A thorough review of available literature was conducted to inform of advancements in mobile LIDAR technology, techniques, and current and emerging applications in transportation. The literature review touches briefly on the basics of LIDAR technology followed by a more in depth description of current mobile LIDAR trends, including system components and software. An overview of existing quality control procedures used to verify the accuracy of the collected data is presented. A collection of case studies provides a clear description of the advantages of mobile LIDAR, including an increase in safety and efficiency. The final sections of the review identify current challenges the industry is facing, the guidelines that currently exist, and what else is needed to streamline the adoption of mobile LIDAR by transportation agencies. Unfortunately, many of these guidelines do not cover the specific challenges and concerns of mobile LIDAR use as many have been developed for airborne LIDAR acquisition and processing. From this review, there is a lot of discussion on "what" is being done in practice, but not a lot on "how" and "how well" it is being done. A willingness to share information going forward will be important for the successful use of mobile LIDAR.

Field geology has traditionally relied on two-dimensional, paper-based workflows. Although digital mapping techniques are rapidly replacing paper ones, three-dimensional (3-D) terrain models and 3-D visualizations have the potential to revolutionize field studies, yet to date, few studies have embraced this technology. The development of structure-from-motion (SfM) photogrammetry has allowed routine production of high-resolution terrain models from a series of photographs taken at arbitrary angles using "multiview stereo" (MVS) software. However, few studies have applied the MVS approach outside of specific, highly controlled field environments that are easily accessible. In this study, we examine methods for ad hoc application of ground-based MVS in remote field areas with large-scale (>2 km 2) multifaceted topography and complex geology. Specifically, we emphasize methods that could be employed in a typical geologic field study without the use of specialized equipment beyond a camera, and we identify various pitfalls that can be avoided during this type of work. We present several scenarios that illustrate the different ways that MVS can be implemented in the field. These scenarios vary with respect to: (1) the manner in which ground control points (GCPs) are collected and distributed; (2) the baseline-to-distance ratio of the imagery; (3) the number of photographs taken; and (4) the type of camera used. Each scenario yields 3-D terrain models from which plane orientations can be extracted and upon which 3-D linework can be drawn. We caution that if absolute accuracythe difference between the location of the objects on the model and their true position on a geodetic coordinate system-is critical to a project, then great care must be taken in using MVS models obtained solely from ground-based photographs because several factors can contribute to spatial errors as large as hundreds of meters over scales of a few square kilometers. The two primary factors that contribute to these significant spatial errors in MVS models are (1) the distribution and positional accuracy of GCPs and (2) the baseline-to-distance ratio. Nonetheless, MVS is a tool that can easily be applied to any field study regardless of terrain complexity, scale, or accessibility, and it has the potential to revolutionize field studies, particularly in areas with steep terrain.

Radar instruments have been widely used to measure snow water equivalent (SWE) and Interferometric Synthetic Aperture Radar is a promising approach for doing so from spaceborne platforms. Electromagnetic waves propagate through the snowpack at a velocity determined by its dielectric permittivity. Velocity estimates are a significant source of uncertainty in radar SWE retrievals, especially in wet snow. In dry snow, velocity can be calculated from relations between permittivity and snow density. However, wet snow velocity is a function of both snow density and liquid water content (LWC); the latter exhibits high spatiotemporal variability, there is no standard observation method, and it is not typically measured by automated stations. In this study, we used ground-penetrating radar (GPR), probed snow depths, and measured in situ vertically-averaged density to estimate SWE and bulk LWC for seven survey dates at Cameron Pass, Colorado (~3120 m) from April to June 2019. During this cooler than average season, median LWC for individual survey dates never exceeded 7 vol. %. However, in June, LWC values greater than 10 vol. % were observed in isolated areas where the ground and the base of the snowpack were saturated and therefore inhibited further meltwater output. LWC development was modulated by canopy cover and meltwater drainage was influenced by ground slope. We generated synthetic SWE retrievals that resemble the planned footprint of the NASA-ISRO L-band InSAR satellite (NISAR) from GPR using a dry snow density model. Synthetic SWE retrievals overestimated observed SWE by as much as 40% during the melt season due to the presence of LWC. Our findings emphasize the importance of considering LWC variability in order to fully realize the potential of future spaceborne radar missions for measuring SWE.