Publication Notices

Notifications of New Publications Released by ERDC

Contact Us

      

  

    866.362.3732

   601.634.2355

 

ERDC Library Catalog

Not finding what you are looking for? Search the ERDC Library Catalog

Results:
Tag: Remote Sensing
Clear
  • UGV SLAM Payload for Low-Visibility Environments

    Abstract: Herein, we explore using a low size, weight, power, and cost unmanned ground vehicle payload designed specifically for low-visibility environments. The proposed payload simultaneously localizes and maps in GPS-denied environments via waypoint navigation. This solution utilizes a diverse sensor payload that includes wheel encoders, inertial measurement unit, 3D lidar, 3D ultrasonic sensors, and thermal cameras. Furthermore, the resulting 3D point cloud was compared against a survey-grade lidar.
  • Improving Spatial and Temporal Monitoring of Dredging Operations Incorporating Unmanned Technologies

    Abstract: The US Army Corps of Engineers (USACE) is responsible for maintaining safe and navigable waterways through the periodic dredging of shoaled sediment from federal navigation channels. While dredging, a portion of the bottom sediments become resuspended creating a sediment plume near the dredging operation. Suspension of sediments during dredging and dredged sediment disposal operations continues to be a primary concern of regulatory agencies charged with the protection of environmental resources. Consequently, almost all dredging projects incorporate some level of regulatory compliance monitoring dedicated to measuring sediment resuspension. For numerous reasons the conventional approach using manned surface vessels to perform compliance monitoring is frequently ineffective in both adaptively managing dredging projects and ensuring true environmental protection. Advancements in unmanned platforms and payload technologies offer new and potentially more robust alternatives to conventional platforms. In this study, the use of unmanned aerial system (UAS) and weather balloon mounted camera imagery was demonstrated, and the use of an unmanned surface vessel (USV) to monitor turbidity in navigation channels and near a dredging operation. The imagery from the UAS and weather balloon were compared to in-situ turbidity measurements in a turbid distributary channel and near a dredging operation, while the USV was used to learn more about in-situ turbidity associated with passing vessels in a navigation channel. The results of the demonstrations show the unmanned technology bundled with off-the-shelf payloads can help to produce evidence-based information through easily interpreted aerial imagery and in situ measurements which can help to inform and manage water quality in areas where sediment plumes are an environmental concern.
  • Soil-Moisture Estimation of Root Zone through Vegetation-Index-Based Evapotranspiration-Fraction and Soil-Properties (SERVES) User’s Manual Version 1.0

    Purpose: The purpose of this user’s guide is to provide background methods and implementation guidance on the Soil-moisture Estimation of Root Zone through Vegetation-Index-Based Evapotranspiration-Fraction and Soil-Properties (SERVES) model (Pradhan 2019).
  • 3D Mapping and Navigation Using MOVEit

    Abstract: Until recently, our focus has been primarily on the development of a low SWAP-C payload for deployment on a UGV that leverages 2D mapping and navigation. Due to these efforts, we are able to autonomously map and navigate very well within flat indoor environments. This report will explore the implementation of 3D mapping and navigation to allow unmanned vehicles to operate on a variety of terrains, both indoor and outdoor. The method we followed uses MOVEit, a motion planning framework. The MOVEit application is typically used in the control of robotic arms or manipulators, but its handling of 3D perception using OctoMaps makes it a promising software for robots in general. The challenges of using MOVEit outside of its intended use case of manipulators are discussed in this report.
  • 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.