2008; Noujdina & Ustin, 2008) for mapping the…”
Mapping invasive plants using hyperspectral imagery and Breiman Cutler classifications (RandomForest) (2006, background): “…al., 2000), undesirable woody vegetation encroaching into grasslands in the Niobrara Valley (Wylie et al., 2000), flowering leafy spurge in northeastern Wyoming (Parker Williams & Hunt, 2002, 2004), flowering leafy spurge in Idaho (Glenn et al., 2005), and hoary cress in Idaho (Mundt et al., 2005).”