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NASA NTRS2002

Continuing Development of a Collaborative Plan to Further Engage South Dakota in NASA's Earth Science Enterprise

An ongoing set of research planning activities have occurred in South Dakota as a consequence of the past two years of NASA-EPSCoR Preparation Grants. During this time a group of approximately 60 scientists, engineers, and university administrators in South Dakota have been directly involved as "theme team" members in a series of five all-day meetings to identify the research and technological priorities that are consistent both with NASA-ESE's interests and the State's expertise. Institutions represented within the group's membership include: South Dakota School of Mines & Technology, South Dakota State University, Augustana College, University of South Dakota, USGS EROS Data Center, Si ranks College, Santa Gleska University, Sisseton Wahpeton Community College, USGS Water Resources Division, US National Weather Service, and the SD Department of Environment & Natural Resources. Many of these organizations are also members and affiliates of the SD Space Grant Consortium. The evolving plan has been guided by the following desirable actions: 1. To establish new contacts and strengthen existing linkages with NASA Centers, relevant NASA researchers, and key personnel at the USGS EROS Data Center. 2. To promote participation from the State's major research institutions, State agencies, and relevant businesses in South Dakota that are interested in strengthening our scientific and technological enterprises. 3. To develop the State's scientific talent and infrastructure for enhanced competitiveness in research, development, and technology-based economic development. 4. To encourage greater participation by under represented groups, especially Native Americans, in scientific education and research. 5. To build greater public and political support in South Dakota for the overall science, engineering, and technology enterprise. 6. To communicate the benefits of current and future NASA programs to the progress and development of South Dakota, the Northern Great Plains Region, and the Nation.

Farwell, Sherry O.↗

NASA NTRS2002

The Joint Agency Commercial Imagery Evaluation (JACIE) Team: Overview and IKONOS Joint Characterization Approach

An overview of the Joint Agency Commercial Imagery Evalation (JACIE) team is presented. JACIE, composed of the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS), was formed to leverage government agencies' capabilities for the characterization of commercial remote sensing data. Each JACIE agency purchases, or plans to purchase, commercial imagery to support its research and applications. It is critical that the data be assessed for its accuracy and utility. Through JACIE, NASA, NIMA, and USGS jointly characterized image products from Space Imaging's IKONOS satellite. Each JACIE agency performed an aspect of the characterization based on its expertise. NASA and its university partners performed a system characterization focusing on radiometric calibration, geopositional accuracy, and spatial resolution assessment; NIMA performed image interpretability and feature extraction evaluations; and USGS assessed geopositional accuracy of several IKONOS products. The JACIE team purchased IKONOS imagery of several study sites to perform the assessments and presented results at an industry-government workshop. Future plans for JACIE include the characterization of DigitalGlobe's QuickBird-2 image products.

Zanoni, Vicki↗

NASA NTRS2004

Global Land Ice Measurements from Space

The NSIDC at the University of Colorado has successfully completed the tasks outlined in its proposal 0999.08.1216B, the 'Global Land Ice Measurements from Space' grant funded by NASA under NAG5-9722. The Global Land Ice Measurements from Space (GLIMS) grant reported on here is one of the first completed elements of the overall GLIMS project that continues with separate funding from NASA, the United States Geological Survey (USGS), and internationally by many national agencies and universities. The primary goals of GLIMS are to survey significant numbers of the world's 160,000 glaciers with data collected by the ASTER (Advanced Spaceborne Thermal Emission and reflection Radiometer) instrument aboard the EOS Terra spacecraft, and Landsat ETM+ (Enhanced Thematic Mapper Plus) and to make these data available to users in a common and easily usable format. GLIMS participants include: NSIDC as developer of the GLIMS database, USGS Flagstaff as the GLIMS Coordination Center, USGS EROS Data Center (EDC) as the archive for satellite imagery used in GLIMS analyses (NASA funding for GLIMS also includes the Flagstaff group and EDC through the related ASTER Science Team and Land Processes Distributed Active Archive Center [LP DAAC] activities), and approximately twenty two Regional Centers (RCs). RCs are funded by the national agencies of participating countries to analyze satellite imagery for a specified set of glaciological parameters and provide the results to NSIDC for archive and distribution to the public.

Scharfen, Gregory R.↗

NASA NTRS2005

The Hurricane-Flood-Landslide Continuum

In August 2004, representatives from NOAA, NASA, the USGS, and other government agencies convened in San Juan, Puerto Rim for a workshop to discuss a proposed research project called the Hurricane-Flood-Landslide Continuum (HFLC). The essence of the HFLC is to develop and integrate tools across disciplines to enable the issuance of regional guidance products for floods and landslides associated with major tropical rain systems, with sufficient lead time that local emergency managers can protect vulnerable populations and infrastructure. All three lead agencies are independently developing precipitation-flood-debris flow forecasting technologies, and all have a history of work on natural hazards both domestically and overseas. NOM has the capability to provide tracking and prediction of storm rainfall, trajectory and landfall and is developing flood probability and magnTtude capabilities. The USGS has the capability to evaluate the ambient stability of natural and man-made landforms, to assess landslide susceptibilities for those landforms, and to establish probabilities for initiation of landslides and debris flows. Additionally, the USGS has well-developed operational capacity for real-time monitoring and reporting of streamflow across distributed networks of automated gaging stations (http://water.usgs.gov/waterwatch/). NASA has the capability to provide sophisticated algorithms for satellite remote sensing of precipitation, land use, and in the future, soil moisture. The Workshop sought to initiate discussion among three agencies regarding their specific and highly complimentary capabilities. The fundamental goal of the Workshop was to establish a framework that will leverage the strengths of each agency. Once a prototype system is developed for example, in relatively data-rich Puerto Rim, it could be adapted for use in data-poor, low-infrastructure regions such as the Dominican Republic or Haiti. This paper provides an overview of the Workshop s goals, presentations and recommendations with respect to the development of the HFLC.

Negri, Andrew J.↗

NASA NTRS2007

Land Remote Sensing Overview

A general overview of the USGS land remote sensing program is presented. The contents include: 1) Brief overview of USGS land remote sensing program; 2) Highlights of JACIE work at USGS; 3) Update on NASA/USGS Landsat Data Continuity Mission; and 4) Notes on alternative data sources.

Byrnes, Ray↗

NASA NTRS2007

On the Use of Ocean Color Remote Sensing to Measure the Transport of Dissolved Organic Carbon by the Mississippi River Plume

We investigated the use of ocean color remote sensing to measure transport of dissolved organic carbon (DOC) by the Mississippi River to the Gulf of Mexico. From 2000 to 2005 we recorded surface measurements of DOC, colored dissolved organic matter (CDOM), salinity, and water-leaving radiances during five cruises to the Mississippi River Plume. These measurements were used to develop empirical relationships to derive CDOM, DOC, and salinity from monthly composites of SeaWiFS imagery collected from 1998 through 2005. We used river flow data and a two-end-member mixing model to derive DOC concentrations in the river end-member, river flow, and DOC transport using remote sensing data. We compared our remote sensing estimates of river flow and DOC transport with data collected by the United States Geological Survey (USGS) from 1998 through 2005. Our remote sensing estimates of river flow and DOC transport correlated well (r2 ~ 0.70) with the USGS data. Our remote sensing estimates and USGS field data showed low variability in DOC concentrations in the river end-member (7-11%), and high seasonal variability in river flow (~50%). Therefore, changes in river flow control the variability in DOC transport, indicating that the remote sensing estimate of river flow is the most critical element of our DOC transport measurement. We concluded that it is possible to use this method to estimate DOC transport by other large rivers if there are data on the relationship between CDOM, DOC, and salinity in the river plume.

DelCastillo, Carlos E.↗

NASA NTRS2008

The Chesapeake Bay Impact Crater: An Educational Investigation for Students into the Planetary Impact Process and its Environmental Consequences

Planetary impact craters are a common surface feature of many planetary bodies, including the Earth, the Moon, Mars, Mercury, Venus, and Jupiter s moons, Ganymede and Callisto. The NASA Langley Research Center in Hampton, VA, is located about 5 km inside the outer rim of the Chesapeake Bay Impact Crater. The Chesapeake Bay Impact Crater, with a diameter of 85 km is the sixth largest impact crater on our planet. The U.S. Geological Survey (USGS), in collaboration with the NASA Langley Research Center, the Virginia Department of Environmental Quality (VDEQ), the Hampton Roads Planning District Commission (HRPDC), and the Department of Geology of the College of William and Mary (WM) drilled into and through the crater at the NASA Langley Research Center and obtained a continuous core to a depth of 2075.9 ft (632.73 meters) from the Chesapeake Bay Impact Crater. At the NASA Langley location, the granite basement depth was at 2046 ft (623.87 meters). This collaborative drilling activity provided a unique educational opportunity and ongoing educational partnership between USGS, NASA Langley and the other collaborators. NASA Langley has a decade-long, ongoing educational partnership with the Colonial Coast Council of the Girl Scouts. The core drilling and on site analysis and cataloguing of the core segments provided a unique opportunity for the Girl Scouts to learn how geologists work in the field, their tools for scientific investigation and evaluation, how they perform geological analyses of the cores in an on-site tent and learn about the formation of impact craters and the impact of impacting bodies on the sub-surface, the surface, the oceans and atmosphere of the target body. This was accomplished with a two-part activity. Girl Scout day camps and local Girl Scout troops were invited to Langley Research Center Conference Center, where more than 300 Girl Scouts, their leaders and adult personnel were given briefings by scientists and educators from the USGS, NASA, VDEQ, HRPDC and WM on the principles of geology, the formation of impact craters, the consequences of the impacting body on the atmosphere, ocean, surface and sub-surface, the geological, chemical and biological analyses of the core and the cataloguing and storage of the core segments, etc. After the briefings, the Girl Scouts visited the drilling site where they inspected the core drilling rig, examined the core samples and discussed the drilling procedures, cores and interpretation of the cores with scientists and educators from the organizations conducting the core drilling. Demonstrations at the drilling site included demonstrations of impacting objects hitting multi-colored layered mud targets at different angles of entry. The multi-colored layers of mud were instructive in mapping out the distribution of impact-ejected material around the impact crater. The presentation will include a series of photographs of the Girl Scout participating in activities at the Chesapeake Bay Impact Crater drill site, including retrieving cores from the drilling rig, inspecting the core samples and participating in the impact-crater formation demonstrations.

Levine, Arlene S.↗

NASA NTRS2011

The Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) on the Landsat Data Continuity Mission (LDCM)

The Landsat Data Continuity Mission (LDCM), a joint NASA and United States Geological Survey (USGS) mission, is scheduled for launch in December, 2012. The LDCM instrument payload will consist of the Operational Land Imager (OLI), provided by Ball Aerospace and Technology Corporation (BATC) under contract to NASA and the Thermal Infrared Sensor (TIRS), provided by NASA's Goddard Space Flight Center (GSFC). This paper will describe the design, capabilities and status of the OLI and TIRS instruments. The OLI will provide 8 channel multispectral images at a spatial resolution of 30 meters and panchromatic images at 15 meter spatial resolution. The TIRS is a 100 meter spatial resolution push-broom imager whose two spectral channels, centered at 10.8 and 12 microns, split the ETM+ thermal bands. The two channels allow the use of the "split-window" technique to aid in atmospheric correction. The TIRS focal plane consists of three Quantum Well Infrared Photodetector (QWIP) arrays to span the 185 km swath width. The OLI and TIRS instruments will be operated independently but in concert with each other. Data from both instruments will be merged into a single data stream at the (USGS)/Earth Resources Observation and Science (EROS) facility. The ground system, being developed by USGS, includes an Image Assessment System (lAS), similar to Landsat-7's, to operationally monitor, characterize and update the calibrations of the two sensors.

Reuter, Dennis↗

NASA NTRS2015

Assessing Compliance with United States Government Orbital Debris Mitigation Guidelines

There are currently no exceptions or special considerations for CubeSats in the United States Government (USG) Orbital Debris (OD) Mitigation Guidelines. For all objects launched into space the 2010 United States Space Policy requires that any failure to comply with the USG OD Mitigation Guidelines requires approval by the head of the launching agency. In addition it requires that the US Secretary of State be notified of any non‐compliance. For these reasons it is important that missions consider these policies during their design phase. This paper will discuss methods to assess compliance with USG OD mitigation guidelines as they apply to CubeSat missions using tools such as the NASA Debris Assessment Software (DAS).

Kelley, R. L.↗

DOE OSTI2020

Magnetotelluric Data from Mountain Home, ID

This dataset includes magnetotelluric transfer functions in the form of EDI files for 16 stations collected by the USGS and 40 stations collected by Quantec Geoscience for Lawerence Berkeley National Lab around the Mountain Home area in Idaho. A 3D electrical resistivity model is included that images resistive and conductive bodies in the subsurface that maybe important for geothermal characterization. The model was created using ModEM using the high performance computer Yeti at the USGS.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

GeoDAWN West Central Nevada EarthMRI Data

This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Western Nevada. The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation Program (3DEP), Department of Energy Geothermal Technologies Office, Natural Resources Conservation Services, and Bureau of Land Management have partnered to conduct airborne geophysical and 3DEP lidar surveys over parts of Nevada and California to collect information on undiscovered geothermal, critical mineral, and groundwater resources in the western Great Basin and the Walker Lane region.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

GeoDAWN Northwestern Elko County Nevada EarthMRI Data

This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Northwestern Elko County, Nevada. The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation Program (3DEP), Department of Energy Geothermal Technologies Office, Natural Resources Conservation Services, and Bureau of Land Management have partnered to conduct airborne geophysical and 3DEP lidar surveys over parts of Nevada and California to collect information on undiscovered geothermal, critical mineral, and groundwater resources in the western Great Basin and the Walker Lane region.

15 GEOTHERMAL ENERGY↗

NASA NTRSDate not supplied

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

NASA NTRSDate not supplied

GeoAI Advances in Specific Landform Mapping

machine learning↗

DOE OSTI2022

RAPID UNSEPARATED RARE EARTH ELEMENT ANALYSES BY ISOTOPE DILUTION MULTICOLLECTOR INDUCTIVELY COUPLED MASS SPECTROMETRY (ID-MC-ICP-MS)

We present a method for analyzing rare earth elements (REEs) by isotope dilution without separation of individual elements. Utilizing a Nu Plasma 2 multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS) equipped with an Aridus II desolvation nebulizer, sample introduction tuning parameters (torch position, gas flows) were investigated and used to minimize oxide formation (e.g., NdO/Nd <0.05%) and remove the need to analyze the REEs as separated “cuts.” Ratios for spike/sample isotopes in mixed synthetic standards containing varying amounts of Ce, Nd, Sm, Eu, Gd, Dy, Er, and Yb were measured accurately within 1% of IUPAC values. La and Lu in the standards were more than 2% off from expected values due to more demanding interference corrections. A USGS BCR-2 rock standard was also processed with flux fusion, iron coprecipitation and a single column pass bulk separation followed by analysis. The concentrations for Ce, Nd, Sm, Eu, Dy, Er, and Yb fell within 2% of consensus values. A United States Geological Survey (USGS) BIR-1A rock standard was also processed in triplicate by hydrofluoric and nitric acid digestion, yielding rare earth concentrations within 3% of consensus values with 0.3% relative standard deviation (n=3). This demonstrates the ability to produce high quality REE patterns of comparable quality to traditional methods involving labor and time intensive REE separation, with sample preparation and analytical times that are comparable to analyses against isotope dilution by single-collector ICP-MS.

Shen, Steve D.↗

DOE OSTI2021

High-precision measurement of U-Pu-Np-Am concentrations and isotope ratios in environmental reference materials by mass spectrometry

Herein, we report results of precise and sensitive mass spectrometric measurements of uranium, plutonium, neptunium, and americium concentrations and isotope ratios in a variety of environmental reference materials. Most of our work has been done on NIST SRM 4350b, River Sediment, but we also present results for NIST SRM 4354, Lake Sediment; NIST SRMs 4355 and 4355a, Peruvian Soil; NIST SRM 4357, Ocean Sediment; NIST SRM 1648a, Urban Particulate Material; NIST SRM 1649b, Urban Dust; IAEA CRM 385, Ocean Sediment; USGS BCR-2, Columbia River Basalt; and USGS BHVO-2, Hawaiian Volcanic Observatory Basalt. These materials reflect a wide range in long-lived actinide concentrations (e.g. 1E4 to 1E10 atoms 239 Pu/g) and isotope ratios. Measurements were performed in a clean laboratory by isotope dilution, multi-collector thermal ionization and multi-collector inductively coupled plasma mass spectrometry. In general, our results are in agreement with, but lower the uncertainty of, literature or certificate values for these reference materials. Our uranium results for the basalts also confirm previously reported high-precision mass spectrometric results from our laboratory. In many cases our measurements of U-Pu-Np-Am nuclides appear to be novel.

58 GEOSCIENCES↗

DOE OSTI2025

Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Two-dimensional hydrodynamic flood models are commonly employed for simulating flood extent and inundation depth. However, the influence of urban drainage network (UDN) is frequently overlooked in these models, potentially compromising their accuracy. Furthermore, the expensive computational costs and longer processing times make them challenging for large-scale hydrodynamic simulation. To address these challenges, this paper develops a machine learning (ML)-driven emulator for an open-source flood model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). A TRITON-ML Emulator (TR-Emulator) that utilizes Convolutional Long Short-Term Memory is developed to capture the spatiotemporal features of flood events based on the outputs from TRITON. We further enhance the emulator by integrating UDN parameters (TR-UDN), such as the flow capacity of drainage pipes, pipe size, and pipe length, via an ML stacking technique to improve the water surface elevation (WSE) simulation. Hurricane Harvey 2017 in Houston, TX is used as the case study. We compare WSE results from TRITON, TR-Emulator, TR-UDN, and the United States Geological Survey (USGS) observations to evaluate the performance of these models. The results indicate that the TR-Emulator effectively replicates the WSE simulated by TRITON. Additionally, TR-UDN performs well in capturing WSE patterns and peak flows, aligning more closely with USGS observations, except in areas with milder slopes where conveyance discrepancies are observed. We further test the generalizability of our ML-based models using another smaller event. This paper shows that the TR-Emulator is effective for users and engineers to emulate a 2D hydrodynamic model, and the enhanced version of the TR-Emulator, TR-UDN, can be an efficient tool for predicting WSEs during urban flooding.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Innovative high-temperature ammonium bifluoride fusion and rapid analysis of elements with nuclear forensic value

High-temperature ammonium bifluoride (ABF) fusions were evaluated for potential use in rapid dissolution of post-detonation nuclear debris. The ABF fusion was carried out in a Pt crucible which allowed evaluation of higher fusion and evaporation temperatures. The high-temperature ABF fusion dissolution method was evaluated using geological reference materials: USGS QLO-1a Quartz Latite, USGS SDC-1 Mica Schist, and NIST 278 Obsidian Rock. The optimized dissolution method involved a 10 min fusion at 540 °C, a 5 min reflux in 8 M HNO 3 , an evaporation at 300 °C and final dilution into 45 mL of 2% (v/v) HNO3. The final solution was filtered after heating at 105 °C using a hotblock. This dissolution method was simple, requiring only a hotplate or hotblock, filtered samples were available for ICP-MS analysis or radiochemical separation within 150 min, and was found to have high (>90%) recovery for many isotopes of interest in nuclear forensics applications. U and Pu in the dissolved material was separated using TEVA and UTEVA extraction chromatography columns, a process which resulted in >90% recovery. An irradiated U tracer was spiked into the material prior to dissolution and analyzed for recovery of major fission products and 239Np. The monitored radionuclides had recoveries of greater than 90%, except for the volatile radioiodine isotopes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗