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Tag: Remote Sensing
  • 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.
  • User Guide: The DEM Breakline and Differencing Analysis Tool—Gridded Elevation Model Analysis with a Convenient Graphical User Interface

    Abstract: Gridded elevation models of the earth’s surface derived from airborne lidar data or other sources can provide qualitative and quantitative information about the terrain and its surface features through analysis of the local spatial variation in elevation. The DEM Breakline and Differencing Analysis Tool was developed to extract and display micro-terrain features and vegetative cover based on the numerical modeling of elevation discontinuities or breaklines (breaks-in-slope), slope, terrain ruggedness, local surface optima, and the local elevation difference between first surface and bare earth input models. Using numerical algorithms developed in-house at the U.S. Army Engineer Research and Development Center, Geospatial Research Laboratory, various parameters are calculated for each cell in the model matrix in an initial processing phase. The results are combined and thresholded by the user in different ways for display and analysis. A graphical user interface provides control of input models, processing, and display as color-mapped overlays. Output displays can be saved as images, and the overlay data can be saved as raster layers for input into geographic information systems for further analysis.
  • Evaluation of Unmanned Aircraft Systems for Flood Risk Management: Results of Terrain and Structure Assessments

    Abstract: The 2017 Duck Unmanned Aircraft Systems (UAS) Pilot Experiment was conducted by the US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory, Field Research Facility (FRF), to assess the potential for different UAS to support US Army Corps of Engineers coastal and flood risk management. By involving participants from multiple ERDC laboratories, federal agencies, academia, and private industry, the work unit leads were able to leverage assets, resources, and expertise to assess data from multiple UAS. This report compares datasets from several UAS to assess their potential to survey and observe coastal terrain and structures. In this report, UAS data product accuracy was analyzed within the context of three potential applications: (1) general coastal terrain survey accuracy across the FRF property; (2) small-scale feature detection and observation within the experiment infrastructure area; and (3) accuracy for surveying coastal foredunes. The report concludes by presenting tradeoffs between UAS accuracy and the cost to operate to aid in selection of the best UAS for a particular task. While the technology and exact UAS models vary through time, the lessons learned from this study illustrate that UAS are available at a variety of costs to satisfy varying coastal management data needs.
  • A Review of Empirical Algorithms for the Detection and Quantification of Harmful Algal Blooms Using Satellite-Borne Remote Sensing

    Abstract: Harmful Algal Blooms (HABs) continue to be a global concern, especially since predicting bloom events including the intensity, extent, and geographic location, remain difficult. However, remote sensing platforms are useful tools for monitoring HABs across space and time. The main objective of this review was to explore the scientific literature to develop a near-comprehensive list of spectrally derived empirical algorithms for satellite imagers commonly utilized for the detection and quantification HABs and water quality indicators. This review identified the 29 WorldView-2 MSI algorithms, 25 Sentinel-2 MSI algorithms, 32 Landsat-8 OLI algorithms, 9 MODIS algorithms, and 64 MERIS/Sentinel-3 OLCI algorithms. This review also revealed most empirical-based algorithms fell into one of the following general formulas: two-band difference algorithm (2BDA), three-band difference algorithm (3BDA), normalized-difference chlorophyll index (NDCI), or the cyanobacterial index (CI). New empirical algorithm development appears to be constrained, at least in part, due to the limited number of HAB-associated spectral features detectable in currently operational imagers. However, these algorithms provide a foundation for future algorithm development as new sensors, technologies, and platforms emerge.