«Year: 1998 Endmember selection procedures for partial spectral unmixing of DAIS 7915 imaging spectrometer data in highly vegetated Areas Kneubühler, ...»
Values lower than 0 are excluded as well. These endmembers are used in a second unmixing step. This process can be repeated until a certain “purity-criteria” like no negative abundances or all abundances between 0 and 1 is achieved. Fig. 6 shows the differences between a one-step spectral unmixing of sugar beet and a two-step unmixing based on iteratively determined purer endmembers from imaging data.
FIGURE 6: One-step (left) and two-step (right) spectral unmixing of sugar beet, based on image derived endmembers The evaluated methods indicate that ground truth collection is important to validate the different approaches of endmember selection. Correlating ﬁeld measurements of biochemical and biophysical parameters to imaging data can offer the possibility to retrieve such parameters from imaging data. The approach using in-situ reference measurements of endmember spectra and the modelling approach using a SVAT Model may be more promising since image derived endmembers are made up of a spectral mixture of contributing elements, unless pure pixels are iteratively determined.
Nevertheless, it remains difﬁcult to deﬁne representative endmember spectra. Modelling endmember spectra bases on the availability of a range of parameters describing the status of the plant and the architecture of the canopy, which itself is subject to strong BRDF effects. Applications in vegetation studies have to take into account these effects, since airborne imaging spectrometers with large swath angles produce data of high geometric complexity.
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