The capability to map anthropogenic aerosol quantities and properties over land can provide significant insights for climate and environmental studies on global and regional scales. One of the primary challenges in aerosol information monitoring is separating two signals measured by downward-viewing airborne or spaceborne instruments: the light scattered from the aerosols and light reflected from the Earth's surface. In order to study the aerosols independently, the surface signal needs to be subtracted out from the measurements. Some observational modalities, such as multispectral and multiangle, do not provide enough information to uniquely define the Earth's directional reflectance properties for this task due to the high magnitude and inhomogeneity of albedo for land surface types. Polarization, however, can provide additional information to define surface reflection. To improve upon current measurement capabilities of aerosols over urban areas, Jet Propulsion Laboratory developed the Multiangle SpectroPolarimetric Imager (MSPI) that can accurately measure the Degree of Linear Polarization to 0.5%. In particular, data acquired by the ground-based prototype, GroundMSPI, is used for directional reflectance studies of outdoor surfaces in this dissertation. This work expands upon an existing model, the microfacet model, to characterize the polarized bidirectional reflectance distribution function (pBRDF) of surfaces and validate an assumption, the Spectral Invariance Hypothesis, on the surface pBRDF that is used in aerosol retrieval algorithms. The microfacet model is commonly used to represent the pBRDF of Earth's surface types, such as ocean and land. It represents a roughened surface comprised of randomly oriented facets that specularly reflect incoming light into the upward hemisphere. The analytic form of the pBRDF for this model assumes only a single reflection of light from the microfaceted surface. If the incoming illumination is unpolarized, as it is with natural light from the Sun, the reflected light is linearly polarized perpendicular to the plane that contains the illumination and view directions, the scattering plane. However, previous work has shown that manmade objects, such as asphalt and brick, show a polarization signature that differs from the single reflection microfacet model. Using the polarization ray-tracing (PRT) program POLARIS-M, a numerical calculation for the pBRDF is made for a roughened surface to account for multiple reflections that light can experience between microfacets. Results from this numerical PRT method shows rays that experience two or more reflections with the microfacet surface can be polarized at an orientation that differs from the analytical single reflection microfacet model. This PRT method is compared against GroundMSPI data of manmade surfaces. An assumption made regarding the pBRDF for this microfacet model is verified with GroundMSPI data of urban areas. This is known as the Spectral Invariance Hypothesis and asserts that the magnitude and shape of the polarized bidirectional reflectance factor (pBRF) is the same for all wavelengths. This simplifies the microfacet model by assuming some surface parameters such as the index of refraction are spectrally neutral. GroundMSPI acquires the pBRF for five prominent region types, asphalt, brick, cement, dirt, and grass, for day-long measurements on clear sky conditions. Over the course of each day, changing solar position in the sky provides a large range of scattering angles for this study. The pBRF is measured for the three polarimetric wavelengths of GroundMSPI, 470, 660, and 865nm, and the best fit slope of the spectral correlation is reported. This investigation shows agreement to the Spectral Invariance Hypothesis within 10% for all region types excluding grass. Grass measurements show a large mean deviation of 31.1%. This motivated an angle of linear polarization (AoLP) analysis of cotton crops to isolate single reflection cases, or specular reflections, from multiple scattering cases of light in vegetation. Results from this AoLP method show that specular reflections off the top surface of leaves follow the Spectral Invariance Hypothesis.