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Category: Technology
  • Semi-Automated Land Cover Mapping Using an Ensemble of Support Vector Machines with Moderate Resolution Imagery Integrated into a Custom Decision Support Tool

    Abstract: Land cover type is a fundamental remote sensing-derived variable for terrain analysis and environmental mapping applications. The currently available products are produced only for a single season or a specific year. Some of these products have a coarse resolution and quickly become outdated, as land cover type can undergo significant change over a short time period. In order to enable on-demand generation of timely and accurate land cover type products, we developed a sensor-agnostic framework leveraging pre-trained machine learning models. We also generated land cover models for Sentinel-2 (20m) and Landsat 8 imagery (30m) using either a single date of imagery or two dates of imagery for mapping land cover type. The two-date model includes 11 land cover type classes, whereas the single-date model contains 6 classes. The models’ overall accuracies were 84% (Sentinel-2 single date), 82% (Sentinel-2 two date), and 86% (Landsat 8 two date) across the continental United States. The three different models were built into an ArcGIS Pro Python toolbox to enable a semi-automated workflow for end users to generate their own land cover type maps on demand. The toolboxes were built using parallel processing and image-splitting techniques to enable faster computation and for use on less-powerful machines.
  • Field Jet Erosion Tests on Benbrook Dam, Texas

    Abstract: This report summarizes the results of eight field Jet Erosion Tests (JETs) performed on Benbrook Dam, TX. The results from these tests will be used by the U.S. Army Corps of Engineers, Fort Worth District, in assessments of the erosion resistance of the Benbrook Dam with regards to possible overtopping by extreme flooding. The JETs were performed at four different locations, i.e., two locations at the lowest crest elevation and two locations at the mid-slope face of the downstream embankment. Variations in estimated critical hydraulic shear stress and erosion rate values may have been caused by differences in soil composition, i.e., when the material changed from silt/sand to clay. The resulting values of the Erodibility Coefficient, Kd, and Critical Stress, τc, are very useful information in assessing the stability of Benbrook Dam during an overtopping event. Because of the observed natural variability of the materials, combining the erosion parameters presented in this report with the drilling logs and local geology will be imperative for assessing erosion-related failure modes of Benbrook Dam.
  • Data Collection Tools for River Geomorphology Studies: LiDAR and Traditional Methods

    Abstract: The purpose of this review is to highlight LiDAR data usage for geomorphic studies and compare to other remote sensing technologies. This review further identifies survey efficiencies and issues that can be problematic in using LiDAR digital elevation models (DEMs) in completing surveys and geomorphic analysis. US Army Corps of Engineers (USACE) geospatial data collection guidance (EM 1110-1-1000) (USACE 2015) aligns with the American Society for Photogrammetry and Remote Sensing Positional Accuracy Standards for Digital Geospatial Data (ASPRS 2014). Geomorphic assessment technologies are rapidly evolving, and LiDAR data collection methods are at the forefront. The FluvialGeomorph (FG) toolbox, developed to support USACE watershed planning, is a recent example of the use of LiDAR high-resolution terrain data to provide a new, efficient approach for rapid watershed assessments (Haring et al. 2020; Haring and Biedenharn 2021). However, there are advantages and disadvantages in using LiDAR data compared to other remote sensing technologies and traditional topographic field survey methods.
  • Development of Smartphone-Based Semi-Prepared Runway Operations (SPRO) Models and Methods

    Abstract: The U.S. Army Engineer Research and Development Center (ERDC) has developed a method for predicting surface friction response by use of ground vehicles equipped with deceleration-based measurement devices. Specifically, the ERDC has developed models and measurement methods between the Findlay Irvine Mk2 GripTester and a variety of deceleration measurement devices: Bowmonk AFM2 Mk3, Xsens MTi-G-710, two Android smartphones, and two iOS smartphones. These models show positive correlation between ground vehicle deceleration and fixed-slip surface continuous surface friction measurement. This effort extends prior work conducted by the U.S. Army ERDC in developing highly correlative models between the Findlay Irvine Mk2 GripTester and actual C-17 braking deceleration, measured via the runway condition rating (RCR) system. The models and measurement methods detailed here are of considerable use to semi-prepared airfield managers around the world needing to measure safe landing conditions following inclement weather. This work provides the tools necessary for airfield managers to quantify safe landing conditions for C-17 aircraft by using easily obtainable equipment and simple test standards.
  • A Detailed Approach to Autonomous Vehicle Control through Ros and Pixhawk Controllers

    Abstract: A Polaris MRZR military utility vehicle was used as a testing platform to develop a novel, low cost yet feature-rich, approach to adding remote operation and autonomous driving capability to a military vehicle. The main concept of operation adapts steering and throttle output from a low cost commercially available Pixhawk autopilot controller and translates the signal into the necessary inputs for the Robot Operating System (ROS) based drive by wire system integrated into the MRZR. With minimal modification these enhancements could be applied to any vehicle with similar ROS integration. This paper details the methods and testing approach used to develop this autonomous driving capability.
  • Imagery Classification for Autonomous Ground Vehicle Mobility in Cold Weather Environments

    Abstract: Autonomous ground vehicle (AGV) research for military applications is important for developing ways to remove soldiers from harm’s way. Current AGV research tends toward operations in warm climates and this leaves the vehicle at risk of failing in cold climates. To ensure AGVs can fulfill a military vehicle’s role of being able to operate on- or off-road in all conditions, consideration needs to be given to terrain of all types to inform the on-board machine learning algorithms. This research aims to correlate real-time vehicle performance data with snow and ice surfaces derived from multispectral imagery with the goal of aiding in the development of a truly all-terrain AGV. Using the image data that correlated most closely to vehicle performance the images were classified into terrain units of most interest to mobility. The best image classification results were obtained when using Short Wave InfraRed (SWIR) band values and a supervised classification scheme, resulting in over 95% accuracy.
  • Methodology for the Analysis of Geospatial and Vehicle Datasets in the R Language

    Abstract: The challenge of autonomous off-road operations necessitates a robust understanding of the relationships between remotely sensed terrain data and vehicle performance. The implementation of statistical analyses on large geospatial datasets often requires the transition between multiple software packages that may not be open-source. The lack of a single, modular, and open-source analysis environment can reduce the speed and reliability of an analysis due to an increased number of processing steps. Here we present the capabilities of a workflow, developed in R, to perform a series of spatial and statistical analyses on vehicle and terrain datasets to quantify the relationship between sensor data and vehicle performance in winter conditions. We implemented the R-based workflow on datasets from a large, coordinated field campaign aimed at quantifying the response of military vehicles on snow-covered terrains. This script greatly reduces processing times of these datasets by combining the GIS, data-assimilation and statistical analyses steps into one efficient and modular interface.
  • Artificial Ground Freezing Using Solar-Powered Thermosyphons

    Abstract: Thermosyphons are an artificial ground-freezing technique that has been used to stabilize permafrost since the 1960s. The largest engineered structure that uses thermosyphons to maintain frozen ground is the Trans Alaska Pipeline, and it has over 124,000 thermosyphons along its approximately 1300 km route. In passive mode, thermosyphons extract heat from the soil and transfer it to the environment when the air temperature is colder than the ground temperature. This passive technology can promote ground cooling during cold winter months. To address the growing need for maintaining frozen ground as air temperatures increase, we investigated a solar-powered refrigeration unit that could operate a thermosyphon (nonpassive) during temperatures above freezing. Our tests showed that energy generated from the solar array can operate the refrigeration unit and activate the hybrid thermosyphon to artificially cool the soil when air temperatures are above freezing. This technology can be used to expand the application of thermosyphon technology to freeze ground or maintain permafrost, particularly in locations with limited access to line power.
  • Sabine Pass to Galveston Bay, TX Pre-Construction, Engineering and Design (PED): Coastal Storm Surge and Wave Hazard Assessment: Report 4 – Freeport

    Abstract: The US Army Corps of Engineers, Galveston District, is executing the Sabine Pass to Galveston Bay Coastal Storm Risk Management (CSRM) project for Brazoria, Jefferson, and Orange Counties regions. The project is currently in the Pre-construction, Engineering, and Design phase. This report documents coastal storm water level (SWL) and wave hazards for the Freeport CSRM structures. Coastal SWL and wave loading and overtopping are quantified using high-fidelity hydrodynamic modeling and stochastic simulations. The CSTORM coupled water level and wave modeling system simulated 195 synthetic tropical storms on three relative sea level change scenarios for with- and without-project meshes. Annual exceedance probability (AEP) mean values were reported for the range of 0.2 to 0.001 for peak SWL and wave height (Hm0) along with associated confidence limits. Wave period and mean wave direction associated with Hm0 were also computed. A response-based stochastic simulation approach is applied to compute AEP values for overtopping for levees and overtopping, nappe geometry and combined hydrostatic and hydrodynamic fluid pressures for floodwalls. CSRM crest design elevations are defined based on overtopping rates corresponding to incipient damage. Survivability and resilience are evaluated. A system-wide hazard level assessment was conducted to establish final recommended system-wide elevations.
  • Demonstration of Subsurface Passive Acoustic Monitoring (SPAM) to Survey for and Estimate Populations of Imperiled Underwater-calling Frogs

    Abstract: The management and recovery of threatened and endangered amphibians on Department of Defense (DoD) lands relies on an understanding of their distribution and abundance. Fortunately, most anuran species can be surveyed acoustically using vocalizations during the breeding season. This work demonstrated the use of subsurface passive acoustic monitoring (SPAM) to survey for rare underwater-calling, at-risk anuran species on DoD installations. We evaluated the performance of SPAM relative to traditional passive acoustic monitoring (PAM) (microphone) and human manual calling survey (MCS) methods. Results showed that SPAM outperformed PAM and MCS in validation experiments where calls were generated underwater; SPAM was less successful than PAM and MCS in the field demonstration. Most leopard frog calls were apparently produced in air despite previous reports of extensive underwater-calling behavior. This project highlights how acoustic information can help address a data gap in the ecology of at-risk species, which can help refine future survey methodology and management efforts. Ultimately, the utility of SPAM for underwater-calling species will depend on the focal species, the landscape where it occurs, and technological considerations available to the surveyor. SPAM is more expensive than traditional methods but, in some situations, may be the only way to effectively detect species.