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1. Structure-from-Motion based 3D mapping of landslides & fault rupture sites during 2016 Kaikoura earthquake reconnaissance

   Zekkos, D. ( June 2018 , 11th US National Conference on Earthquake Engineering)

   Following the November 14 2016 Mw7.8 Kaikoura earthquake, field expeditions were undertaken using Unmanned Aerial Vehicles (UAVs) to map 25 sites of scientific interest with a plan area of 7.2 km2. A total of 23,172 images collected by the UAVs were used as input in Structure-from-Motion (SfM) to create 3D models of the target areas with a focus on landslides and fault rupture. Two sites are presented in more detail as examples of the data generated; a section of the Kekerengu fault that ruptured during the earthquake, and the Limestone Hills landslide. The sites were mapped at high resolution with ground sampling distance that varied from 0.5 to 7.0 cm/pixel. The developed SfM models were compared to 1-m aerial LiDAR data and the results were found to be comparable. However, the higher resolution of the SfM digital surface model (DSM), paired with the imagery facilitated more detailed interpretations, highlighting the usefulness of the UAV-enabled SfM as a mobile and effective technique for documenting perishable post-earthquake reconnaissance data. 

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2. Reconstructing Digital Terrain Models from ArcticDEM and WorldView-2 Imagery in Livengood, Alaska

   https://doi.org/10.3390/rs15082061  

   Zhang, Tianqi ; Liu, Desheng ( April 2023 , Remote Sensing)

   ArcticDEM provides the public with an unprecedented opportunity to access very high-spatial resolution digital elevation models (DEMs) covering the pan-Arctic surfaces. As it is generated from stereo-pairs of optical satellite imagery, ArcticDEM represents a mixture of a digital surface model (DSM) over a non-ground areas and digital terrain model (DTM) at bare grounds. Reconstructing DTM from ArcticDEM is thus needed in studies requiring bare ground elevation, such as modeling hydrological processes, tracking surface change dynamics, and estimating vegetation canopy height and associated forest attributes. Here we proposed an automated approach for estimating DTM from ArcticDEM in two steps: (1) identifying ground pixels from WorldView-2 imagery using a Gaussian mixture model (GMM) with local refinement by morphological operation, and (2) generating a continuous DTM surface using ArcticDEMs at ground locations and spatial interpolation methods (ordinary kriging (OK) and natural neighbor (NN)). We evaluated our method at three forested study sites characterized by different canopy cover and topographic conditions in Livengood, Alaska, where airborne lidar data is available for validation. Our results demonstrate that (1) the proposed ground identification method can effectively identify ground pixels with much lower root mean square errors (RMSEs) (<0.35 m) to the reference data than the comparative state-of-the-art approaches; (2) NN performs more robustly in DTM interpolation than OK; (3) the DTMs generated from NN interpolation with GMM-based ground masks decrease the RMSEs of ArcticDEM to 0.648 m, 1.677 m, and 0.521 m for Site-1, Site-2, and Site-3, respectively. This study provides a viable means of deriving high-resolution DTM from ArcticDEM that will be of great value to studies focusing on the Arctic ecosystems, forest change dynamics, and earth surface processes. 

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3. Phased Reconnaissance Approach to Documenting Landslides following the 2016 Central Italy Earthquakes

   https://doi.org/10.1193/082117EQS165M  

   Franke, Kevin W. ; Lingwall, Bret N. ; Zimmaro, Paolo ; Kayen, Robert E. ; Tommasi, Paolo ; Chiabrando, Filiberto ; Santo, Antonio ( November 2018 , Earthquake Spectra)

   The 2016 Central Italy earthquake sequence caused numerous landslides over a large area in the Central Apennines. As a result, the Geotechnical Extreme Events Reconnaissance Association (GEER) organized post-earthquake reconnaissance missions to collect perishable data. Given the challenging conditions following the earthquakes, the GEER team implemented a phased reconnaissance approach. This paper illustrates this approach and how it was used to document the largest and most impactful seismically induced landslides. This phased approach relied upon satellite-based interferometric damage proxy maps, preliminary published reports of observed landslides, digital imaging from small unmanned aerial vehicles (UAVs), traditional manual observations, and terrestrial laser scanning. Data collected from the reconnoitered sites were used to develop orthophotos and meshed three-dimensional digital surface models. These products can provide valuable information such as accurate measurements of landslide ground movements in complex topographic geometries or boulder runout distances from rock falls. The paper describes three significant landslide case histories developed and documented with the phased approach: Nera Valley, Village of Pescara del Tronto, and near the villages of Crognaleto and Cervaro. 

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4. Potential Future Lake Drainage for the Western Arctic Coastal Plain in northern Alaska from an Interferometric Synthetic Aperture Radar (IFSAR)-Derived Digital Surface Model, 2002-2003

   https://doi.org/10.18739/A2JH3D29N  

   Jones, Benjamin ; Arp, Christopher ; Grosse, Guido ; Nitze, Ingmar ; Lara, Mark ; Whitman, Matthew ; Farquharson, Louise ; Kanevskiy, Mikhail ; Parsekian, Andrew ; Breen, Amy ; et al ( January 2019 , Arctic Data Center)

   Assessment of lakes for their future potential to drain relied on the 2002/03 airborne Interferometric Synthetic Aperture Radar (IFSAR) Digital Surface Model (DSM) data for the western Arctic Coastal Plain in northern Alaska. Lakes were extracted from the IfSAR DSM using a slope derivative and manual correction (Jones et al., 2017). The vertical uncertainty for correctly detecting lake-based drainage gradients with the IfSAR DSM was defined by comparing surface elevation differences of several overlapping DSM tile edges. This comparison showed standard deviations of elevation between overlapping IfSAR tiles ranging from 0.0 to 0.6 meters (m). Thus, we chose a minimum height difference of 0.6 m to represent a detectable elevation gradient adjacent to a lake as being most likely to contribute to a rapid drainage event. This value is also in agreement with field verified estimates of the relative vertical accuracy (~0.5 m) of the DSM dataset around Utqiaġvik (formerly Barrow) (Manley et al., 2005) and the stated vertical RMSE (~1.0 m) of the DSM data (Intermap, 2010). Development of the potential lake drainage dataset involved several processing steps. First, lakes were classified as potential future drainage candidates if the difference between the elevation of the lake surface and the lowest elevation within a 100 m buffer of the lake shoreline exceeded our chosen threshold of 0.6 m. Next, we selected lakes with a minimum size of 10 ha to match the historic lake drainage dataset. We further filtered the dataset by selecting lakes estimated to have low hydrological connectivity based on relations between lake contributing area as determined for specific surficial geology types and presented in Jones et al. (2017). This was added to the future projection workflow to isolate the lake population that likely responds to changes in surface area driven largely by geomorphic change as opposed to differences in surface hydrology. Lakes within a basin with low to no hydrologic connectivity that had an elevation change gradient between the lake surface and surrounding landscape are considered likely locations to assess for future drainage potential. Further, the greater the elevation difference, the greater the drainage potential. This dataset provided a first-order estimate of lakes classified as being prone to future drainage. We further refined our assessment of potential drainage lakes by identifying the location of the point with the lowest elevation within the 100 m buffer of the lake shoreline and manually interpreted lakes to have a high drainage potential based on the location of the likely drainage point to known lake drainage pathways using circa 2002 orthophotography or more recent high resolution satellite imagery available for the Western Coastal Arctic Plain (WACP). Lakes classified as having a high drainage potential typically had the likely drainage location associated with one or more of the following: (1) an adjacent lake, (2) the cutbank of a river, (3) the ocean, (4) were located in an area with dense ice-wedge networks, (5) appeared to coincide with a potentially headward eroding stream, or (6) were associated with thermokarst lake shoreline processes in the moderate to high ground ice content terrain. We also added information on potential lake drainage pathways to the high potential drainage dataset by manually interpreting the landform associated with the likely drainage site to draw comparisons with the historic lake drainage dataset. 

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5. A remote field course implementing high-resolution topography acquisition with geomorphic applications

   https://doi.org/10.5194/gc-5-101-2022  

   Bywater-Reyes, Sharon ; Pratt-Sitaula, Beth ( January 2022 , Geoscience Communication)

   Abstract. Here we describe the curriculum and outcomes from a data-intensivegeomorphic analysis course, “Geoscience Field Issues Using High-ResolutionTopography to Understand Earth Surface Processes”, which pivoted to virtualin 2020 due to the COVID-19 pandemic. The curriculum covers technologies formanual and remotely sensed topographic data methods, including (1) GlobalPositioning Systems and Global Navigation Satellite System (GPS/GNSS)surveys, (2) Structure from Motion (SfM) photogrammetry, and (3) ground-based(terrestrial laser scanning, TLS) and airborne lidar. Course content focuseson Earth-surface process applications but could be adapted for othergeoscience disciplines. Many other field courses were canceled in summer2020, so this course served a broad range of undergraduate and graduatestudents in need of a field course as part of degree or researchrequirements. Resulting curricular materials are available freely within theNational Association of Geoscience Teachers' (NAGT's) “Teaching with Online Field Experiences” collection. Theauthors pre-collected GNSS data, uncrewed-aerial-system-derived (UAS-derived) photographs, and ground-based lidar, which students then used in courseassignments. The course was run over a 2-week period and had synchronousand asynchronous components. Students created SfM models that incorporatedpost-processed GNSS ground control points and created derivative SfM and TLSproducts, including classified point clouds and digital elevation models(DEMs). Students were successfully able to (1) evaluate the appropriatenessof a given survey/data approach given site conditions, (2) assess pros andcons of different data collection and post-processing methods in light offield and time constraints and limitations of each, (3) conduct error andgeomorphic change analysis, and (4) propose or implement a protocol to answera geomorphic question. Overall, our analysis indicates the course had asuccessful implementation that met student needs as well as course-specificand NAGT learning outcomes, with 91 % of students receiving an A, B, or Cgrade. Unexpected outcomes of the course included student self-reflectionand redirection and classmate support through a daily reflection anddiscussion post. Challenges included long hours in front of a computer,computing limitations, and burnout because of the condensed nature of thecourse. Recommended implementation improvements include spreading the courseout over a longer period of time or adopting only part of the course andproviding appropriate computers and technical assistance. This paperand published curricular materials should serve as an implementation andassessment guide for the geoscience community to use in virtual or in-personhigh-resolution topographic data courses that can be adapted for individuallabs or for an entire field or data course. 

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