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  • Multiscale Observation Product (MOP) for Temporal Flood Inundation Mapping of the 2015 Dallas Texas Flood

    Abstract: This paper presents a new data fusion multiscale observation product (MOP) for flood emergencies. The MOP was created by integrating multiple sources of contributed open-source data with traditional spaceborne remote sensing imagery to provide a sequence of high spatial and temporal resolution flood inundation maps. The study focuses on the 2015 Memorial Day floods that caused up to US$61 million of damage. The Hydraulic Engineering Center River Analysis System (HEC-RAS) model was used to simulate water surfaces for the northern part of the Trinity River in Dallas, using reservoir surcharge releases and topographic data provided by the US Army Corps of Engineers. A measure of fit assessment is performed on the MOP flood maps with the HEC-RAS simulated flood inundation output to quantify spatial differences. Estimating possible flood inundation using individual datasets that vary spatially and temporally allow an understanding of how much each observational dataset contributes to the overall water estimation. Results show that water surfaces estimated by MOP are comparable with the simulated output for the duration of the flood event. Additionally, contributed data, such as Civil Air Patrol, although they may be geographically sparse, become an important data source when fused with other observation data.
  • Spatial Variations in Vegetation Fires and Emissions in South and Southeast Asia during COVID-19 and Pre-pandemic

    Abstract: Vegetation fires are common in South/Southeast Asian (SA/SEA) countries. However, few studies focused on vegetation fires and the changes during COVID compared to pre pandemic. This study fills an information gap and reports total fire incidences, total burnt area, type of vegetation burnt, and total particulate matter emission variations. Results from the short term 2020 COVID versus 2019 non COVID year showed a decline in fire counts varying from -2.88 to 79.43%. The exceptions in South Asia include Afghanistan and Sri Lanka, and Cambodia and Myanmar in Southeast Asia. The burnt area decline for 2020 compared to 2019 varied from -0.8% to 92% for South/Southeast Asian countries, with most burning in agricultural landscapes than forests. Several patches in S/SEA showed a decrease in fires for the 2020 pandemic year compared to long term 2012–2020 pre pandemic record, with Z scores greater or less than two denoting statistical significance. However, on a country scale, the results were not statistically significant in both S/SEA, with Z scores ranging from -0.24 to -1, although most countries experienced a decrease in fire counts. The study highlights variations in fires and emissions useful for fire management and mitigation.
  • Quantifying Coastal Evolution and Project Performance at Beaches by Using Satellite Imagery

    Abstract: Accurately delineating the shoreline is crucial for tracking coastal evolution, community vulnerability, storm impacts, and for coastal management decision-making. However, existing shoreline measurement methods are often time-consuming and expensive and therefore, USACE Districts are often forced to narrow areas of interest or monitoring frequency, decreasing the likelihood of making data-driven management decisions, especially over regional scales. In the last decade, space-borne earth observations have captured images subweekly, and can potentially be used for shoreline monitoring. This work investigated the Python-based CoastSat toolkit and compared the shorelines derived from publicly available satellite imagery to ground truth surveys at 37 sites across the nation chosen in coordination with Districts. Mean horizontal errors ranged from 4.21 to 20.58 m with an overall mean of 11.32 m. Tidal corrections improved accuracies at 82% of sites. The CoastSat slope function was tested and there were negligible differences in shoreline accuracy when compared with user-defined slopes Twenty-year satellite-derived trends generally align well with ground truth trends. The satellite approach identified quantifying storm impacts/recovery, beach nourishment equilibration, diffusion and decay, shoreline response to nearshore berm placements and decadal shoreline evolution at the evaluated district sites. Work is ongoing to transition to a user-friendly software tool.
  • Snow-Impacted National Inventory of Dams by GAGESII Watershed

    Abstract: This Engineering Research and Development Center (ERDC) Technical Note describes the development of a set of locations within the contiguous United States (CONUS) where snowmelt is a component of the annual streamflow. The locations are selected from the US Geological Survey (USGS) Geospatial Attributes of Gages for Evaluating Streamflow II (GAGESII) and National Inventory of Dams (NID) data sets. The 30-year normal snow regimes were used to identify all GAGESII watersheds that have any of the basin delineated as transitional (rain/snow), snow dominated, or perennial snow zones. NID dams that are within snow affected GAGESII watersheds are included in the data set. The purpose of this ERDC Technical Note is to describe the development of a comprehensive data set of CONUS GAGESII and dam infrastructure affected by snow changing regimes.
  • Spherical Shock Waveform Reconstruction by Heterodyne Interferometry

    Abstract: The indirect measurement of shock waveforms by acousto-optic sensing requires a method to reconstruct the field from the projected data. Under the assumption of spherical symmetry, one approach is to reconstruct the field by the Abel inversion integral transform. When the acousto-optic sensing modality measures the change in optical phase difference time derivative, as for a heterodyne Mach–Zehnder interferometer, e.g., a laser Doppler vibrometer, the reconstructed field is the fluctuating refractive index time derivative. A technique is derived that reconstructs the fluctuating index directly by assuming plane wave propagation local to a probe beam. With synthetic data, this approach is compared to the Abel inversion integral transform and then applied to experimental data of laser-induced shockwaves. Time waveforms are reconstructed with greater accuracy except for the tail of the waveform that maps spatially to positions near a virtual origin. Furthermore, direct reconstruction of the fluctuating index field eliminates the required time integration and results in more accurate shock waveform peak values, rise times, and positive phase duration.
  • The Influence of Mesoscale Atmospheric Convection on Local Infrasound Propagation

    Abstract: Infrasound—that is, acoustic waves with frequencies below the threshold of human hearing—has historically been used to detect and locate distant explosive events over global ranges (≥1,000 km). Simulations over these ranges have traditionally relied on large-scale, synoptic meteorological information. However, infrasound propagation over shorter, local ranges (0–100 km) may be affected by smaller, mesoscale meteorological features. To identify the effects of these mesoscale meteorological features on local infrasound propagation, simulations were conducted using the Weather Research and Forecasting (WRF) meteorological model to approximate the meteorological conditions associated with a series of historical, small-scale explosive test events that occurred at the Big Black Test Site in Bovina, Mississippi. These meteorological conditions were then incorporated into a full-wave acoustic model to generate meteorology-informed predictions of infrasound propagation. A series of WRF simulations was conducted with varying degrees of horizontal resolution—1, 3, and 15 km—to investigate the spatial sensitivity of these infrasound predictions. The results illustrate that convective precipitation events demonstrate potentially observable effects on local infrasound propagation due to strong, heterogeneous gradients in temperature and wind associated with the convective events themselves. Therefore, to accurately predict infrasound propagation on local scales, it may be necessary to use convection-permitting meteorological models with a horizontal resolution ≤4 km at locations and times that support mesoscale convective activity.
  • Amphibious Uncrewed Ground Vehicle for Coastal Surfzone Survey

    Abstract: The capability of a commercial off-the-shelf amphibious bottom crawling robot is explored for surveying seamless topography and bathymetry across the beachface, surfzone, and very nearshore. A real-time-kinematic (RTK) antenna on a mast was added to the robotic platform, a Bayonet-350 (previously the C2i SeaOx). Data collected from the robot were compared with those collected by the Coastal Research Amphibious Buggy (CRAB) and the Lighter Amphibious Resupply Cargo (LARC), unique amphibious vessels capable of collecting seamless topography and bathymetry in use for decades at the US Army Engineer Research and Development Center’s Field Research Facility (FRF). Data were compared on five different days in a range of wave conditions (Hs < 1 m in 8-m depth) resulting in a root-mean square difference of 8.7 cm and bias of 2 cm for 24 different cross-shore profile comparisons. Additionally, a repeatability test was performed to assess measurement uncertainty. The repeatability test indicated a total vertical uncertainty (TVU) of 5.8 cm, with the highest spatial error at the shoreline.
  • Spatial Screening for Environmental Pool Management Opportunities

    Abstract: US Army Corps of Engineers (USACE) reservoir projects significantly alter river ecosystem structure and function. Each project adheres to a defined set of operating rules to achieve primary objectives, which typically include flood risk management, hydropower, or navigation along with ancillary objectives for drinking water/irrigation, recreation, and natural resources management. Environmental flows (E-Flows) planning under the Sustainable Rivers Program has demonstrated new opportunities for environmental pool management (EPM; Theiling et al. 2021a, 2021b) that have no negative impact on other reservoir functions. In some locations, water level drivers can be managed to improve ecological outcomes, like wetlands, waterbirds, reptiles, and water quality, by altering the magnitude, timing, frequency, and duration of pool level changes that affect riparian and shoreline plant communities. Reservoirs with large delta areas may provide particularly important wetland or riparian habitat management along avian migratory pathways or in wildlife conservation regions (Johnson 2002). These large deltas can be identified and characterized using available satellite imagery, which along with water level habitat drivers available in hydrology databases, can be used to identify USACE reservoirs with good potential for EPM. A spatial analysis of USACE reservoirs capable to support EPM can be developed utilizing estimates of water occurrence, transition, and seasonality as well as surface elevation data derived from satellite imagery to assess geomorphology drivers. USACE water management records can be used to assess wetland drivers. Nationwide screening will be broken down into ecoregions to establish the anticipated geographic range of variation for wetland and riparian habitat drivers. Southwestern US reservoirs, for example, will have much different hydrology and fauna than Midwest and Eastern US reservoirs.
  • Low Size, Weight, Power, and Cost (SWaP-C) Payload for Autonomous Navigation and Mapping on an Unmanned Ground Vehicle

    Abstract: Autonomous navigation and unknown environment exploration with an unmanned ground vehicle (UGV) is extremely challenging. This report investigates a mapping and exploration solution utilizing low size, weight, power, and cost payloads. The platform presented here leverages simultaneous localization and mapping to efficiently explore unknown areas by finding navigable routes. The solution utilizes a diverse sensor payload that includes wheel encoders, 3D lidar, and red-green-blue and depth cameras. The main goal of this effort is to leverage path planning and navigation for mapping and exploration with a UGV to produce an accurate 3D map. The solution provided also leverages the Robot Operating System
  • During Nearshore Event Vegetation Gradation (DUNEVEG): Geospatial Tools for Automating Remote Vegetation Extraction

    Abstract: Monitoring and modeling of coastal vegetation and ecosystems are major challenges, especially when considering environmental response to hazards, disturbances, and management activities. Remote sensing applications can provide alternatives and complementary approaches to the often costly and laborious field-based collection methods traditionally used for coastal ecosystem monitoring. New and improved sensors and data analysis techniques have become available, making remote sensing applications attractive for evaluation and potential use in monitoring coastal vegetation properties and ecosystem conditions and changes. This study involves the extraction of vegetation metrics from airborne lidar and hyperspectral imagery (HSI) collected by the US Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP) to quantify coastal dune vegetation characteristics. A custom geoprocessing toolbox and associated suite of tools were developed to allow inputs of common NCMP lidar and imagery products to help automate the workflow for extracting prioritized dune vegetation metrics in an efficient and repeatable way. This study advances existing coastal ecosystem knowledge and remote sensing techniques by developing new methodologies to classify, quantify, and estimate critical coastal vegetation metrics which will ultimately improve future estimates and predictions of nearshore dynamics and impacts from disturbance events.