Dear RG-Community,
for my PhD, I asked a drone company to capture multispectral imagery from a lemon myrtle plantation. Based on this imagery I defined different vegetation classes (Treated, Untreated, Shadow). The data was converted into reflectance using Agisoft Photoscan. Now, after plotting the data, it can be observed that the baseline for "Shadow" is different to those of the other two (shadow starts at ~10% reflectance while "Treated" and "Untreated" start at 40%). I assume that this might be caused by a flawed reflectance calibration (see attached image "normal"). Is there a valid way to adjust the spectra and still be able to use them for classification procedures? I thought that a SNV transformation might be helpful (see attached image "SNV").
Thank you for your help.
René
check this links maybe help you
Article The ASTER spectral library version 2.0
https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20000064520.pdf#page=65
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