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Griffin, Robert

Publications and source records attributed to Griffin, Robert.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Diamond rotors

The resolution of magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectra remains bounded by the spinning frequency, which is limited by the material strength of MAS rotors. Since diamond is capable of withstanding 1.5–2.5x greater MAS frequencies, compared to state-of-the art zirconia, we fabricated rotors from single crystal diamond. When combined with bearings optimized for spinning with helium gas, diamond rotors could achieve the highest MAS frequencies to date. Furthermore, the excellent microwave transmission properties and thermal conductivity of diamond could improve sensitivity enhancements in dynamic nuclear polarization (DNP) experiments. The fabrication protocol we report involves novel laser micromachining and produced rotors that presently spin at ω r = 111.000 ± 0.004 kHz, with stable spinning up to 124 kHz, using N 2 gas as the driving fluid. Here, we present the first proton-detected 13 C/ 15 N MAS spectra recorded using diamond rotors, a critical step towards studying currently inaccessible ex-vivo protein samples with MAS NMR. Previously, the high aspect ratio of MAS rotors (~10:1) precluded fabrication of MAS rotors from diamond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

TRACER-MAP AMS Measurement

Aerosol composition was measured by using the high resolution time-of-flight aerosol mass spectrometer (HR ToF-AMS). The data were collected at five different sites (AMF1, Aldine, University of Houston (UH), Jones Forest (JF), San Jacinto Battleground (BG)) from July to August, 2022. Dataset includes time series of five species of aerosol composition: Organic, sulfate (SO4), nitrate (NO3), ammonium (NH4), chlorine (Chl)

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Evaluating Drought Indices for Early Warning in East and Southern Africa

Sparsely populated regions of east and southern Africa often have little ground based data to monitor drought, crops, and water resources. The Regional Hydrologic Extremes Assessment System (RHEAS) is a NASA supported data assimilation framework that combines both a hydrologic and crop model, which provide another monitoring approach. RHEAS can also be run in forecast mode, providing outlook on drought and crop yield.

Miller, Sara↗
NASA NTRS2020

Developing a Customized Composite Drought Index for Pakistan

Pakistan experiences frequent and intense agricultural drought, varying spatially and temporally. Prolonged dry conditions often result in failed crop production. Using multiple variables, different components of drought can be captured across a multitude of climatic zones and throughout different seasons. Developing a composite drought index (CDI), specific for each district, will provide a more complete view of agricultural drought and enhance early warning systems.

Schwartz, Caily↗
NASA NTRS2020

Evaluating Flood Forecasting System Performance in Cambodia

Every year, Cambodia experiences flooding as a result of monsoon rains and typhoons. Flood forecasting systems are designed to enable people to mitigate economic and social impacts from these events. However, in order for forecasts to be used effectively, an assessment of their accuracy is needed. This study demonstrates the performance of regional and global flood forecasting systems over the 2019 flood season. To do this, we assess the flood forecast accuracy at different forecast lead times and gauge locations in Cambodia. We then compare the flood forecast performance to satellite-based flood maps produced by the Hydrological Remote Sensing Analysis of Floods (HYDRAFloods) tool currently being co-developed by SERVIR-Mekong in collaboration with the Myanmar Department of Disaster Management. This assessment of the flood forecasting systems’ performance and comparison to flood extents helps (1) provide valuable information to forecasters and disaster managers as they make improvements to their models, and (2) provides support to forecast users as they evaluate the strengths and weaknesses of different systems for taking action.

Nauman, Claire↗
NASA NTRS2019

Assessing the Use of SAR/Optical Data Fusion and TensorFlow for Improved Mangrove Mapping

Mangrove forests are found in intertidal zones of tropical regions around the world and provide important ecological and economic benefits – they are considered carbon sequesters, habitats for flora and fauna, and natural barriers to hurricanes and tsunamis. Wood from mangrove forests are used as fuel and building materials in surrounding coastal communities, therefore promoting local livelihoods. Despite the importance of these ecosystems, mangrove forests have historically been degraded in natural processes such as severe weather, and anthropogenic factors like conversion to agriculture and aquaculture. This study assesses change in mangrove forests in Nigeria and Mozambique from 2015 to 2018 using SAR and optical data fusion. Due to frequent cloud cover over the study area, SAR and optical data is fused to obtain gap-free imagery without clouds. Landsat-8 OLI and Sentinel-1 imagery is fused with TensorFlow, an open source platform used in developing machine learning models. The resulting images are classified to discriminate mangrove forest cover from other land cover types, and change is estimated using image differencing. Understanding the rates and magnitude of mangrove change across space and time can aid in identifying priority areas for forest regeneration, and can help construct sustainable management practices for the future.

Strattman, Katherine↗
NASA NTRS2019

Evaluating Flood Forecasting System Performance in Cambodia During the 2019 Flood Season

Every year, Cambodia experiences both flash and prolonged riverine flooding as a result of monsoon rains and typhoons. Floods occur frequently in various parts of the region, and result in significant economic cost. Flood forecasting systems are designed to mitigate economic and social impacts, enabling people to prepare for extreme events. However, in order for forecasts to be used effectively, an assessment of the available forecasting systems is needed. In addition, following the onset of flooding, satellite imagery is used to generate flood maps to aid in response efforts. This study demonstrates the performance of regional and global flood forecasting systems over the 2019 flood season. To do this, we assess the flood forecast accuracy at different forecast lead times through a series of forecast verification metrics at gauge locations in Cambodia. We then compare the flood forecast performance to Sentinel 1 flood maps produced by the Hydrological Remote Sensing Analysis of Floods (HYDRAFloods) tool currently being co-developed by SERVIR-Mekong in collaboration with the Myanmar Department of Disaster Management. This assessment of the flood forecasting systems’ performance and comparison to generated flood maps helps provide context to forecasters and disaster managers as they make improvements to their models. Additionally, these results provide support to forecast users as they evaluate the strengths and weaknesses of different systems for taking action.

Nauman, Claire M.↗
DOE OSTI2019

A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams

This article outlines a semi-autonomous approach for using a fusion of light detection and ranging (LiDAR) and optical remote sensing data to identify and measure small impoundments (SIs) and their dams. Quantifying such water bodies as hydrologic network features is critical for ecosystem and species conservation, emergency management, and water resource planning; however, such features are incompletely mapped at national and state levels. By merging an airborne LiDAR-derived point cloud with a normalized water index using airborne optical imagery we demonstrate an improvement upon single-source methods for identifying these water bodies; classification accuracies increased over 10% by using this multi-source fusion method. Furthermore, the method presented here illustrates a cost-effective pathway to improve the National Inventory of Dams (NID) and includes a framework for estimating dam heights, with results showing strong correlations between derived dam heights and those recorded in the NID (r=.78). With the steady increase in available LiDAR coverage, the 87,000+ dams in the NID could be updated using this technique, a method which could also be expanded for global inventories of SIs and dams.

47 OTHER INSTRUMENTATION↗
NASA NTRS2019

Alternative Datasets for Identification of Earth Science Events and Data

Alternative, or non-traditional, data sources can be used to generate datasets which can in turn be analyzed for temporal, spatial and climatological patterns. Events and case studies inferred from the analysis of these patterns can be used by the remote sensing community to more effectively search for Earth observation data. In this paper, we present a new alternative Earth science dataset created from the National Weather Service’s Area Forecast Discussion (AFD) documents. We then present an exploratory methodology for identifying interesting climatological patterns within the AFD data and a corresponding motivating example as to how these data and patterns can be used to search for relevant events or case studies.

Alternative data↗
NASA NTRS2019

Alternative Datasets for Identification of Earth Science Events and Data

Alternative, or non-traditional, data sources can be used to generate datasets which can in turn be analyzed for temporal, spatial and climatological patterns. Events and case studies inferred from the analysis of these patterns can be used by the remote sensing community to more effectively search for Earth observation data. In this paper, we present a new alternative Earth science dataset created from the National Weather Service’s Area Forecast Discussion (AFD) documents. We then present an exploratory methodology for identifying interesting climatological patterns within the AFD data and a corresponding motivating example as to how these data and patterns can be used to search for relevant events or case studies.

Bugbee, Kaylin↗