13 May 2026

Processing and Optimization of Global Land Ice Measurements from Space (GLIMS) Glacier Polygon Shapefiles for Army Geospatial Data Model Integration

Abstract: This technical note documents the methodology used to prepare glacier polygon datasets from the Global Land Ice Measurements from Space (GLIMS) database for integration into Army geospatial workflows. The Army Geospatial Data Model contains a feature class within the GGDM (Ground-Warfighter Geospatial Data Model) for permanent snow, defined operationally as snow persisting on the ground for more than two years. However, in cryospheric science, snow that persists across multiple accumulation seasons transitions into firn and ultimately becomes glacial ice. Thus, most “permanent snow” surfaces are more accurately classified as permanent ice, and GGDM does not currently contain a dedicated feature class representing this land-surface category. The GLIMS database provides authoritative, globally maintained glacier and perennial ice extents, making it ideally suited to fill this structural gap in the GGDM schema. The purpose of this work is to (1) transform raw GLIMS glacier polygons into a clean, nonoverlapping, attribute-free dataset; (2) standardize the geometry for compatibility with GGDM; and (3) establish a US Army Engineer Research and Development Center (ERDC)–compliant workflow for maintaining a credible representation of global permanent ice surfaces.

13 May 2026

Geospatial AI (GeoAI) Agent Stack: Router-Based Orchestration and Design Rationale

Abstract: This report summarizes the current state of a router-based, multiagent Geospatial AI (GeoAI) system designed to reliably execute geospatial workflows while retaining the flexibility of large language model (LLM) reasoning. The architecture is intentionally both language-model agnostic and orchestration-framework agnostic to support organizational controls and mandates, and it is designed to operate in air-gapped environments. It uses a domain router to scope tools before the model is invoked; a microrouter to decide whether the system should execute tools, retrieve knowledge, or produce a direct response; and a bounded cycle of execution and validation that supports multistep tool use. The design emphasizes determinism after the model makes decisions, strict boundaries around what the model can “see,” and modularity that keeps core business logic largely independent from orchestration and tool-protocol frameworks. The remainder of this report describes the architecture as implemented today, explains the design rationale, and outlines anticipated future work.

12 May 2026

A Scalable Algorithm for Dynamic Vector Model Representation Utilizing Time-Series Reduction

Abstract: This document follows a technical report published by the US Army Engineer Research and Development Center–Geospatial Research Laboratory (ERDC-GRL), Time-Series Reduction for Dynamic Vector Model Attribute Representation in a Geographic Information System (ERDC/GRL TR-24-2, Drouillard and Lewis 2024). In that publication, we described the theoretical basis for extracting and modeling raster-format spatiotemporal phenomena for inclusion as a vector model attribute and provided a preliminary Python code example that was unsuitable for large-scale application. This report details the algorithm we subsequently developed to enable global-scale application of the time-series reduction method in service of the Intelligent Environmental Battlefield Awareness (IEBA) project.

7 May 2026

Quantifying the Role of Vegetation on Urban Heat over Bengaluru, India

Abstract: The urban heat island (UHI) effect refers to how cities tend to be warmer than their non-urban surroundings, which increases the risk for heat-related illnesses and amplifies energy demands. Therefore, developing UHI mitigation strategies is crucial. Bengaluru, India has been rapidly urbanizing, but has yet to receive attention regarding potential UHI mitigation strategies. This work uses the Weather Research and Forecasting model with the single-layer urban canopy model to determine how UHI intensity changes in Bengaluru with perturbations of −10%, + 10%, + 20%, and + 30% in vegetation amount since recent work has shown that vegetation amount is the leading control of urban heat in Bengaluru. These perturbations illustrate how much the UHI could be amplified by near-depletion of vegetation or mitigated via realistic increases in vegetation. The simulations were investigated diurnally and during the dry and wet seasons. Results show that increases in vegetation were associated with a decrease in urban land surface temperature, an increase in the latent heat flux, and decreases in the sensible heat flux, and vice versa for a decrease in vegetation. Significant changes in UHI intensity usually occurred only when vegetation was increased by 20% or more. However, for the dry season nighttime, which exhibited the highest UHI intensity in the control run (1.70oC), the 10% increase in vegetation produced a significant decrease of − 0.19oC in UHI intensity, likely due to a shallow planetary boundary layer height. These results could have implications for mitigating urban heat, and reducing energy demands and public health risk in Bengaluru.

20 Apr 2026

Multimethod Change-Detection Analysis Using Prithvi-EO-2.0: A Comparative Study of Traditional and Segmentation-Based Approaches for Vector Database Validation

Abstract: This technical note presents an evaluation of the performance of four change-detection methodologies, with a focus on validating and maintaining authoritative vector-feature databases using Earth observation data. In this study, we implemented traditional pixel-to-pixel change detection, feature-data-compliant segmentation, pixel-to-feature segmentation, and feature-to-pixel change detection, leveraging the Prithvi-EO-2.0 Vision Transformer model (Szwarcman et al. 2025), to analyze imagery from California’s Central Valley. The analysis of Sentinel-2 imagery from California’s Central Valley (in 2021–2023) demonstrated that there was a trade-off between sensitivity and reliability in the change-detection approaches: feature-to-feature methods achieved the highest sensitivity (0.637 average), while the feature-to-pixel approach provided the most reliable validation (0.280 average), exceeding the performance of traditional pixel-to-pixel methods (0.256 average).

20 Apr 2026

Utilizing Laser Diffraction for Soil Particle Size Analysis

Abstract: This US Army Engineer Research and Development Center (ERDC) technical note (TN) describes the process and methodology for utilizing laser diffraction to analyze soil samples. The effort fulfills an Intelligent Environmental Battlefield Awareness (IEBA) project’s need to validate the performance of a global soil boundary mapping methodology that was developed as part of the Integration task. To validate the methodology, soil samples were classified by grain size into a texture class and compared against soil maps created for a given study area. The goal of this effort was to develop a repeatable standard operating procedure for the Horiba Partica LA-960V2, a laser diffraction particle size analyzer, that would allow rapid soil analysis to be conducted by individuals without a soil science background. The Horiba Partica has been used for soil particle size analysis, but it is not common in the field. Therefore, only limited documentation details the analysis protocol for the system. This TN will discuss the methodology used to analyze soil samples and the challenges encountered with the Horiba Partica.

3 Mar 2026

Enhanced Spatial Resolution of Landsat Imagery Through Systematic Sensor Offset Exploitation: A Blended Pansharpening Approach

Purpose: This technical note presents a novel blended pansharpening methodology that exploits the systematic 7.5-meter (m) geometric offset between Landsat multispectral (MS) and panchromatic (pan) sensors to achieve selective spatial enhancement beyond conventional 15 m resolution limits. The approach creates a variable resolution product with an effective resolution of approximately 11.25 m and demonstrates superior spatial detail preservation in urban infrastructure while maintaining perfect spectral integrity.

3 Mar 2026

The Use of Nitrocellulose Production Waste for Energy Generation

Abstract: The US Army Engineer Research and Development Center investigated the use of nitrocellulose (NC) fines, an ammunition waste, for energy generation. NC is a natural high polymer obtained from treating cotton or wool with nitric and sulfuric acid. It is widely used in the industry, with military applications being the largest use currently. Since military applications range from bullet propellants to missiles for tube munitions, large quantities must be produced to meet the demand. However, large NC production batches result in large quantities of NC fines waste, generated in the form of insoluble fibers in suspension in wastewater after manufacturing. Hence, a method to reuse this generated waste and convert it into energy was tested. This study evaluated the potential of creating energy from NC waste through hydrothermal liquefaction and gasification of NC, yielding methane (CH4) as the final product. Results demonstrated that the CH4 concentrations increased as the temperature, reaction time, and catalyst addition were increased, yielding a maximum concentration of 2,000 ppm (6,400 peak area of the chromatograph). The homogenous catalyst performed better than the heterogenous catalyst, since it increased the CH4 yield up to 6 times the concentration obtained with no catalyst added.

1 Oct 2025

Relief Well Sustainment Deployable Resilient Installation Water Purification and Treatment System (RWS-DRIPS): Treatment of Relief Wells at Perry Dam, Kansas

Purpose: This report details the treatment process and resulting outcomes for relief wells at Perry Dam (Jefferson County, Kansas) using the Relief Well Sustainment Deployable Resilient Installation Water Purification and Treatment System (RWS-DRIPS) treatment trailer. The RWS-DRIPS is a mobile treatment unit with comprehensive water treatment capabilities designed to disinfect surface and subsurface water with high efficiency. Immediately following treatment with the RWS-DRIPS unit, video monitoring was used to observe the condition of the relief wells. The results of that observation are described in this report.

25 Sep 2025

From Analog to Digital: A Systematic Workflow for Converting Published Landform Maps to Georeferenced Datasets

Abstract: Reference datasets for geomorphological analysis often require the integration of multiple data sources, including legacy maps and published figures that exist only as scanned images or hard copies. This report documents a systematic five-step workflow for converting landform information from these analog sources into georeferenced point datasets suitable for digital analysis. The methodology encompasses acquiring and evaluating imagery, georeferencing using ground control points, manually digitizing landform polygons, converting to centroid points using a systematic grid-based approach, and assigning attributes with quality control measures. In a case study on East Asia, we demonstrate the workflow’s practical application by processing 15 published sources to generate over 2 million labeled landform points representing approximately 1,015 km² of land across China and Mongolia. The dataset encompasses seven landform classes commonly found in arid environments: active washes, alluvial fans, bedrock, pediments, playas, sand dunes, and sand sheets. Quality assessments using analyst confidence ratings revealed reliable classification performance for most landform types. This workflow provides researchers with an efficient approach to leveraging existing published landform data, thus expanding the spatial coverage and temporal depth of reference datasets that are available for geomorphological analysis and machine learning applications.