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  • A Generalized Photon-Tracking Approach to Simulate Spectral Snow Albedo and Transmittance Using X-ray Microtomography and Geometric Optics

    Abstract: A majority of snow radiative transfer models (RTMs) treat snow as a collection of idealized grains rather than an organized ice–air matrix. Here we present a generalized multi-layer photon-tracking RTM that simulates light reflectance and transmittance of snow based on X-ray micro- tomography images, treating snow as a coherent 3D structure rather than a collection of grains. The model uses a blended approach to expand ray-tracing techniques applied to sub-1 cm3 snow samples to snowpacks of arbitrary depths. While this framework has many potential applications, this study’s effort is focused on simulating reflectance and transmittance in the visible and near infrared (NIR) through thin snow- packs as this is relevant for surface energy balance and remote sensing applications. We demonstrate that this framework fits well within the context of previous work and capably reproduces many known optical properties of a snow surface, including the dependence of spectral reflectance on the snow specific surface area and incident zenith angle as well as the surface bidirectional reflectance distribution function (BRDF). To evaluate the model, we compare it against reflectance data collected with a spectroradiometer at a field site in east-central Vermont. In this experiment, painted panels were inserted at various depths beneath the snow to emulate thin snow. The model compares remarkably well against the reflectance measured with a spectroradiometer, with an average RMSE of 0.03 in the 400–1600 nm range. Sensitivity simulations using this model indicate that snow transmittance is greatest in the visible wavelengths, limiting light penetration to the top 6 cm of the snowpack for fine-grain snow but increasing to 12 cm for coarse-grain snow. These results suggest that the 5% transmission depth in snow can vary by over 6 cm according to the snow type.
  • Geomorphic Feature Extraction to Support the Great Lakes Restoration Initiative’s Sediment Budget and Geomorphic Vulnerability Index for Lake Michigan

    Purpose: This Coastal and Hydraulics Engineering technical note (CHETN) details a Geographic Information Systems (GIS) methodology to produce advanced lidar-derived datasets for use in a coastal erosion vulnerability analysis conducted by the US Army Corps of Engineers (USACE) and other federal partners for the Great Lakes Restoration Initiative (GLRI).
  • Waste Management and Landfill Facilities Assessment Using Unmanned Aircraft Systems

    Abstract: Finite and decreasing landfill space on Army installations is a significant concern. Efficient waste management is essential for achieving resiliency and extending the lifespan of remaining landfills. The purpose of this demonstration was to conduct independent performance tests of small unmanned aircraft systems (sUAS) and their utility for providing landfill assessments in remote areas where physical presence is either dangerous or inefficient. An active, near capacity construction and demolition (C&D) landfill at Fort Gordon, Georgia, was identified for the demonstration. The flights, data requirements, and outputs generated by the sUAS flyovers were analyzed for efficacy in detecting cell capacity and subsidence. Each flight took 1–2 hours for mobilization, ground marker placement, flight, and postflight analysis. Volumetric and topographic surveys were analyzed in less time than is typical for traditional surveying methods. After initial setup of ground markers and rectification, sUAS flights save a significant amount of time. However, skilled individuals are required for flights and for processing and maintaining data. The technology is widely relevant to the Army, is commercially available, and offers an average of 30% cost savings in terms of manpower, repeatability, and equipment. The use of sUAS technology is recommended for monitoring and surveying Army landfills.
  • Remote Sensing Tools to Support Ordinary High Water Mark Delineation

    Abstract: This document is a technical note (TN) that describes existing and recently developed tools to support ordinary high water mark (OHWM) identification and delineation. It also presents a case study to demonstrate how utilizing the tools provide supporting lines of evidence in OHWM delineations.
  • Three-Dimensional Geospatial Product Generation from Tactical Sources, Co-Registration Assessment, and Considerations

    Abstract: According to Army Multi-Domain Operations (MDO) doctrine, generating timely, accurate, and exploitable geospatial products from tactical platforms is a critical capability to meet threats. The US Army Corps of Engineers, Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL) is carrying out 6.2 research to facilitate the creation of three-dimensional (3D) products from tactical sensors to include full-motion video, framing cameras, and sensors integrated on small Unmanned Aerial Systems (sUAS). This report describes an ERDC-GRL processing pipeline comprising custom code, open-source software, and commercial off-the-shelf (COTS) tools to geospatially rectify tactical imagery to authoritative foundation sources. Four datasets from different sensors and locations were processed against National Geospatial-Intelligence Agency–supplied foundation data. Results showed that the co-registration of tactical drone data to reference foundation varied from 0.34 m to 0.75 m, exceeding the accuracy objective of 1 m described in briefings presented to Army Futures Command (AFC) and the Assistant Security of the Army for Acquisition, Logistics and Technology (ASA(ALT)). A discussion summarizes the results, describes steps to address processing gaps, and considers future efforts to optimize the pipeline for generation of geospatial data for specific end-user devices and tactical applications.
  • The DEM Breakline and Differencing Analysis Tool—Step-by-Step Workflows and Procedures for Effective Gridded DEM Analysis

    Abstract: The DEM Breakline and Differencing Analysis Tool is the result of a multi-year research effort in the analysis of digital elevation models (DEMs) and the extraction of features associated with breaklines identified on the DEM by numerical analysis. Developed in the ENVI/IDL image processing application, the tool is designed to serve as an aid to research in the investigation of DEMs by taking advantage of local variation in the height. A set of specific workflow exercises is described as applied to a diverse set of four sample DEMs. These workflows instruct the user in applying the tool to extract and analyze features associated with terrain, vegetative canopy, and built structures. Optimal processing parameter choices, subject to user modification, are provided along with sufficient explanation to train the user in elevation model analysis through the creation of customized output overlays.
  • Meteorological Influences of a Major Dust Storm in Southwest Asia during July–August 2018

    Abstract: Dust storms can be hazardous for aviation, military activities, and respiratory health and can occur on a wide variety of spatiotemporal scales with little to no warning. To properly forecast these storms, a comprehensive understanding of the meteorological dynamics that control their evolution is a prerequisite. To that end, we chose a major dust storm that occurred in Southwest Asia during July–August 2018 and conducted an observation-based analysis of the meteorological conditions that influenced the storm’s evolution. We found that the main impetus behind the dust storm was a large-scale meteorological system (i.e., a cyclone) that affected Southwest Asia. It seems that cascading effects from this system produced a smaller, near-surface warm anomaly in Mesopotamia that may have triggered the dust storm, guided its trajectory over the Arabian Peninsula, and potentially catalyzed the development of a small low-pressure system over the southeastern end of the peninsula. This low-pressure system may have contributed to some convective activity over the same region. This type of analysis may provide important information about large-scale meteorological forcings for not only this particular dust storm but also for future dust storms in Southwest Asia and other regions of the world.
  • Landform Identification in the Chihuahuan Desert for Dust Source Characterization Applications: Developing a Landform Reference Data Set

    Abstract: ERDC-Geo is a surface erodibility parameterization developed to improve dust predictions in weather forecasting models. Geomorphic landform maps used in ERDC-Geo link surface dust emission potential to landform type. Using a previously generated southwest United States landform map as training data, a classification model based on machine learning (ML) was established to generate ERDC-Geo input data. To evaluate the ability of the ML model to accurately classify landforms, an independent reference landform data set was created for areas in the Chihuahuan Desert. The reference landform data set was generated using two separate map-ping methodologies: one based on in situ observations, and another based on the interpretation of satellite imagery. Existing geospatial data layers and recommendations from local rangeland experts guided site selections for both in situ and remote landform identification. A total of 18 landform types were mapped across 128 sites in New Mexico, Texas, and Mexico using the in situ (31 sites) and remote (97 sites) techniques. The final data set is critical for evaluating the ML-classification model and, ultimately, for improving dust forecasting models.
  • Automated Detection of Austere Entry Landing Zones: A “GRAIL Tools” Validation Assessment

    Abstract: The Geospatial Remote Assessment for Ingress Locations (GRAIL) Tools software is a geospatial product developed to locate austere entry landing zones (LZs) for military aircraft. Using spatial datasets like land classification and slope, along with predefined LZ geometry specifications, GRAIL Tools generates binary suitability filters that distinguish between suitable and unsuitable terrain. GRAIL Tools combines input suitability filters, searches for LZs at user‐defined orientations, and plots results. To refine GRAIL Tools, we: (a) verified software output; (b) conducted validation assessments using five unpaved LZ sites; and (c) assessed input dataset resolution on outcomes using 30 and 1‐m datasets. The software was verified and validated in California and the Baltics, and all five LZs were correctly identified in either the 30 or the 1‐m data. The 30‐m data provided numerous LZs for consideration, while the 1‐m data highlighted hazardous conditions undetected in the 30‐m data. Digital elevation model grid size affected results, as 1‐m data produced overestimated slope values. Resampling the data to 5 m resulted in more realistic slopes. Results indicate GRAIL Tools is an asset the military can use to rapidly assess terrain conditions.
  • Remote Sensing Capabilities to Support EWN® Projects: An R&D Approach to Improve Project Efficiencies and Quantify Performance

    PURPOSE: Engineering With Nature (EWN®) is a US Army Corps of Engineers (USACE) Initiative and Program that promotes more sustainable practices for delivering economic, environmental, and social benefits through collaborative processes. As the number and variety of EWN® projects continue to grow and evolve, there is an increasing opportunity to improve how to quantify their benefits and communicate them to the public. Recent advancements in remote sensing technologies are significant for EWN® because they can provide project-relevant detail across a large areal extent, in which traditional survey methods may be complex due to site access limitations. These technologies encompass a suite of spatial and temporal data collection and processing techniques used to characterize Earth's surface properties and conditions that would otherwise be difficult to assess. This document aims to describe the general underpinnings and utility of remote sensing technologies and applications for use: (1) in specific phases of the EWN® project life cycle; (2) with specific EWN® project types; and (3) in the quantification and assessment of project implementation, performance, and benefits.