|Institution:||The Ohio State University|
|Keywords:||Electrical Engineering; Electromagnetics; Remote Sensing|
|Full text PDF:||http://rave.ohiolink.edu/etdc/view?acc_num=osu1437587673|
Remote sensing of soil moisture has become a topic of increasing interest over the past several decades. Mapping of soil moisture content is a critical element in meteorological modeling, agricultural planning, disease spread monitoring, flood/landslide risk evaluation, studies of the Earth's water and carbon cycles, and many other environmental issues. The remote sensing of surface soil moisture conditions is necessary for fostering these large-scale studies in which deployment of in-situ soil moisture sampling networks (e.g. via dielectric probes) is not possible or economically feasible. While remote sensing soil moisture from radiometric measurements has a long history, the subject of inverting soil moisture from radar measurements (particularly in the presence of vegetation) is a difficult problem which remains the subject of active research.Due to the relatively high dielectric constant of water (e.g. when compared to soil), the normalized radar cross section of soil has been found to be particularly sensitive to soil moisture content. Synthetic Aperture Radar (SAR) is particularly attractive for soil moisture remote sensing, given SAR's capability to form images of the Earth's surface at high spatial resolutions when compared to passive approaches such as radiometry. L-band frequencies are of particular interest due to their low susceptibility to atmospheric effects, their ability to penetrate through vegetation (and sense the underlying soil surface), and their high sensitivity to changes in soil moisture.This dissertation focuses on the inversion of soil moisture from radar returns using airborne and space borne instruments. The inversion techniques discussed herein specifically include change-detection-based and forward-model-based methods. Chapter 1 provides the introduction to this dissertation, including motivations and a brief history of soil moisture remote sensing using radar. Chapter 2 describes the use of bistatic radar configurations (where the transmitter and receiver are not co-located) and discusses bistatic, polarimetric normalized radar cross section (NRCS) predictions from randomly rough surfaces using several approximate and numerically exact models. Chapter 3 describes the use of single- and two-layer rough surface scattering to explain airborne interferometric SAR (InSAR) decorrelations observed for bare soil surfaces. Chapter 4 presents a simulation study of the use of a compact polarimetric radar mode, its advantages for use in soil moisture remote sensing, and its performance in comparison to a traditional, fully-polarimetric system. Chapter 5 introduces a new time-series soil moisture retrieval method, tailored for use with the Soil Moisture Active/Passive (SMAP) radar system, and discusses results from this method using simulated and measured data. Chapter 6 explains recent advances in the detection of inland water bodies using the SMAP radar. The culmination of the research described herein aims to benefit current and future soil moisture remote sensing radar systems. Advisors/Committee Members: Johnson, Joel (Advisor).