## 4 Results
Multispectral green vegetation and dark EMs are generalizable globally with spectral shapes consistent with physical and biological properties. However, as has been noted in numerous previous studies (e.g., [16; 17; 18]), rock, sediment, and soil substrates demonstrate a diversity of spectral shapes. Local substrate EMs are generally used for more accurate spectral unmixing results because they can take into account this regional pedologic and geologic diversity. These EMs can be selected directly from the spectral feature space. For comparison with pure substrate EMs spanning a wider range of rocks and soils than that found in the study area, we rendered a spectral feature space from laboratory spectra of rock and soil samples. Using the Johns Hopkins University (JHU) spectral library, we compiled 161 laboratory rock and soil reflectance spectra. The spectra span a wide range of soil and rock types, including 67 igneous rocks, 55 metamorphic rocks, 14 sedimentary rocks, and 25 soils. PCA of the JHU substrate spectra reveals the first three dimensions account for 85.8%, 10.5%, and 2.2%, respectively. The first three dimensions thus account for over 96% of the overall variance of this diverse library of substrate spectra. The spectral feature space in Figure 6 shows that the 25 soils cluster in a relatively confined subset of this substrate space. The soil spectra are observed to deviate from each other in much less pronounced ways than rocks vary both within and between the igneous, metamorphic, and sedimentary classes. Given the dominance of agricultural land cover in our study area, it is this relatively narrow range of soil spectra which we would expect to dominate as the substrate EM in our Landsat-AVIRIS analysis. The range of substrate EMs actually present in this analysis is shown in Figure 7. In order to clearly identify these substrate EMs, the fourth dimension of the spectral feature space is used. While accounting for less than 2% of the total variance in either dataset, PC 4 proves to be useful in this case for distinguishing between the shapes of soil and rock spectra. Figure 6: _Cont._  
Six substrate EMs are identified from the PC 1 vs. 4 projection of the feature space. The clear visual similarity in feature space topologies and EM spectra between the hyperspectral and multispectral datasets continues through the fourth dimension. This similarity is unsurprising given the dominance of the spectral continuum (rather than narrowband or broadband absorption features) in the reflectance spectra of these soil EMs. Each EM corresponds to a spatial cluster of points in a bare (or senescent) agricultural field or a spatially extensive sedimentary deposit. The locations of the EMs are indicated on both the feature space and the false color composite of the flight line subsets. USDA-NCCSS soil survey data were acquired for the location of each spectral EM using the California Soil Resource Lab SoilWeb browser ([[https://casoilresource.lawr.ucdavis.edu/gmap/](https://casoilresource.lawr.ucdavis.edu/gmap/)]([https://casoilresource.lawr.ucdavis.edu/gmap/](https://casoilresource.lawr.ucdavis.edu/gmap/))). The map unit name is given for each EM (e.g., Clear Lake Clay), as well as its order (e.g., Vertisol) and suborder (e.g., Aquerts). Figure 6: Spectral feature space and endmembers for the rock and soil substrate spectra from the JHU spectral library. Visible/NIR/SWIR false color composite (**top**) gives some indication of the spectral diversity in three principal wavebands. Three orthogonal projections of the spectral feature space (**bottom**), along with example endmember spectra from the periphery of the space, illustrate the broad diversity of metamorphic spectra compared to the more continuous soil spectra. Notably, the spectral properties of the continuum of substrate EMs appear to correspond to a continuum of soil grain sizes and textures. The soil at EM 1 is classified as a Clay, with surface composition of the dominant series (Clear Lake) of roughly 60% clay and 15% sand.