The hydrological and mechanical behavior of soil is determined by the moisture content, soil water (matric) potential, fines content, and plasticity. However, these parameters are often difficult or impractical to determine in the field. Remote characterization of soil parameters is a non-destructive data collection process well suited to large or otherwise inaccessible areas. A ground-based, field-deployable remote sensor, called the soil observation laser absorption spectrometer (SOLAS), was developed to collect measurements from the surface of bare soils and to assess the in-situ condition and essential parameters of the soil. The SOLAS instrument transmits coherent light at two wavelengths using two, continuous-wave, near-infrared diode lasers and the instrument receives backscattered light through a co-axial 203-mm diameter telescope aperture. The received light is split into a hyperspectral sensing channel and a laser absorption spectrometry (LAS) channel via a multi-channel optical receiver. The hyperspectral channel detects light in the visible to shortwave infrared wavelengths, while the LAS channel filters and directs near-infrared light into a pair of photodetectors. Atmospheric water vapor is inferred using the differential absorption of the on- and off-line laser wavelengths (823.20 nm and 847.00 nm, respectively). Range measurement is determined using a frequency-modulated, self-chirped, coherent, homodyne detection scheme. The development of the instrument (transmitter, receiver, data acquisition components) is described herein. The potential for rapid characterization of physical and hydro-mechanical soil properties, including volumetric water content, matric potential, fines content, and plasticity, using the SOLAS remote sensor is discussed. The envisioned applications for the instrument include assessing soils on unstable slopes, such as wildfire burn sites, or stacked mine tailings. Through the combination of spectroradiometry, differential absorption, and range altimetry methodologies, the SOLAS instrument is a novel approach to ground-based remote sensing of the natural environment.

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The Garner and Coffman method was developed to design a proposed underground facility based on an allowable settlement profile; the method may also be used to characterize an unknown underground facility based on an observed surface settlement profile. The method uses both static methods and 2‐D finite element analyses to relate the characteristics of the ground surface settlement profile to the underground facility (depth, diameter, and number of tunnels). The calibration and validation of the Garner and Coffman method, as obtained by using tunnel segment data from historical tunneling projects (Bangkok, London, Taipei, Singapore, and Heinenoord), are presented. Specifically, the method was calibrated using settlement profiles and facility characteristics from 15 tunnel segments and validated using settlement profiles from 16 additional tunnel segments. A numerical relationship (developed during this research project) was then used during the validation of the model to predict facility characteristics for the “unknown” underground structures. The predicted depth and diameter for each of the “unknown” underground structures were within ten percent of the actual diameter and actual depth of the underground structure, as obtained from the literature. For all 16 validation tunnel segments, the tunnel location was predicted within one tunnel diameter of the actual facility centerline.

A single-polarization, vertical wave propagation transmitted-vertical wave propagation received (VV), terrestrial imaging radar and time domain reflectometry (TDR) equipment were used to monitor the fluctuations of water content within two thin (15.24 centimeters) compacted clay test sections (each 30.48-m long, by 15.34-m wide). Radar imagery was obtained in 2013 on March 22, June 26, July 7 and July 10 using a Gamma Remote Sensing Portable Radar Interferometer version II (GAMMA Remote Sensing and Consulting AG, Bern, Switzerland). In situ observations were acquired hourly using TDR probes. The background, methodology, and comparison of the results of the remote sensing and in situ measurements are presented. Specifically, two remote sensing data reduction algorithms were considered. The water content results obtained from these algorithms were compared with the water content values derived from correlations with the dielectric permittivity values measured by the TDR probes. Key findings include: 1) there were differences between the values obtained from the data reduction methods, 2) there were differences between the values obtained from the remote sensing methods and the values obtained from the in situ method, and 3) the identification of additional avenues of research. The remotely sensed measurements were, on average, higher than the in situ measurements (the average volumetric water content values were 0.2 and 0.5 depending on the method, as obtained via the remotely sensed methods; the average volumetric water content value in the compacted native soil test sections was 0.22, as obtained via the in situ method).