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Monitoring unstable slopes with terrestrial laser scanning (TLS) has been proven effective. However, end users still struggle immensely with the efficient processing, analysis, and interpretation of the massive and complex TLS datasets. Two recent advances described in this paper now improve the ability to work with TLS data acquired on steep slopes. The first is the improved processing of TLS data to model complex topography and fill holes. This processing step results in a continuous topographic surface model that seamlessly characterizes the rock and soil surface. The second is an advance in the automated interpretation of the surface model in such a way that a magnitude and frequency relationship of rockfall events can be quantified, which can be used to assess maintenance strategies and forecast costs. The approach is applied to OPEN ACCESSRemote Sens. 2015, 7 12104 unstable highway slopes in the state of Alaska, U.S.A. to evaluate its effectiveness. Further, the influence of the selected model resolution and degree of hole filling on the derived slope metrics were analyzed. In general, model resolution plays a pivotal role in the ability to detect smaller rockfall events when developing magnitude-frequency relationships. The total volume estimates are also influenced by model resolution, but were comparatively less sensitive. In contrast, hole filling had a noticeable effect on magnitudefrequency relationships but to a lesser extent than modeling resolution. However, hole filling yielded a modest increase in overall volumetric quantity estimates. Optimal analysis results occur when appropriately balancing high modeling resolution with an appropriate level of hole filling.

In this paper, we introduce the Rockfall Activity Index (RAI), a point cloud-derived, high-resolution, morphology-based approach for assessing rockfall hazards. With the RAI methodology, rockfall hazards are evaluated in a two-step procedure. First, morphological indices (local slope and roughness) are used to classify mass wasting processes acting on a rockslope. These classifications are then used with estimated instability rates to map rockfall activity across an entire slope face. The rockfall hazard is quantified as the estimated annual kinetic energy produced by rockfall along 1-m length segments of a slope face. Field assessment of the RAI method at multiple study sites indicates that the morphology-derived classification and hazard assessment routines provide results that closely match the observed behavior and performance of rock slopes.

Ground surveys and remote sensing are integral to establishing fair and equitable property valuations necessary for real property taxation. The International Association of Assessing Officers (IAAO) has embraced aerial and street-view imaging as part of its standards related to property tax assessments and audits. New technologies, including unmanned aerial systems (UAS) paired with imaging sensors, will become more common as local governments work to ensure their cadastre and tax rolls are both accurate and complete. Trends in mapping technology have seen an evolution in platforms from large, expensive manned aircraft to very small, inexpensive UAS. Traditional methods of photogrammetry have also given way to new equipment and sensors: digital cameras, infrared imagers, light detection and ranging (LiDAR) laser scanners, and now synthetic aperture radar (SAR). At the University of Alaska Fairbanks (UAF), we work extensively with unmanned aerial systems equipped with each of these newer sensors. UAF has significant experience flying unmanned systems in the US National Airspace, having begun in 1969 with scientific rockets and expanded to unmanned aircraft in 2003. Ongoing field experience allows UAF to partner effectively with outside organizations to test and develop leading-edge research in UAS and remote sensing. This presentation will discuss our research related to various sensors and payloads for mapping. We will also share our experience with UAS and optical systems for creating some of the first cadastral surveys in rural Alaska.

This study examines three sites in Alaska with unstable rock slopes that were surveyed using both terrestrial laser scanning (TLS) and structure-from-motion (SfM) techniques. The datasets were acquired simultaneously and linked to a rigorous survey control network. An accuracy evaluation of the SfM-derived surface models was performed using the TLS data and numerous reflectorless total station observations collected across the rock slopes. A quality evaluation was conducted to examine differences in point density, model completeness and distributions of morphological properties between the SfM and TLS datasets. The results indicate that SfM is a viable option for unstable rock-slope assessment when a sufficient number of images with adequate overlap are acquired and the reconstruction is tied to a survey control network. The best results, in terms of accuracy and completeness, were achieved when combining both unmanned aerial vehicle (UAV) and terrestrial imagery for the SfM reconstruction. However, issues such as over-smoothing and geometric inconsistencies bring into question the suitability of SfM for the detection of small changes over time. 220were uplifted and sequentially eroded. The highway follows the glacial cut into the Chickaloon Formation; however, no other glacial evidence can be found in the area. Regions of the Matanuska Formation exposed in road cuttings along the Glenn Highway largely consist of dark mudstones while Chickaloon Formation outcrops mainly consist of carbonaceous siltstone, coal and sandstone (Trop et al., 2015).Three independent sites were selected for this study (Fig. 2):RS1. Rock-Slope 1 (RS1, at Glenn Highway milepost 71) is a nearly vertical (70°to 90°) road cutting approximately 50 to 60 m high and 140 m wide. It is composed of wellindurated dark mudstone of the Matanuska Formation. RS2. Rock-Slope 2 (RS2, milepost 85Á5) is a 60°road cutting approximately 8 to 10 m high and 40 m wide. RS2 consists of highly fractured, fine-to-medium grained, moderately weathered grey-and-tan hard sandstone of the Chickaloon Formation. The fractures are oriented such that the sandstone is broken into cobble-sized blocks. Fig. 2. SfM-derived 5 cm surface models of the three rock slopes (RS1, RS2 and RS3) with the layout of black-and-white targets used as ground control points (GCPs). Note the three different scales.