29 Feb 2024

Analysis of Vegetation as Terrain: The “How” and “Why” of US Army Doctrine

Abstract: There is a significant knowledge gap for Army doctrine concerning civilian research scientists. A relatively small number of soldiers make the transition from warfighter to research and development at the basic and applied levels. That number is even less when considering former warfighters that have applied Army doctrine in an operational or advanced Army schooling environment. This special report is intended to focus solely on the Army’s current capabilities and doctrinally defined processes to analyze vegetation as an essential component of the natural terrain. The objective of this report is to review current Army doctrine related to analysis of the vegetated terrain; to explore currently leveraged tactics, techniques, and procedures (TTPs); and identify valuable geospatial resources as they apply to military planning. For ease to readers unfamiliar with US Army doctrine, much of the referenced material is directly presented herein as tables and figures throughout the document and appendices (e.g., data sources, product examples, and glossary).

21 Nov 2023

Rotorcraft Resupply Site Selection (RRSS) v1.0 and the USACE Model Interface Platform (UMIP): Documentation and User’s Guide

Abstract: This research effort aimed to create an operational prototype of the Geomorphic Oscillation Assessment Tool (GOAT) v1.0, developed by the US Army Engineer Research and Development Center, as a part of the US Army Corps of Engineers’ Model Interface Platform (UMIP). This platform is a web-based software that allows for easy and rapid construction and deployment of spatial planning and analysis capabilities. The prototype tool in UMIP represents the science embedded in GOAT while providing a user-friendly interface for interaction and spatially referenced result viewing. It also includes user access control, data storage, and integration with a long-term data management system, enabling users to access, share, and interrogate past analyses through profile management and result persistence. The prototype tool incorporates surface roughness into terrain suitability assessment tools used in the forward arming and refueling point (FARP) site-selection process.

25 Jul 2023

Bridge Resource Inventory Database for Gap Emplacement Selection (BRIDGES)

Abstract: Wet gap crossings are one of the most complex maneuvers undertaken by military engineers, who, along with engineer planners, require better tools to increase the capacity for efficient use of limited bridging resources across the battlespace. Planning for bridging maneuvers often involves a complicated and inefficient system of ad hoc spreadsheets combined with an overreliance on the personal experience and training of subject matter experts (SMEs). Bridge Resource Inventory Database for Gap Emplacement Selection (BRIDGES) uses interactive mapping and database technology in order to streamline the bridging planning process and provide answers to question about myriad scenarios to maximize efficiency and provide better means of data persistence across time and data sharing across operational or planning units.

6 Feb 2023

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.

28 Nov 2022

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.

28 Nov 2022

Cross Country Mobility (CCM) Modeling Using Triangulated Irregular Networks (TIN)

Abstract: Cross country mobility (CCM) models terrain that has insufficient or unavailable infrastructure for crossing. This historically has been done with either hand-drawn and estimated maps or with raster-based terrain analysis, both of which have their own strengths and weaknesses. In this report the authors explore the possibility of using triangulated irregular networks (TINs) as a means of representing terrain characteristics used in CCM and discuss the possibilities of using such networks for routing capabilities in lieu of a traditional road-based network. The factors used to calculate CCM are modified from previous methods to capture a more accurate measurement of terrain characteristics. Using a TIN to store and represent CCM information achieves comparable results to raster cost analysis with the additional benefits of an integrated network useful for visualization and routing and a reduction in the number of related files. Additionally, TINs can in some cases more accurately show the contours of the landscape and reveal feature details or impediments that may be lost within a raster, thus improving the quality of CCM overlays.

12 Aug 2022

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.

30 Sep 2021

Incorporating Terrain Roughness into Helicopter Landing Zone Site Selection by Using the Geomorphic Oscillation Assessment Tool (GOAT) v1.0

ABSTRACT: The Geomorphic Oscillation Assessment Tool (GOAT) quantifies terrain roughness as a mechanism to better explain forward arming and refueling point (FARP) suitability for Army aviation. An empirically driven characteristic of FARP consideration, surface roughness is a key discriminator for site utility in complex terrain. GOAT uses a spatial sampling of high-resolution elevation and land cover data to construct data frames, which enable a relational analysis of component and aggregate site suitability. By incorporating multiple criteria from various doctrinal sources, GOAT produces a composite quality assessment of the areal options available to the aviation commander. This report documents and demonstrates version 1.0 of the GOAT algorithms developed by the U.S. Army Engineer Research and Development Center (ERDC). These details will allow users familiar with R to implement it as a stand-alone program or in R Studio.

10 May 2021

Automated Terrain Classification for Vehicle Mobility in Off-Road Conditions

ABSTRACT:  The U.S. Army is increasingly interested in autonomous vehicle operations, including off-road autonomous ground maneuver. Unlike on-road, off-road terrain can vary drastically, especially with the effects of seasonality. As such, vehicles operating in off-road environments need to be informed about the changing terrain prior to departure or en route for successful maneuver to the mission end point. The purpose of this report is to assess machine learning algorithms used on various remotely sensed datasets to see which combinations are useful for identifying different terrain. The study collected data from several types of winter conditions by using both active and passive, satellite and vehicle-based sensor platforms and both supervised and unsupervised machine learning algorithms. To classify specific terrain types, supervised algorithms must be used in tandem with large training datasets, which are time consuming to create. However, unsupervised segmentation algorithms can be used to help label the training data. More work is required gathering training data to include a wider variety of terrain types. While classification is a good first step, more detailed information about the terrain properties will be needed for off-road autonomy.