Imaging Science Ph.D. Defense: Dylan Shiltz
Ph.D. Dissertation Defense
Radiometric Effects of Centimeter Scale Roughness of Bare Soils
Dylan J. Shiltz
Imaging Science Ph.D. Candidate
Chester F. Carlson Center for Imaging Science, RIT
Abstract:
The roughness of a bare soil surface has important implications in both the reflective and microwave domains of remote sensing. In a natural environment, roughness is present at a wide range of length scales, from the roughness of individual particles to meter or kilometer scale geological features. This thesis will focus on centimeter scale roughness, i.e. surface features whose length scale is much greater than individual soil particles, but which are still small enough that they are unresolved in remote sensing applications. Wind-driven and hydrologically-driven features, such as the ripples found on a beach or on the surfaces of sand dunes, exist at this length scale. Since these features are often unresolved in both reflective and microwave remote sensing imagery, it is important to understand their radiometric effects such that their contribution may be distinguished and accounted for in the two domains. This thesis consists of two primary research efforts. In the first section, a reflective domain roughness model used widely in the astronomy community is analyzed, and an improved version is proposed that more accurately models the shadowing and tilt effects introduced by the roughness. Laboratory measurements of rough surface reflectance indicate that the proposed model is a significant improvement over the existing model. In the second section, several existing microwave scattering models are applied in an attempt to retrieve roughness and moisture estimates from bare soil using a commercial X-band SAR constellation. Commercial SAR platforms typically utilize only a single wavelength and single polarization, but are able to image sites from multiple incidence angles with short revisit times. The objective is to determine whether the moisture and roughness inversion can be performed using such multi-angular imagery when more advanced polarimetric or multi-frequency platforms are not available.
Intended Audience:
Undergraduates, graduates, and experts. Those with interest in the topic.
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