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At least 1,135 records · Page 63

Multiscale maps of Active Layer Depth for Teller site Mile Marker 27 and Kougarok Mile Marker 80, Seward Peninsula, AK

Remote sensing maps of active layer depth derived from Unmanned Areal System (UAS) data. The UAS datasets were stepwise scaled until matching the AVIRIS-NG (Airborne Visible / Infrared Imaging Spectrometer - Next Generation) and Sentinel-2 spatial resolutions. Using the field observed Active Layer Depth (ALD) measurement in combination with spectral and topographic predictors derivatives from DJI UAS imagery, we used a spatially explicit RF regression model to predict and map ALD across our study landscapes. This package includes maps for Next-Generation Ecosystem Experiment Arctic (NGEE Arctic)’s Teller Mile Marker (MM) 27, and Kougarok MM80 (aka Mile 80) watersheds. The field, map data, and metadata are provided as geoTIF and text (*.csv) formats. These datasets are provided in support of Hantson et al., 2024 (accepted) “Scaling Arctic landscape and permafrost features improves active layer depth modeling”

54 ENVIRONMENTAL SCIENCES↗

Convolutional Neural Network Approach for Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion

Accurate and high-resolution maps of vegetation are critical for projects seeking to understand the terrestrial ecosystem processes and land-atmosphere interactions in Arctic ecosystems, such as U.S. Department of Energy's Next Generation Ecosystem Experiment (NGEE) Arctic. However, most existing Arctic vegetation maps are at a coarse resolution and with a varying degree of detail and accuracy. Remote sensing-based approaches for mapping vegetation, while promising, are challenging in high latitude environments due to frequent cloud cover, polar darkness, and limited availability of high-resolution remote sensing datasets (e.g., ~ 5 m). This study proposes a new remote sensing based multi-sensor data fusion approach for developing high-resolution maps of vegetation in the Seward Peninsula, Alaska. We focus detailed analysis and validation study around the Kougarok river, located in the central Seward Peninsula of Alaska. We seek to evaluate the integration of hyper-spectral, multi-spectral, radar, and terrain datasets using unsupervised and supervised classification techniques over a ~343.72 km 2 area for generating vegetation classifications at a variety of resolutions (5 m and 12.5 m). We fist applied a quantitative goodness-of-fit method, called Mapcurves, that shows the degree of spatial concordance between the public coarse resolution maps and k-means clustering values and relabels the k values based on the best overlap. We develop a convolutional neural network (CNN) approach for developing high resolution vegetation maps for our study region in Arctic. We compare two CNN approaches: (1) breaking up the images into small patches (e.g., 6 × 6) and predict the vegetation class for entire patch and (2) semantic segmentation and predict the vegetation class for every pixel. We also perform accuracy assessments of the developed data products and evaluate varying CNN architectures. The fusion of hyperspectral and optical datasets performed the best, with accuracy values increased from 0.64 to 0.96-0.97 when using a training map produced by unsupervised clustering and Mapcurves labeling for both CNN models.

Langford, Zach↗

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗

Investigating the Effects of Mixing Dynamics on Twin-Screw Granule Quality Attributes via the Development of a Physics-Based Process Map

Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing dynamics on the granule quality attributes (PSD, content uniformity, and microstructure). Mixing is an important dynamic process that simultaneously occurs along with the granulation rate mechanisms during the wet granulation process. An improved mechanistic understanding was achieved by identifying and quantifying the physically relevant intermediate parameters that affect the mixing dynamics in TSG, and then their effects on the granule attributes were analyzed by investigating their effects on the granulation rate mechanisms. The fill level, granule liquid saturation, extent of nucleation, and powder wettability were found to be the key physically relevant intermediate parameters that affect the mixing inside the twin-screw granulator. An improved geometrical model for the fill level was developed and validated against existing experimental data. Finally, a process map was developed to depict the effects of mixing on the temporal and spatial evolution of the materials inside the twin-screw granulator. This process map illustrates the mechanism of nucleation and the growth of the granules based on the fundamental material properties of the primary powders (solubility and wettability), liquid binders (viscosity), and mixing dynamics present in the system. Furthermore, it was shown that the process map can be used to predict the granule product quality based on the granule growth mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Onboard Data Analysis for the Planetary Instrument for X-Ray Lithography

Imaging spectrometers are invaluable instruments for robotic science exploration, enabling quantitative maps of physical and chemical properties at high spatial resolution. This is particularly valuable in remote missions to other planetary bodies like Mars. The PIXL instrument on the Mars 2020 rover will deploy an arm-mounted X-Ray fluorescence spectrometer to map chemical composition at sub-millimeter scales. Its high resolution places dramatic new demands on instrument placement accuracy and measurement time. We address these challenges using novel on board data analysis strategies inspired by FRC science autonomy research.

Thompson, David R.↗

Ensemble Estimation of Historical Evapotranspiration for the Conterminous U.S.

Abstract Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall‐to‐wall explanatory variable maps to generate CONUS‐wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national‐scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.

Environmental Sciences & Ecology↗

Daily Global Mapping of Mars Ozone Column Abundances with MARCI UV Band Imaging

Since November of 2006, The Mars Color Imager (MARCI) onboard the Mars Reconnaissance Orbiter (MRO) has obtained multiple-filter daily global images of Mars centered upon a local time (LT) of 3 pm. Ultraviolet imaging bands placed within (260 nm) and longward (320 nm) of Hartley band (240-300 nm) ozone (O3) absorption support retrievals of atmospheric ozone columns, with detection limits (approximately 1 micrometer-atm) appropriate to mapping elevated O3 abundances at low latitudes around Mars aphelion, and over mid-to-high latitudes during fall/winter/spring seasons. MARCI O3 maps for these regions reveal the detailed spatial (approximately 1 deg lat/long, for 8 x 8 pixel binned resolution) and temporal (daily, with substantial LT coverage at pole) behaviors of water vapor saturation conditions that force large variations in water vapor photolysis products (HOx-OH, HO2, and H) responsible for the catalytic destruction of O3 in the Mars atmosphere. A detailed description of the MARCI O3 data set, including measurement and retrieval characteristics, is provided in conjunction with comparisons to Mars Express SPICAM ozone measurements (Perrier, S. et al. [2006]. J. Geophys. Res. (Planets) 111) and LMD GCM simulated O3 abundances (Lefevre, F. [2004]. J. Geophys. Res. (Planets) 109). Presented aspects of the MARCI ozone mapping data set include aphelion increases in low latitude O3, dynamically evolving high latitude O3 maxima associated with planetary waves and weather fronts during northern early spring, and distinctive winter/spring O3 and CO increases within the Hellas Basin associated with transport of condensation enhanced south polar air mass. Comparisons of coincident MARCI measurements and LMD simulations for ice cloud and O3 columns are considered in the context of potential heterogeneous photochemical processes (Lefevre, F. [2008]. Nature 454, 971-975), which are not strongly evidenced in the MARCI observations. Modest interannual variations are exhibited, most notably a 20% reduction in aphelion low latitude O3 columns following the 2007 perihelic global dust storm.

Clancy, R. Todd↗

Einstein observations of selected regions of the Cygnus Loop

The imaging proportional counter on the Einstein X-ray Observatory is used to obtain high quality soft X-ray maps of two 40 x 40 arcmin regions of the Cygnus Loop. One region covers the western shock front; the other is centered on the southern diffuse extension. After careful correction for background and detector gain variations these two regions were subdivided for X-ray spectral analysis. In both cases the spectra of the brightest X-ray emitting areas are characterized by temperatures of about 2 million K, whereas the spectra of the fainter diffuse regions are indicative of higher temperatures (T greater than about 4 million K) and suggest the presence of a second, hard component. These results, together with the correlation of the X-ray spatial distribution with the optical and radio maps, are discussed in terms of current models of supernova remnant evolution. The evidence suggests that the Cygnus Loop is the result of a Type II supernova of a star of initial mass of less than about 20 solar masses.

Charles, P. A.↗

THE GINI COEFFICIENT AS A MORPHOLOGICAL MEASUREMENT OF STRONGLY LENSED GALAXIES IN THE IMAGE PLANE

Characterization of the morphology of strongly lensed galaxies is challenging because images of such galaxies are typically highly distorted. Lens modeling and source plane reconstruction is one approach that can provide reasonably undistorted images from which morphological measurements can be made, though at the expense of a highly spatially variable telescope point-spread function (PSF) when mapped back to the source plane. Unfortunately, modeling the lensing mass is a time- and resource-intensive process, and in many cases there are too few constraints to precisely model the lensing mass. If, however, useful morphological measurements could be made in the image plane rather than the source plane, it would bypass this issue and obviate the need for a source reconstruction process for some applications. We examine the use of the Gini coefficient as one such measurement. Because it depends on the cumulative distribution of the light of a galaxy, but not the relative spatial positions, the fact that surface brightness is conserved by lensing means that the Gini coefficient may be well preserved by strong gravitational lensing. Through simulations, we test the extent to which the Gini coefficient is conserved, including by effects due to PSF convolution and pixelization, to determine whether it is invariant enough under lensing to be used as a measurement of galaxy morphology that can be made in the image plane.

79 ASTRONOMY AND ASTROPHYSICS↗

Martian spectral units derived from ISM imaging spectrometer data

Based on results of the Viking mission, the soil layer of Mars has been thought to be fairly homogeneous and to consist of a mixture of as few as two components, a 'dark gray' basaltic material and a 'bright red' altered material. However, near-infrared reflectance spectra measured recently both telescopically and from spacecraft indicate compositional heterogeneity beyond what can be explained by just two components. In particular, data from the ISM imaging spectrometer, which observed much of the equatorial region at a spatial resolution of approximately 22 km, indicate spatial differences in the presence and abundance of Fe-containing phases, hydroxylated silicates, and H2O. The ISM data was used to define, characterize, and map soil 'units' based on their spectral properties. The spatial distribution of these 'units' were compared to morphologic, visible color, and thermal inertia features recognized in Viking data.

Murchie, S.↗

Improving Chirped Fiber Bragg Grating Resolution for Position-Sensitive Sensors in Shock- and Detonation-Driven Experiments

Chirped fiber Bragg gratings (CFBGs) are robust diagnostic sensors that are widely used to track detonation-driven and shock wave propagation. CFBGs are inscribed with a linearly chirped periodic index of refraction changes that alter the Bragg wavelength along the length of the probe. The light return of each individual Bragg element is captured by a detector at a unique time to map the full reflected spectrum. The CFBG spectrum is measured with a dispersive Fourier transform of the reflected light that temporally stretches the spectrum to increase spatial resolution and make a one-to-one map of the wavelength on a time axis. Here, we propose an improvement of CFBG temporal resolution by incorporating two co-linear laser pulses with orthogonal polarization states and a 5 ns time offset. The two separate signals were split and tracked by two separate detectors. An oscilloscope captured good separation in the signals, and two separate spectrograms were generated and interleaved in the post-processing of the data. This novel technique doubled the CFBG temporal resolution and led to a doubled location resolution. As a proof-of-concept of this technique, the resolution improvement was compared between standard CFBG measurements and the two polarization states method on a position-sensitive CFBG sensor. CFBG resolution doubling will advance sensor capabilities and will have a direct impact on improving capture and analysis in dynamic, high-explosive experiments.

42 ENGINEERING↗

Satellite Power System (SPS) mapping of exclusion areas for rectenna sites

The areas of the United States that were not available as potential sites for receiving antennas that are an integral part of the Satellite Power System concept are presented. Thirty-six variables with the potential to exclude the rectenna were mapped and coded in a computer. Some of these variables exclude a rectenna from locating within the area of its spatial influence, and other variables potentially exclude the rectenna. These maps of variables were assembled from existing data and were mapped on a grid system.

Blackburn, J. B., Jr.↗

Geometric accuracy of LANDSAT-4 MSS image data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CCT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 x 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSATS -1, -2 and -3.

Welch, R.↗

Geometric Accuracy of LANDSAT-4 MSS Image Data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CTT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 by 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSAT-1, -2 AND -3.

Welch, R.↗

Lunar Reconnaissance Orbiter (LRO): Observations for Lunar Exploration and Science

The Lunar Reconnaissance Orbiter (LRO) was implemented to facilitate scientific and engineering-driven mapping of the lunar surface at new spatial scales and with new remote sensing methods, identify safe landing sites, search for in situ resources, and measure the space radiation environment. After its successful launch on June 18,2009, the LRO spacecraft and instruments were activated and calibrated in an eccentric polar lunar orbit until September 15, when LRO was moved to a circular polar orbit with a mean altitude of 50 km. LRO will operate for at least one year to support the goals of NASA's Exploration Systems Mission Directorate (ESMD), and for at least two years of extended operations for additional lunar science measurements supported by NASA's Science Mission Directorate (SMD). LRO carries six instruments with associated science and exploration investigations, and a telecommunications/radar technology demonstration. The LRO instruments are: Cosmic Ray Telescope for the Effects of Radiation (CRaTER), Diviner Lunar Radiometer Experiment (DLRE), Lyman-Alpha Mapping Project (LAMP), Lunar Exploration Neutron Detector (LEND), Lunar Orbiter Laser Altimeter (LOLA), and Lunar Reconnaissance Orbiter Camera (LROC). The technology demonstration is a compact, dual-frequency, hybrid polarity synthetic aperture radar instrument (Mini-RF). LRO observations also support the Lunar Crater Observation and Sensing Satellite (LCROSS), the lunar impact mission that was co-manifested with LRO on the Atlas V (401) launch vehicle. This paper describes the LRO objectives and measurements that support exploration of the Moon and that address the science objectives outlined by the National Academy of Science's report on the Scientific Context for Exploration of the Moon (SCEM). We also describe data accessibility by the science and exploration community.

Vondrak, Richard↗

Simultaneous Boundary-Layer Transition, Tip Vortex, and Blade Deformation Measurements of a Rotor in Hover

This paper describes simultaneous optical measurements of a sub-scale helicopter rotor in the U.S. Army Hover Chamber at NASA Ames Research Center. The measurements included thermal imaging of the rotor blades to detect boundary layer transition; retro-reflective background-oriented schlieren (RBOS) to visualize vortices; and stereo photogrammetry to measure displacements of the rotor blades, to compute spatial coordinates of the vortices from the RBOS data, and to map the thermal imaging data to a three-dimensional surface grid. The test also included an exploratory effort to measure flow near the rotor tip by tomographic particle image velocimetry (tomo PIV)an effort that yielded valuable experience but little data. The thermal imaging was accomplished using an image-derotation method that allowed long integration times without image blur. By mapping the thermal image data to a surface grid it was possible to accurately locate transition in spatial coordinates along the length of the rotor blade.

Rotorcraft↗

Comparing Level-2 and Level-3 Satellite Ocean Color Retrieval Validation Methodologies

Many ocean color data applications leverage global spatially composited Level-3(L3) satellite data, because of their regular Earth-grid frame of reference. However, ocean color satellite retrieval performance is routinely evaluated on Level-2 (L2) data at the native satellite swath resolution and geometries. This study assesses how accurately binned and gridded L3 data represent L2 satellite data products via satellite-to-in situ match-up activities.L2 and L3 satellite data retrievals of the photosynthetic pigment chlorophyll-a are compared with a common in situ data set, revealing similar L2 and L3 satellite-to-in situ performance for both MODIS-Aqua and VIIRS-SNPP. This agreement implies that L2 validation results are generally applicable to L3 data. However, uncertainties are introduced during the generation of L3 data from L2 data. L3 data comparisons introduce a wider temporal window between the time of in situ measurement and the time of the satellite observation, which can unintentionally reflect on the quality of the satellite retrieval or algorithm performance. The choice of L3 map projection may introduce additional uncertainty by spatially distorting the true location of the satellite retrievals. Each manipulation of satellite data beyond theinstrument's native spatio temporal reference (L2) reduces the applicability of L2 validation results to higher data processing levels.

Ocean Color↗

Temperature Correction of Pressure-Sensitive Paints Simplified

Pressure-sensitive paint (PSP) has become a useful tool to augment conventional pressure taps in measuring the surface pressure distribution of aerodynamic components in wind tunnel testing. Although PSP offers the advantage of nonintrusive global mapping of the surface pressure, one prominent drawback to the accuracy of this technique is the inherent temperature sensitivity of PSP's luminescent intensity. Typical aerodynamic surface PSP tests rely on the coated surface to be both spatially and temporally isothermal, along with conventional instrumentation, to yield the highest accuracy pressure mappings. In some tests, however, spatial and temporal thermal gradients are generated by the nature of the test, as in a blowing jet impinging on a surface. In these cases, high accuracy and reliable data cannot be obtained unless the temperature variations on the painted surface are accounted for. A new temperature-correction technique was developed at the NASA Glenn Research Center at Lewis Field to collapse a "family" of PSP calibration curves to a single curve of intensity ratio versus pressure. This correction allows a streamlined procedure to be followed whether or not temperature information is used in the data reduction of the PSP.

Bencic, Timothy J.↗