In order to assess the influence of litter cover on soil background spectral response, trays of dry Lehmann Lovegrass (Eragrostis lehmanniana) were used at three different densities (635, 1015, 2815 Kg/ha) over three different soil backgrounds (Whitehouse sandy clay loam, Superstition sand, and Cloversprings loam). After analysis, spectral measurements made with a Barnes Multi-Modular Radiometer revealed that, soil-litter mixtures exhibit an oil like spectral behavior in the (0.45-2.30 m) waveband range. Mulched soils could not be discriminated from bare soils solely on the basis of the spectral response. However, mulched and bare soil spectral responses differed in amplitude depending on the difference in brightness between the bare soil and the litter cover. In addition, the results showed that while an increase of litter cover density on the soil surface decreased RVI, NDVI and PVI predicted greenness, it increased the GVI based greenness for all soils except the Superstition sand where the GVI showed a reversed trend. The PVI increased at low and intermediate litter densities and decreased at higher ones for the Superstition sand.

<p> The ionospheric total electron content (TEC) is the integrated electron density across a unit area. TEC is an important property of the ionosphere. Accurate estimation of TEC and TEC spatial distributions are needed for many space-based applications such as precise positioning, navigation, and timing. The Global Positioning System (GPS) provides one of the most versatile methods for measuring the ionosphere TEC, as it has global coverage, high temporal resolution, and relatively high spatial resolution. The objective of this thesis is to develop an algorithm for accurate estimation of the TEC using dual-frequency GPS receiver measurements and simultaneously estimate the receiver hardware bias in order to mitigate its effect on the TEC. This method assumes the TEC in the portion of sky visible to the receiver can be represented as a two dimensional sheet with an absolute value and spacial gradients with respect to latitude and longitude. A code-phase multipath noise estimation algorithm is integrated with the TEC estimation process to mitigate environmental multipath contamination of the measurements. The integrated algorithm produces an approximate map of local TEC using a single dual-frequency receiver while minimizing both multipath induced errors and the receiver hardware bias. The goal of this method is to provide an accurate map of the ionosphere TEC, in the region local to the receiver, without the need for a network of receivers and in the absence of knowledge of the receiver hardware induced bias. This thesis describes the algorithm, its implementation, and attempts to validate the method through comparison with incoherent scatter radar (ISR) data from low, mid, and high latitude locations.</p>

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The role of clouds in reflecting solar radiation to space and thereby reducing surface heating is of critical importance to climate. Combustion processes that produce greenhouse gases also increase cloud condensation nuclei (CCN) concentrations which in turn increase cloud drop concentrations and thereby cloud albedo. A calculation of cloud susceptibility, defined in this work as the increase in albedo resulting from the addition of one cloud drop per cubic centimeter (as cloud liquid water content remains constant), is made through satellite remote sensing of cloud drop radius and optical thickness. The remote technique uses spectral channels of the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA polar orbiting satellites. Radiative transfer calculations of reflectance and effective surface and cloud emissivities are made for applicable sun and satellite viewing angles, including azimuth, at various radii and optical thicknesses for each AVHRR channel. Emission in channel 3 (at 3.75 μm) is removed to give the reflected solar component. These calculations are used to infer the radius and optical thickness giving the best match to the satellite measurements. The effect of the atmosphere on the signal received by the satellite is included in the analysis. Marine stratus clouds are a focus of this work. As well as being important modifiers to climate, they are cleaner than continental clouds and so likely to be of higher susceptibility. Analysis of several stratus scenes, including some containing ship tracks, supports this expectation.