Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “raster”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for CN values specific to various land and crop cover types and account for various farming best practices but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and it captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geologic Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

Ella Griffith↗

Riley County Water Resources Project Summary - Comparing Runoff Curve Calculation Methods to Inform Local Resiliency Initiatives in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for land cover-specific CN and account for various farming techniques but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geological Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

DEVELOP Project Summary↗

Utilizing NASA Earth Observations to Evaluate Urban Tree Canopy and Land Surface Temperature for Green Infrastructure Development and Urban Heat Mitigation in Huntsville, AL

Huntsville, Alabama’s population has grown by 10.8% since 2010, due in part to the city’s advancing engineering industry. Rapid urban growth negatively impacts the environment by decreasing tree canopy cover and increasing impervious surface cover, which can intensify the urban heat island effect. To examine the impacts of this urban growth on the environment, the team partnered with the City of Huntsville to utilize Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Space Station’s Global Ecosystems Dynamic Investigation (GEDI) and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). The team utilized these Earth observations in combination with ancillary datasets to create a suite of end products to assist in mitigating the effects of extreme heat due to urban expansion and tree canopy loss. Rasters of annual land surface temperature (LST) was calculated in Google Earth Engine from 2010 to 2019. The team derived land cover classes through supervised and threshold classification methods to distinguish trees, other vegetation types, impervious surfaces, and water. From 2010 to 2019, LST increased approximately 4 °F for all census tracts within the city and the total amount of tree cover increases less than 3%. The findings will aid the city in future decision-making processes by indicating areas that would benefit from increased green infrastructure.

Greta Paris↗

Unveiling Urban Pollution Patterns from a Bird’s-Eye View

Low-earth orbiting satellites have been observing the global distribution of nitrogen dioxide (NO2) since the 1990s and these observations have been used to identify pollution source regions, temporal trends, and links to health effects and community disparities. However, historically, space-based NO2 observations have been coarse in spatial and temporal resolution resulting in challenges in data interpretation and product validation; therefore, NASA developed airborne capabilities and measurements strategies to observe ultraviolet-visible (UV-VIS) trace gases at high temporal and spatial resolutions to unveiling never before seen spatiotemporal patterns over major urban hubs during recent air quality field studies. In this talk, Dr. Judd will share the story of these field studies with datasets collected from NASA’s airborne spectrometers, GeoTASO and GCAS, and how they integrate in with other space- and ground-based instrumentation to illustrate the conceptual model of air quality episodes in coastal urban environments, contribute to satellite validation and regional chemical transport model evaluation. These imagers have the capability to observe UV-VIS absorbing species, typically NO2 and HCHO, at spatial resolutions as fine as 250 m when observing from the upper-troposphere. Flight strategies allowed for the collection of repeated raster samples over urban areas multiple times per flight day in cities like Chicago, Los Angeles, and New York City, capturing never before seen pictures of the diurnal evolution of emissions, chemistry, and meteorology associated with NO2 heterogeneity. These airborne efforts help local air quality management better understand their air quality challenges as well as benefit the larger air quality community in preparation for geostationary air quality observations and the development of the global air quality observing system.

Laura Judd↗

NASA’s Global Imagery Browse Services and Worldview Migrate to Mapbox Vector Tiles: The Drawbacks and Advantages

NASA’s Global Imagery Browse Services (GIBS) is in the process of migrating their vector data from raster tiles to Mapbox Vector Tiles (MVTs). MVTs are becoming ubiquitous in the world of web mapping. Serving data in place of pixels for each feature presents numerous new visualization opportunities as well as various new challenges to overcome. This presentation will cover some of the hardships these teams encountered, the techniques used to overcome those barriers, and it will give you a glimpse at how the user experience was enhanced.

Benjamin King↗

Understanding the Space Weathering of Mercury Through Laboratory Experiments

Introduction: Airless surfaces across the solar system are continually modified by energetic particles from solar wind and micrometeoroid bombardment [1,2]. This process is known as space weathering, and it alters the chemical, microstructural, and optical properties of surface regoliths on airless bodies, including Mercury. On the Moon and S-type asteroids, the reflectance spectral signatures of space weathering include reddening (increasing reflectance with increasing wavelength), darkening (lowering of reflectance), and the attenuation of characteristic absorption bands [2]. Such spectral changes are driven by the production of Fe-bearing nanoparticles(npFe) through both solar wind irradiation and micrometeoroid bombardment. While our understanding of space weathering for the Moon and near-Earth S-types asteroids is advanced, insight into how these processes operate on other planetary bodies is limited. In particular, Mercury experiences a uniquely intense space weathering environment than planetary counterparts at 1 AU, including a moreintense solar wind flux and higher velocity micrometeoroid impacts [4]. Additionally, Mercury has a surface composition unique in the inner solar system, including regions of the surface with very low albedo known as the low reflectance material (LRM), which is enriched in carbon, likely graphite, up to 4wt.% [5].In addition, the concentration of Fe across Mercury’s surface islow (<2 wt.%) compared to the Moonor S-type asteroids asteroids[6]. Our understanding of the effects of space weathering on C-rich and Fe-poor phases is limited. Since Fe plays a critical role inthe development of space weathering characteristicson other airless surfaces(e.g., npFe), its limited availability may significantly affect the development of space weathering features in Mercury surface materials. We can simulate space weathering processes in the laboratory to explore their effects on the microstructural, chemical, and spectral characteristics of Mercury surface materials[7]. Here we used pulsed laser irradiation to simulate the short duration, high-temperature events associated with micrometeoroid impacts. We performed coordinated analyses including reflectance spectroscopy and electron microscopy to investigate the spectral, chemical, and microstructural changes in these mercurian analog samples. Methods: For these experiments, we usedforsteritic olivine with varying FeOcontents, a mineral phase proposed to be abundant on the surface of Mercury. We mixed each sample with graphite to simulate LRM regions of the surface. Wesynthesized the olivinesamplesat 1-bar at NASA’s Johnson Space Centerand prepared pressed powder pellets for laser irradiation [8].We prepared three samples, each with a base layer of olivineto maintain structural integrity and topped witha surface layer containing the graphite-olivine mixture: 1) Sample SC-001 San Carlos olivine(Fo90.91),2)Sample F-S-002 with0.05 wt.% FeO olivine, and 3) F-T-004 with 0.53 wt.% FeO olivine. Each sample was mixed with 5 wt.% powdered graphite and had grain sizes ranging from 45to 125μm. We irradiated each sample usinga pulsed Nd-YAG laser, (l=1064 nm, ~6 ns pulse duration, energy of 48 mJ/pulse) while undervacuumat Northern Arizona University. The laser was rastered1x and then 5x over the surfaceof each sample to simulate progressive space weathering. We collected in situreflectance spectra from the samples after each laser pulse witha Nicolet IS50 Fourier-Transform Infrared spectrometer (lfrom 0.65-2.5 μm). We used an FEI Nova NanoSEM200scanning electron microscope (SEM) and a Hitachi TM4000 Plus benchtop SEM at Purdue University to image the surface morphology and topography of the samples. We extracted thin sections for analysis in the transmission electron microscope(TEM)using the FEI Helios NanoLab 660 focused ion beam (FIB) SEM at the University of Arizona.We performed analysis of the microstructural and chemical characteristics of the samples using the 200 keV JEOL 2500 scanning TEM at Johnson Space Center. Reflectance Spectroscopy Results:Reflectance spectra for each sample are shown in Fig. 1.SC-001:The spectrum of the unirradiated sample exhibits a weak 1.0 μm absorption feature, associated with Fe2+in the olivine,and low overall reflectance (Fig. 1a). Thereflectance and the depth of the absorption band increases after 1x laser raster but are at their lowest after 5x laser rasters.F-T-004:The unirradiated sample has a blue-sloped spectrum with low reflectance without identifiable absorption features (Fig. 1b). With progressive laser irradiation, the sample reflectance increases and becomes strongly red-sloped.F-S-002:The unirradiated sample exhibits a dark, blue-slopedspectrum. The brightness of the sample increases significantly from <0.2average reflectance over >0.8 reflectance in the most irradiated sampleand thespectral slope also becomesslightly reddened (Fig. 1c). Microstructural and Chemical Analysis: Two primary alteration textures were observed in the samples exposed to simulated space weathering: 1) fluffy C-rich,and 2) vesiculated melt. The fluffy C-rich texture is composed oflow-densitydeposits distributed across the surface of the sample(Fig. 2A). Analysis of a FIB section extracted from a low-density C-rich region in sample SC-001 reveals multiple globule-type deposits, discrete from stacked graphite, likely produced via melting from the laser irradiation [9].The vesiculated melt textureis smooth and uniformly distributed across isolated regions of the sample surface. The vesicles measure up to 100s of nmin diameter. Analysis of a FIB section from this texture was extracted from sample F-T-004 reveals a layer of amorphous melt material, close to 100 nm thick and uniform across the FIB section (Fig. 2B). Isolated regions of this melt layer contain small nanoparticles, <5 nm in diameter. Chemical analysis through energy dispersive X-ray spectroscopy reveals the composition of this layer is enriched in Si and depleted in Mg and O compared to the underlying sample. Implications for Space Weathering on Mercury: Previous experiments simulating space weathering of Mercury have showndarkening and reddening of spectra[7,10].However, our use of low-Fe materials and graphite to create a sample set more analogous to the mercurian surface. Our results indicate that sample composition plays a significant and important role in the space weathering of Mercury. In particular, our spectral data demonstrates a strong correlation between spectral slope, Fe content, and simulated space weathering. While the variation in FeO content between samples F-S-002 and F-T-004 is <0.6 wt.%, the spectra deviate from flat to strongly red-sloped(F-T-004). This reddeningmay be linked to the presence of very small nanoparticles observed in the melt textures extracted from sample F-T-004. For the SC-001 sample, the fluffy C-rich textures may be developed by the amalgamation of small graphite particles into these unique morphologies. Such observations indicate that space weathering on Mercury may result in both familiar and new microstructural and chemical characteristics. References: [1]Hapke B. (2001) J. Geophys. Res.-Planet.,106,10039–10073. [2]Pieters C.M. and Noble S.K. (2016) J. Geophys. Res-Planet., 121, 1865–1884. [3] Lucey P.G., and Riner, M.A. (2011) Icarus,212, 451-462.[4]CintalaM.J.(1992)J. Geophys. Res.-Planet.,97,947–973.[5]Klima R.L.et al.(2018)Geophys.Res.Letters, 45, 2945–2953. [6]Nittler L.R., et al. (2011) Science 333, 1847-1850.[7]Sasaki S. and Kurahashi E. (2004) Space weathering on Mercury, Adv.Space Res., 33, 2152-2155.[8] Vander KaadenK.E., et al. (2018) LPSCXLIX, Abstract 1230. [9] McGlaun M.L. et al. (2019) LPSCL, Abstract 2019. [10] TrangD.et al. (2018)LPSCXLIX,Abstract2083

M S Thompson↗

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗

Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA): A Scalable Open Source Method for Land Cover Monitoring Using Data Fusion

The increasing availability of very-high resolution (VHR; <2 m) imagery has the potential to enable agricultural monitoring at increased resolution and cadence, particularly when used in combination with widely available moderate-resolution imagery. However, scaling limitations exist at the regional level due to big data volumes and processing constraints. Here, we demonstrate the Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA), using a suite of open source software capable of efficiently characterizing time-series field-scale statistics across large geographical areas at VHR resolution. We provide distinct implementation examples in Vietnam and Senegal to demonstrate the approach using WorldView VHR optical, Sentinel-1 Synthetic Aperture Radar, and Sentinel-2 and Sentinel-3 optical imagery. This distributed software is open source and entirely scalable, enabling large area mapping even with modest computing power. FARMA provides the ability to extract and monitor sub-hectare fields with multisensor raster signals, which previously could only be achieved at scale with large computational resources. Implementing FARMA could enhance predictive yield models by delineating boundaries and tracking productivity of smallholder fields, enabling more precise food security observations in low and lower-middle income countries.

fusion↗

Landsat Derived Bathymetry of Lakes on the Arctic Coastal Plan of Northern Alaska

The Pleistocene sand sea on the Arctic Coastal Plain (ACP) of northern Alaska is underlain by anancient sand dune field, a geological feature that affects regional lake characteristics. Many of these lakes, whichcover approximately 20 % of the Pleistocene sand sea, are relatively deep (up to 25 m). In addition to the nat-ural importance of ACP sand sea lakes for water storage, energy balance, and ecological habitat, the need forwinter water for industrial development and exploration activities makes lakes in this region a valuable resource.However, ACP sand sea lakes have received little prior study. Here, we collect in situ bathymetric data to test12 model variants for predicting sand sea lake depth based on analysis of Landsat-8 Operational Land Imager(OLI) images. Lake depth gradients were measured at 17 lakes in midsummer 2017 using a Humminbird 798ciHD SI Combo automatic sonar system. The field-measured data points were compared to red–green–blue (RGB)bands of a Landsat-8 OLI image acquired on 8 August 2016 to select and calibrate the most accurate spectral-depth model for each study lake and map bathymetry. Exponential functions using a simple band ratio (withbands selected based on lake turbidity and bed substrate) yielded the most successful model variants. For eachlake, the most accurate model explained 81.8 % of the variation in depth, on average. Modeled lake bathymetrieswere integrated with remotely sensed lake surface area to quantify lake water storage volumes, which rangedfrom 1.056×10−3to 57.416×10−3km3. Due to variations in depth maxima, substrate, and turbidity betweenlakes, a regional model is currently infeasible, rendering necessary the acquisition of additional in situ datawith which to develop a regional model solution. Estimating lake water volumes using remote sensing will fa-cilitate better management of expanding development activities and serve as a baseline by which to evaluatefuture responses to ongoing and rapid climate change in the Arctic. All sonar depth data and modeled lakebathymetry rasters can be freely accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) andhttps://doi.org/10.18739/A2HT2GC6G (Simpson, 2019), respectively.

Claire E Simpson↗

What would it take to manufacture perovskite solar cells in space?

Imagine, astronauts land on the moon. They verify their arrival with mission control, and perform system checks and validations. After the dust settles, they open the airlock of the landing vehicle and venture outside. A side hatch opens, and a flexible substrate slowly unfurls on a boom. A series of printer heads raster, hovering over the substrate and sequentially vapor-depositing the constituent layers of a perovskite solar module (Figure 1). In time, a 1-megawatt array has been manufactured on the moon and can now be connected to supply power to the Artemis Base Camp. This ambitious vision could someday become a reality. On August 29, 2021, a SpaceX Falcon 9 rocket launched a commercial resupply payload from Kennedy Space Center en route to the International Space Station (ISS). On board were perovskite solar cells that will fly for 6 months outside the ISS in low earth orbit (LEO) on the 15th Materials International Space Station Experiment (MISSE-15). This will be the first long duration flight of perovskite solar cell devices in LEO and a major step toward realizing the in-space operation and, potentially, manufacture of perovskite solar cells.

Lyndsey McMillon-Brown↗

Celestial Mapping System and Digital Lunar Library Initiative

We are preparing to create an interactive, global 3D lunar environment with integrated dataset and AI/ML tools to provide unique value to mission planners, scientists and the entire lunar community. This lunar environment will be based on NASA Ames Celestial Mapping System (CMS) [1] and Digital Lunar Library (DLL) Initiative. CMS provides a 3D virtual Lunar Globe with extensive user friendly tool sets, that include high resolution terrain visualization, elevation profiles, measurement kits, slope analysis, path optimization, line of sight analysis, equipment planning and placement tools and many other functionalities [1]. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The application is developed to provide situational and domain awareness on the Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on the Lunar surface. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. In the future, these capabilities will be enhanced by incorporating AI/ML tools and a plug-in architecture to enable customization by the user groups. With the help of DLL we will be able to : 1) Amplify the value of lunar information with AI-powered data enhancements 2) Acquire and integrate lunar data with AI-assisted georectification and homogenization 3) Analyze lunar data with advanced 3D visualization, intelligent search-by-example 4) Apply lunar data insights to specific use cases with an open plug-in architecture. The CMS-DLL initiative will have several potential use cases for NASA and the lunar community in general, including subsurface lava tube visualization and analysis, soil analysis, in-situ lunar resource visualization and representation on 3D globe, and data analytics for utilization. REFERENCES: [1] https://celestial.arc.nasa.gov/

3D Globe↗

Oxygen Isotopic Composition of Refractory Inclusions from the Miller Range (MIL) 090019 Carbonaceous Chondrite

Introduction: Primitive meteorites contain Calcium-Aluminum-rich Inclusions (CAIs)that preserve the records of the earliest times in the Solar System. CAIs record O isotopic variations with time and/or location from solar (16O-rich) to planetary (16O-poor) compositions [e.g., 1, 2].However, CAIs were also affected by parent body processing to varying degrees. The goal of this work was to identify the processes that resulted in the fine-scale spatial variations in oxygen isotopic compositions within the most ancient Solar System solids. We report oxygen isotopic composition of CAIs from MIL 090019 CO3.1 carbonaceous chondrite. MIL 090019 contains a high abundance of CAIs showing mineralogical as well as textural variations [3]. Methods: We analyzed 10 CAIs with different mineralogical assemblages, classified as corundum-bearing, grossite-bearing, hibonite-bearing, melilite-bearing, anorthite-bearing inclusions and amoeboid olivine aggregates(AOA’s). The mineralogical and petrological characterization of CAIs was performed using the JOEL Hyperprobe 8530 electron microprobe at NASA JSC. Oxygen isotopic imaging of the CAIs was done using the Cameca NanoSIMS 50L ion microprobe at NASA JSC. We followed the analytical protocol described in [4]. O-isotopic maps of the CAI were acquired by rastering a ~3 pA primary Cs+beam at 16 keVover an area of 20 ×20μm2over a period of ~7 hours. Negative secondary ions of 16O−, 17O−, 18O−, 28Si−, 24Mg16O−, 27Al16O−, and 40Ca16O−were simultaneously acquired using electron multiplier detectors at a mass resolving power sufficient to resolve the 16OH−interference from the 17O−peak, where the contribution of 16OH−was <0.1%.An electron flood gun was used to mitigate sample charging during the analyses. We used San Carlos olivine and Madagascar hibonite as isotopic standards to correct for the instrumental mass fractionation. The O-isotopic ratios were corrected for the quasi simultaneous arrival (QSA) effect and the detector dead time. All reported errors are 1 sigma. Results: The MIL 090019 carbonaceous chondrite hosts refractory inclusions varying in their mineralogies and textures[2, 3]. We found the oxygen isotopic compositions of mineral phases in MIL 090019 CAIs show large variations with Δ17O values varying from -27 to 0‰. A corundum-bearing inclusion records isotopic variations with corundum, melilite, perovskite, and anorthite showing Δ17Ovalues of -20 ±2.5, -10.2 ± 6.5, -10.7 ± 1.3,and -1.2 ± 3.2‰ respectively. A grossite-hibonite-bearing inclusion also records O-isotopic heterogeneity, where grossite, hibonite, Mg-rich spinel, and melilite show -3.7 ± 2.7, -22.9 ± 2.5, -21.4 ± 2.6, and -17.3 ± 2.8‰ respectively, whereas perovskite grains record a heterogenous isotopic composition ranging from -22.6 to -13.9‰. A hibonite-bearing inclusion shows average Δ17Ο values of -17.6 ± 5.3 ‰ and -15.1 ± 4.8 ‰ for hibonite and spinel respectively. The two perovskite grains also show relatively 16O-poor composition (Δ17Ο = -11.8 ± 6.4 ‰ and -8.6 ± 5.2 ‰). Anorthite has ~0.1 wt% Na2O and ~0.52 wt% FeO and a Δ17Ο value of -7.2 ± 5.0 ‰, whereas diopside records a Δ17Ο value of -3.5 ± 5.0 ‰. A hibonite-spinel-rich inclusion contains spinel and hibonite that are16O-rich (Δ17Οvalues -21.3 ± 2.8‰ and -19.4 ± 3.0‰, respectively). Melilite shows heterogenous oxygen isotopic composition, with an inner 16O-rich region and an outer 16O-poor region separated by a sharp boundary, with a bulk Δ17Ο= -16.2 ± 2.1‰, whereas two perovskite grains are relatively 16O-poor (Δ17Ο= -13.2 ± 3.7‰ and -7.1 ± 3.4‰).A spinel-rich inclusion contains perovskite grains with Δ17Οranging from -27.0 to -22.8 ‰and spinel with average Δ17Οvalue of -21.4 ± 2.8 ‰. In a melilite and spinel-rich CAI, perovskite, spinel, diopside, melilite, and Al-Ti-rich pyroxene record Δ17Ο values of-26.9 ± 4.6‰, -22.4 ± 4.3‰,-23.4 ± 4.9, -19.3 ± 3.4, and -19.0 ± 4.3 ‰ respectively. Olivine and spinel components of 2 AOA’s record a 16O-rich composition with Δ17O~-23‰. Discussion: The coexistence of 16O-rich and 16O-poor minerals within CAIs has been attributed to differing degrees of O isotopic exchange, reflecting a wide range of O diffusion rates[5]. However, the O isotopic heterogeneity observed in these CAIs cannot be explained by oxygen diffusion in nebular or parent body settings alone. The isotopic imaging of CAIs from the MIL 090019 meteorite shows variations in the O isotopic composition recorded in their mineral components, suggesting that these CAIs record the oxygen isotopic heterogeneity in the nebular gas from which they condensed. The coexistence of 16O-rich and 16O-poor mineral components in the CAI-forming region suggests that the gas in this region was not well-mixed and consisted of distinct 16O-rich and 16O-poor gaseous reservoirs.

P Mane↗

Heterogeneity of Bulk Oxygen Isotopic Compositions in Anhydrous Interplanetary Dust Particles

Introduction: Anhydrous interplanetary dust particles are one of the least altered ancient solar systemmaterials. Their bulk chemical compositions match those of CI chondrites within a factor of 2-3, except for carbonwhich is enriched in both anhydrous and hydrated IDPs by ~4x CI [1]. Hydrous IDPs often show 16O-poor isotopiccompositions, likely due to the interaction with isotopically heavy H2O [2]. Anhydrous IDPs are interpreted tooriginate from comets from the outer solar system [3]. Oxygen isotopic data for these materials is scarce, but resultspoint to a wider range of compositions [4]. This heterogeneity might be a result of mixing between a 16O-rich and a16O-poor reservoir formed via self-shielding and photodissociation of CO [5]. Here, we report bulk oxygen isotopiccompositions of three anhydrous IDPs in context of their mineralogical composition and discuss possible origins ofisotopic heterogeneity. Experimental: Bulk chemical composition and mineralogy of 70 nm thin ultramicrotomed sections of threeanhydrous IDPs (L2099A7, L2099A8, and L2071AB1) were analyzed using a Thermo Scientific Titan Themis G360-300 TEM equipped with a four-quadrant energy-dispersive X-ray detector (Super-X G2) at University ofMünster. Bulk oxygen isotopic compositions were measured using a NanoSIMS 50 at the Max-Planck-Institut fürChemie in Mainz. A focused Cs+ ion beam (~1 pA, ~100 nm) was rastered over a field of view varying from 5 x 5 to6 x 6 μm2, depending on particle size for 15 layers. Negative secondary ions of 16O, 17O, 18O, 12C14N, and 28Si werecollected on electron multipliers. The 16OH contribution to the 17O peak was 1-2 ‰. As a standard, a matrix regionof meteorite CR2 Queen Alexandra Range (QUE) 99177 was used, whose oxygen isotopic composition wasmeasured by [6]. Results and Discussion: Particles A7 and A8 are both fine-grained, consisting mostly of small, 100 nm-sizedequilibrated aggregates (EA). Both particles exhibit discontinuous magnetite rims with thicknesses up to 50 nm inA7 and 100 nm in A8 on the outsides. In Particle AB1, the upper part of the particle consists of a few EAs, while thelower part contains lots of small GEMS grains with 100-200 nm diameter clustered together. Magnetite rims arenearly absent, the rare rims reaching maximum 20 nm thickness, indicating that AB1 is of more primitive naturethan the other two IDPs [1]. Furthermore, it contains several diffuse GEMS-like areas, identified by an amorphoussilicate groundmass with small nano-inclusions of Fe,Ni-metal and Fe-sulfides. All three particles are subsolar forall major element/Si ratios. Mean S/Si of particles A7 and A8 is 0.046 and 0.048, respectively, while it is an order ofmagnitude higher in AB1 (0.184). This reflects the higher degree of thermal alteration in A7 and A8, resulting in theloss of volatile S and oxidation of Fe-sulfides and FeNi-metal to magnetite as present in particle rims. A8 is rather16O-poor with δ17OSMOW = 7.8 ± 3.4 ‰ and δ18OSMOW = 9.5 ± 3.1 ‰ (1σ), followed by A7 with δ17OSMOW = − 0.8 ±4.6 ‰ and δ18OSMOW = −2.2 ± 3.4 ‰. In contrast to that, AB1 has the most 16O-rich bulk composition with δ17OSMOW= −24.2 ± 5.4 ‰ and δ18OSMOW = −25.3 ± 3.6 ‰. All investigated IDPs plot slightly above the CCAM line aspreviously reported for other anhydrous IDPs [4], maybe due to a contribution from circumstellar dust from AGBstars enriched in 17O [7]. The 16O-rich composition of AB1 is similar to the most 16O-rich anhydrous IDP U2015D21measured by [8] which is dominated by GEMS [9] and the GEMS-rich IDP GM4-2 reported by [10]. Nevertheless,it is unlikely that GEMS are the carrier for the 16O-rich composition of AB1 because most GEMS have O isotopiccompositions indistinguishable from terrestrial values, although errors on these analyses are large [11]. The isotopicheterogeneity is best explained by contribution of grains from different regions in the protoplanetary disk, samplingdifferent O isotope reservoirs, created by self-shielding and photodissociation of CO. This process resulted in 16O-rich CO gas and 16O-poor H2O that froze as ice-mantles onto dust grains [12]. Alternatively, the higher degree ofheating in A7 and A8 could have influenced isotopic fractionation, because higher δ17,18O values are reported fromthe regions of the atmosphere where small particles are heated and oxidized, as observed for the thermal alteration ofcosmic spherules [13]. Acknowledgements: We would like to thank NASA Astromaterials Acquisition & Curation Office for providing IDPsamples and DFG for funding this project (VO1816/5-1)

B Schulz↗

STAR-X: Survey and Time-domain Astrophysical Research eXplorer

STAR-X is a MIDEX mission proposed to NASA in December 2021. Comprising an X-ray telescope (XRT) provided by GSFC and MIT, a UV telescope (UVT) provided by the University of Colorado, and a spacecraft (SC) provided by Ball Aerospace, STAR-X is designed to conduct time-domain survey and to respond rapidly to transient events discovered by other observatories such as LIGO, Rubin LSST, Roman WFIRST, and SKA. The key features of the XRT are its excellent PSF (2.5 arc-seconds half-power diameter), large effective area (1,800 cm2 at 1 keV), and large field of view (1 deg2), making it more than an order of magnitude more capable and more sensitive than Chandra and Swift/XRT to conduct survey and to find and study transient sources. The UVT has a 30-cm aperture with 5 filters covering the 160nm to 340nm band, providing simultaneous spectral coverage with the XRT and enabling reverberation mapping of accretion disk geometries around black holes. The SC is highly autonomous and is capable of fast slewing, enabling efficient raster scans and time-domain surveys. In particular, in combination with a state-of-the-art mission operations center at the University of Colorado, the SC can respond to targets of opportunity within 2 hours 90% of the time. With its nearly equatorial low-earth orbit, STAR-X’s telescopes will have low particle background, enabling them to have unprecedented sensitivity for measuring faint diffuse emissions from clusters of galaxies. STAR-X is a timely response to Astro2020’s recommendation for a space-based, sustaining time-domain and multi-messenger program.

William W. Zhang↗

Hot Cracking Behavior and Beam-Induced Grain Refinement in Electron Beam Freeform Fabricated Al 7075

Electron beam freeform fabrication (EBF 3 ) is a high deposition rate, wire-based directed energy deposition (DED) additive manufacturing (AM) process used to print metallic parts in a vacuum environment. While high specific strength 7xxx-series Al alloys are of interest in the aerospace and automotive industries, these alloys suffer from hot cracking issues during fusion welding and AM. In this work, linear deposits of Al 7075 were fabricated with EBF 3 to study the effects of baseplate thickness, preheat temperature, and beam focus on hot cracking behavior. Solidification cracks were observed in the first deposition layer, and by the third layer coalesced into large “macrocracks” running vertically through the build height. Fine, intergranular liquation “microcracks” appeared between macrocracks below the root of the final deposit layer fusion zone. Increasing the substrate preheat temperature from 165°C to 320°C deepened the partially melted zone and resulted in a more than twofold increase in the liquation microcrack density. Analysis of Scheil solidification diagrams revealed that fugitive losses of Zn and Mg during deposition increased the susceptibility to solidification cracking and promoted substrate liquation cracking. Focused electron beam (EB) conditions combined with a high aspect ratio elliptical raster pattern resulted in bands of refined, equiaxed grains. The refined microstructure suppressed solidification macrocracking and caused a nearly fivefold reduction in liquation crack density, demonstrating that beam-induced grain refinement may be a promising low-cost method for reducing hot cracking during AM.

aluminum↗

Aster Global Dem (gdem) Version 3

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 14-channel imaging instrument operating on NASA’s Terra satellite since 1999. ASTER’s visible–near infrared (VNIR) instrument, with three bands and a 15 m Instantaneous field of view (IFOV), is accompanied by an additional VNIR band using a second, backward-looking telescope. Collecting along-track stereo pairs, the geometry produces a base-to-height ratio of 0.6. In 2009, the ASTER Science Team released Version 1 of the global DEM (GDEM) based on stereo correlation of 1.2 million ASTER scenes. The DEM has 1 arc-second latitude and longitude postings (~30 m) and employed cloud masking to avoid cloud-contaminated pixels. The GDEM covers all of the Earth’s land surface from 83 degrees north to 83 degrees south latitude. Version 2 was released in 2011, with notable improvements in coverage and accuracy. In 2019, the final, Version 3, was released; again improving on coverage and removing almost all artifacts. Th GDEM is a unique, global high spatial resolution digital elevation dataset available to all users at no cost. In addition, a second unique dataset was produced and released. The raster-based ASTER Global Water Body Dataset (ASTWBD) identifies the presence of permanent water bodies, and marks them as ocean, lake, or river. An accompanying DEM file indicates the elevation for each water pixel. To date, over 110+ million 1x1 degree GDEM tiles have been distributed.

Crippen, R.↗

Front Range Wildland Fires: Evaluating the Efficacy of Remote Sensing Imagery in Monitoring Forest Fuels Treatment Methods

Over the last several decades, wildfire frequency and severity in forested areas along Colorado’s Front Range have increased due to a buildup of fuels. This has led to an increase in forest treatments, as well as an increased need to evaluate the success of these treatments. Remote sensing products offer an efficient and cost-effective way to monitor forest treatments; however, not all remote sensing products and analysis techniques have been explored by Coloradan land managers. Specifically, project partners at the Colorado State Forest Service (CSFS) and the Colorado Forest Restoration Institute (CFRI) were interested in using an effective and streamlined method of mapping canopy cover to better monitor forest treatment success. To support their needs, the NASA DEVELOP Front Range Wildland Fires team explored National Agricultural Imagery Program (NAIP) imagery at different spatial resolutions and numbers of training points with NASA’s Shuttle Radar Topography Mission (SRTM) Data Elevation Model (DEM) as a predictor in addition to NAIP imagery spectral predictors. From this analysis, we created classified canopy cover rasters, and compared accuracy metrics across model iterations. We also determined that the best performing model, with an overall accuracy of 0.900 uses 2021 NAIP imagery at 2-meter resolution, 800 training points, 200 testing points, does not use topographic predictors, and reclassifies shadow pixels via a pre-selected NDVI threshold.

Remote Sensing↗

Study of Coronal Heating in Solar Active Regions Using Wide-Field Imaging Spectroscopy: Hinode EIS Slot Observations

Understanding the frequency of heating events that keep the coronal plasma at several million Kelvin above the photospheric temperature of~ 6000K, is one of the most important problems in solar astrophysics. Spectroscopic observations of the Sun in the extreme ultraviolet (EUV) indicate that the coronal plasma reaches temperatures from 1 to 5 MK in active regions. It is also established that temperature in active regions can vary strongly with time and, moreover, contain sub-regions that evolve and develop separately. Tracking the spatio-temporal evolution of temperature requires continuous observation of the entire active region via imaging and spectroscopy. Traditional slit imaging spectroscopy probes plasma heating in solar active regions through observations of diagnostic emission lines and the resulting data are spectrally pure. Here, imaging is performed through rastering process, which severely limits co-temporal observations and often can be slow to miss events that evolve at other portions of the active region. In contrast, wide-field imaging spectroscopy offer simultaneous coverage of a large field of view as well as obtain spectral information in the same direction. This data suffers from spatial-spectral confusion, and are called spectroheliograms. Using the state-of-the-art inversion techniques that are developed recently, now spectroheliogram data can be unfolded to yield spectrally pure maps of large fields over long duration of observations. We use wide slit data, usually referred as ‘slot’, from the EUV Imaging Spectrometer (EIS) onboard Hinode satellite, focusing on active region observations. Here, we present our study of coronal heating in an active region using a long duration Hinode EIS slot observation.

Active region heating↗