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. In the reflective domain, centimeter scale features can be described by geometric optics. The roughness of a surface introduces several new mechanisms of scattering in addition to the ones already present in a smooth surface. These mechanisms include: i) shadowing of portions of the surface (from both the light source and the observer’s position), ii) tilting of the visible portions of the surface, and iii) multi-facet scattering from one point on the surface to another (also called inter-facet scattering). In the microwave domain, there is an additional mechanism at play due to the coherent illumination and longer wavelengths used in active microwave remote sensing. The centimeter scale features create a series of reflected waves which constructively and destructively interfere with each other. At X-band (λ≈3 cm), geometric optics is no longer valid, and roughness features on this length scale will introduce a significant coherent contribution. This effect can be modeled analytically via the power spectral density of the surface statistics, or simply through empirical relationships. This thesis consists of two primary research efforts. In the first chapter, I analyze a widely used macroscopic roughness model for the reflective domain and propose an improved version. The proposed model more accurately describes single-facet scattering, while also accounting for the effects of multi-facet scattering via an empirical approximation. I performed extensive laboratory measurements of rough mineral surfaces to assess the performance of the proposed model and to compare it with the existing model. In the second chapter, I apply several existing microwave scattering models in an attempt to retrieve roughness and moisture estimates from bare soil using a commercial X-band synthetic aperture radar (SAR) constellation. Typically, to perform moisture and roughness inversions, multiple SAR images are used at different frequencies and/or polarizations. However, most of the commercial SAR constellations utilize only a single frequency, typically X-band, and a single polarization. These constellations consist of multiple spacecraft in complementary orbits, and their numbers continue to grow every year. Therefore, obtaining multi-angular SAR imagery of a site will become increasingly achievable. It is important to assess the degree to which the multi-angular imagery of commercial X-band platforms may be used to estimate moisture and roughness when more advanced polarimetric or multi-band platforms are not available.

Library of Congress Subject Headings

Earth sciences--Remote sensing; Soils--Remote sensing; Multisensor data fusion; Synthetic aperture radar

Publication Date

9-18-2022

Document Type

Dissertation

Student Type

Graduate

Degree Name

Imaging Science (Ph.D.)

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)

Advisor

Charles M. Bachmann

Advisor/Committee Member

David Ross

Advisor/Committee Member

Carl Salvaggio

Comments

This dissertation has been embargoed. The full-text will be available on or around 11/1/2023.

Campus

RIT – Main Campus

Plan Codes

IMGS-PHD

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