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Separability of maize and soybean in the spectral regions of chlorophyll and carotenoids using the Moment Distance Index

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We introduce a new framework for analyzing spectra called Moment Distance that uses metrics derived from the shape of the curve described by fine resolution spectra. We locate potential pivot wavelength regions (PWR) useful for estimation of chlorophyll and carotenoids, and explore the spectral separability of maize (Zea mays L.) and soybean (Glycine max (L.) Merr.) at specific PWRs. We find the Moment Distance Index (MDI) to perform as well as or better than optimized band ratio models in terms of bias and RMSE. The 720-730 nm PWR for chlorophyll and 450-500 nm PWR for carotenoids are not only sensitive to pigment concentrations, but could distinguish maize spectra from soybean spectra. The separability of the spectra appears as the absence of crossings that define the maximal spectral shape difference. The larger the difference, the more the maize MDI can be distinguished from the soybean MDI. MDI yields significantly different linear models (p < 0.05) for retrieval of chlorophyll from maize and soybean. What we present here works at the leaf level. Next, we need to investigate MDI performance at canopy, field, and landscape scales, especially with imaging spectrometer data containing both pure and mixed spectra.

Affiliations: 1: Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, Brookings


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