Beyond Abiraterone solubility the wide application of VISNIR remote sensing for the determination of different soil properties, the electromagnetic ranges considered optimal for the determination of different properties has varied. Using a spectral range of 1,300 to 2,500 nm, Chang et al. found a high correlation between predicted values of total C, N, moisture and other soil properties [14]. Krishman et al. utilized the visible part of the electromagnetic spectrum using bands 0.6236 and 0.5644 ��m to predict organic matter and obtained a maximum R2 value of 0.98 which they found better than using the Near Infrared (NIR) region which yielded a maximum R2 of 0.87 [15].
Classification and regression trees (CART) within R have been used for ecological applications including, for example, relating soil properties with lead levels [16], explaining woody cover influenced by precipitation in Africa [17], modeling of forest productivity using remote sensing [18], and other ecological modeling which linear regressions fail to fully characterize [19].Addressing a need to quantify landscape-level soil productivity, this study expanded upon previous research by utilizing new remote sensing technologies and statistical models. Observation of terrestrial conditions such as soil properties allows for the indexing of potential below-ground productivity, carbon sequestration or other applications through the analysis of soil spectra. Within this context sampling of soils within Washington and Oregon was conducted to establish a correlation between analyzed soil spectra and their specific soil properties.
Characterization of soil samples were analyzed using traditional laboratory analytical methods and also spectrally analyzed in the electromagnetic range of 400 to 1,000 nm. The following questions were examined for this study:What are the variations of soil spectra? Is there variation within GSK-3 the soil samples that allows differentiation between selleck chem Seliciclib different soil series or within series?What effect does different concentrations of nitrogen, carbon, carbonate and organic matter have on the spectral signature of the soil samples?Can regression trees be used to model the carbon, nitrogen, organic matter and carbonate concentrations from soil spectra and chemical laboratory reference measurements?2.?Experimental SectionUsing selected soil samples obtained from locations within Washington and Oregon, the methodology outlined in the following sections was used to create prediction models for concentrations of total nitrogen, total carbon, carbonate carbon and organic matter.

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