Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Inventory”

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 739 records · Page 41

Complications of Metadata Curation for NASA Airborne and Field Campaigns, Platforms, and Instruments

The Airborne Data Management Group (ADMG) curates metadata that describe NASA's airborne and field campaigns, platforms and instruments. This activity is vital to building a useful inventory of sub-orbital Earth science data that improves data discovery and access. During the curation process, many metadata issues were identified that required improvement to campaign and data product metadata. In some cases, locating the needed metadata to add to the inventory was a simple process. For other cases, the information was hard to find. In addition, identifying accurate investigation instrument details to add to the inventory was especially complicated because of the variety of definitions used in the Earth science community for the same concepts. One example of this is the concept of instruments' spatial and temporal resolution. The spatial resolution is one of the more difficult elements to curate given the variations in meaning across various disciplines. Clarified definitions are needed to enable consistency of information across campaigns and instruments. In this presentation, we introduce results from a survey of scientists from various fields in which we asked for definitions of spatial and temporal resolution. Our survey results highlight the importance of creating more universally acceptable definitions for certain metadata elements. By curating sub-orbital field campaign and instrument metadata, ADMG is enabling more efficient discovery and access to NASA observations by allowing science data users to search for certain clearly defined criteria and metadata values.

Ashlyn Shirey↗

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗

A Dynamic Landslide Hazard Monitoring Framework for the Lower Mekong Region

The Lower Mekong region is one of the most landslide-prone areas of the world. Despite the need for dynamic characterization of landslide hazard zones within the region, it is largely understudied for several reasons. Dynamic and integrated understanding of landslide processes requires landslide inventories across the region, which have not been available previously. Computational limitations also hamper regional landslide hazard assessment, including accessing and processing remotely sensed information. Finally, open-source software and modelling packages are required to address regional landslide hazard analysis. Leveraging an open-source data-driven global Landslide Hazard Assessment for Situational Awareness model framework, this study develops a region-specific dynamic landslide hazard system leveraging satellite-based Earth observation data to assess landslide hazards across the lower Mekong region. A set of landslide inventories were prepared from high-resolution optical imagery using advanced image-processing techniques. Several static and dynamic explanatory variables (i.e., rainfall, soil moisture, slope, relief, distance to roads, distance to faults, distance to rivers) were considered during the model development phase. An extreme gradient boosting decision tree model was trained for the monsoon period of 2015–2019 and the model was evaluated with independent inventory information for the 2020 monsoon period. The model performance demonstrated considerable skill using receiver operating characteristic curve statistics, with Area Under the Curve values exceeding 0.95. The model architecture was designed to use near-real-time data, and it can be implemented in a cloud computing environment (i.e., Google Cloud Platform) for the routine assessment of landslide hazards in the Lower Mekong region. This work was developed in collaboration with scientists at the Asian Disaster Preparedness Center as part of the NASA SERVIR Program’s Mekong hub. The goal of this work is to develop a suite of tools and services on accessible open-source platforms that support and enable stakeholder communities to better assess landslide hazard and exposure at local to regional scales for decision making and planning.

Nishan Kumar Biswas↗

An Overview of NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI): Supporting FAIR and Open Access to Airborne and Field Data

Since 2019, NASA’s Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) has worked to promote and ensure the discoverability and accessibility of the agency’s non-satellite Earth science observations. A primary component of this effort is the development of NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI) and the vetting of key contextual details required to sustain this unique inventory of airborne and field metadata. CASEI provides information on the science objectives motivating data collection, key events/time periods in the observational record aligned with the science objectives, complementary simultaneous observations, programmatic details, and much more. The diverse set of data formats and disciplines served by CASEI have required the implementation of a common data model to organize suborbital observation metadata and efficiently connect appropriate campaigns, platforms, and instruments. The CASEI inventory provides a single entry point for users to search and browse NASA’s airborne and field data archives, regardless of which repository is responsible for their stewardship. This presentation will provide a summary of the motivations for and the development of the CASEI system. Particular attention will be granted to how CASEI facilitates discovery and reuse of these lesser-known NASA data, supporting the Open Science vision and enhancing the return on investments made to collect these unique and varied observations. An up-to-date summary of CASEI inventory content and initial metrics will be provided. Current and future avenues ADMG is pursuing to enhance both CASEI and specific components of suborbital data stewardship at various stages of the data life cycle will also be discussed.

Stephanie M. Wingo↗

New Insights on the 7[superscript]Be Cycle in the Ocean

The cosmogenic radionuclide 7[superscript]Be has been applied as a tracer of dynamical processes in the upper ocean and of atmospheric deposition of trace elements at the sea surface. These applications usually assume that 7[superscript]Be is entirely in the dissolved form, and that scavenging and downward export of 7[superscript]Be by settling particles can be neglected. In this work, we explore these assumptions and more generally assess the significance of the 7[superscript]Be activity in the particulate fraction, through the generation of vertical profiles of particulate 7[superscript]Be in the open ocean. From detailed measurements obtained from low-background gamma spectrometers placed in underground facilities, we report vertical profiles of 7[superscript]Be activity in suspended particles (7[superscript]Bep[subscript]) collected in various oceanic regions: the Mediterranean Sea (DYFAMED station), the Indian Sector of the Southern Ocean (station A3-2 from the KEOPS2 cruise), the Sargasso Sea (OFP station), and the subpolar North Atlantic Ocean (GEOVIDE cruise). We find that, in each oceanic region, 7[superscript]Bep[subscript] activities are generally higher in the mixed layer than in the thermocline. They vary in the mixed layer from 3.0 dpm/m3 at DYFAMED to 33.1dpm/m3 at GEOVIDE cross-over station 51/60, i.e., within a range consistent with previous 7[superscript]Bep[subscript] measurements for the open ocean. For the GEOVIDE cruise, the 7[superscript]Bep[subscript] activities measured on different filter types at different depths are corrected for filter offsets derived from multiple 7[superscript]Bep[subscript] measurements at a near-coastal station in the western Mediterranean Sea. We then combine measurements of total 7[superscript]Be activity (Shelley et al., 2017) with our measurements of 7[superscript]Bep[subscript] activity to estimate the solid/solution partitioning of 7[superscript]Be. On average, the particulate fraction would represent 6% of total 7[superscript]Be activity at 5-m water depth (n = 6), 22% at 20 m (n = 2) and 9% at 70 m (n = 3). At GEOVIDE stations, 7[superscript]Bep[subscript] inventories range from 5% to 19% of the total 7[superscript]Be inventories. In the Labrador Sea, the measured 7[superscript]Bep[subscript] inventories are lower than the dry 7[superscript]Be deposition fluxes estimated from aerosol samples collected during GEOVIDE, suggesting that a significant portion of 7[superscript]Bep[subscript] may be removed by sinking particles. The distribution coefficient Kd for 7Be increases with depth, with log10Kd averaging 5.2 ± 0.1 at 5 m to 6.1 ± 0.1 between 70 and 150 m, suggesting that scavenging of dissolved 7[superscript]Be by particles is more pronounced in the thermocline than in the mixed layer when differences in particle concentrations are taken into account. Overall, our study suggests that, at least in some oceanic regions, the removal of 7[superscript]Be by marine particles may be significant and that it may need to be considered in applications of 7[superscript]Be as a tracer of oceanic processes and atmospheric deposition.

Beryllium-7↗

The Habitability of Proxima Centauri b II. Possible Climates and Observability

Radial velocity monitoring has found the signature of a M sin i = 1.3 M(sub ⨁) planet located within the habitable zone (HZ) of Proxima Centauri. Despite a hotter past and an active host star, the planet Proxima b could have retained enough volatiles to sustain surface habitability. Here we use a 3D Global Climate Model (GCM) to simulate the atmosphere and water cycle of Proxima b for its two likely rotation modes (1:1 and 3:2 spin-orbit resonances), while varying the unconstrained surface water inventory and atmospheric greenhouse effect. Any low-obliquity, low-eccentricity planet within the HZ of its star should be in one of the climate regimes discussed here. We find that a broad range of atmospheric compositions allow surface liquid water. On a tidally locked planet with sufficient surface water inventory, liquid water is always present, at least in the substellar region. With a non-synchronous rotation, this requires a minimum greenhouse warming (~10 mbar of CO2 and 1 bar of N2). If the planet is dryer, ~0.5 bar or 1.5 bars of CO2 (for asynchronous or synchronous rotation, respectively) suffice to prevent the trapping of any arbitrary, small water inventory into polar or nightside ice caps. We produce reflection and emission spectra and phase curves for the simulated climates. We find that atmospheric characterization will be possible via direct imaging with forthcoming large telescopes. The angular separation of 7 λ/D at 1 μm (with the E-ELT) and a contrast of ~10(exp -7) will enable high-resolution spectroscopy and the search for molecular signatures, including H2O, O2, and CO2. The observation of thermal phase curves can be attempted with the James Webb Space Telescope, thanks to a contrast of 2 × 10(exp -5) at 10 μm. Proxima b will also be an exceptional target for future IR interferometers. Within a decade it will be possible to image Proxima b and possibly determine whether the surface of this exoplanet is habitable.

Proxima Cen↗

Blue Carbon Stock Estimation of US Coastal Marshes from New York to Georgia How Much Do We Have to Lose?

Valued for their myriad multifunctional roles in preserving habitat for biodiversity, cycling nutrients, protecting shorelines, improving water quality, and sequestering blue carbon, coastal and riverine marshes continue to disappear not only due to land use change but also sea level rise. Blue carbon’s role in the carbon cycle has been underappreciated until the last few decades, and the carbon stocks for U.S. Atlantic coastal margins have previously been estimated for a depth of 0.5-1 meter. We select several North American East Coast databases that have been utilized to study sea level rise and instead use them to estimate marsh depth from New York to Georgia; in local marshes that lack depth data, we present new depth data and perform several full-depth transects. This alongside marsh area data from the National Wetlands Inventory (NWI) enables us to estimate marsh volume. We then utilize an average carbon density of 27 kg/m 3 by Holmquist et al. 2018 to calculate blue carbon stocks. We present the inventories of peat depth by state, marsh area by state, and total marsh volume by state, followed by the blue carbon stocks. The peat depth inventory of eastern U.S. marshes reveals that riverine marshes are significantly deeper than coastal marshes. While both are important, we highlight the jeopardy of rapidly eroding urban marshes due to the heavy metals these marshes have sequestered for centuries as they contaminate the surrounding estuary. Uncertainties and caveats include carbon density values, loss of marsh since the NWI assessment, and depth averages. The high cost of marsh disappearance underscores the urgent need for their preservation.

Coastal marshes↗

High-Resolution Mapping of Nitrogen Oxide Emissions in Large US Cities From TROPOMI Retrievals of Tropospheric Nitrogen Dioxide Columns

Satellite-derived spatiotemporal patterns of nitrogen oxide (NO x ) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NO x emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO 2 ) retrievals. The accuracy of the coupled method is validated through application to synthetic NO 2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = −0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R=0.88 ± 0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = −0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

NOx emissions↗

Quantifying Burned Area and Smoke from Prescribed and Smaller Fires: West Palm Beach, Florida

In the Central and Southeastern U.S. (C&SE), small, short-lived fires are often underestimated by satellites due to their size, timing, cloud cover, and rapid regrowth or plowing after burns. Satellite data are essential for the National Emissions Inventory, as ground-based inventories are historically incomplete and geographically inconsistent. Agricultural burning, a widespread annual practice in many U.S. regions, significantly impacts air quality on local to regional scales. As part of NASA’s Health and Air Quality Applied Sciences (HAQAST) team, we develop a burned area inventory to account for these ‘missing’ small fires. Our study focuses on West Palm Beach, FL, near Lake Okeechobee, where agriculture fields are burned annually fall-spring for crop management and harvest. This region poses challenges for satellite detection due to frequent rain, flooding, and cloud cover.

Emily Gargulinski↗

Landslides Across the USA: Occurrence, Susceptibility, and Data Limitations

Detailed information about landslide occurrence is the foundation for advancing process understanding, susceptibility mapping, and risk reduction. Despite the recent revolution in digital elevation data and remote sensing technologies, landslide mapping remains resource intensive. Consequently, a modern, comprehensive map of landslide occurrence across the United States (USA) has not been compiled. As a first step toward this goal, we present a national-scale compilation of existing, publicly available landslide inventories. This geodatabase can be downloaded in its entirety or viewed through an online, searchable map, with parsimonious attributes and direct links to the contributing sources with additional details. The mapped spatial pattern and concentration of landslides are consistent with prior characterization of susceptibility within the conterminous USA, with some notable exceptions on the West Coast. Although the database is evolving and known to be incomplete in many regions, it confirms that landslides do occur across the country, thus highlighting the importance of our national-scale assessment. The map illustrates regions where high-quality mapping has occurred and, in contrast, where additional resources could improve confidence in landslide characterization. For example, borders between states and other jurisdictions are quite apparent, indicating the variation in approaches to data collection by different agencies and disparity between the resources dedicated to landslide characterization. Further investigations are needed to better assess susceptibility and to determine whether regions with high relief and steep topography, but without mapped landslides, require further landslide inventory mapping. Overall, this map provides a new resource for accessing information about known landslides across the USA.

Landslide mapping↗

J. E. Nichols and D. M. Peteet reply

The quantification of northern peatland carbon stocks is vital to our understanding of the global carbon cycle, and we welcome the opportunity to respond to the comments submitted in the preceding “Matters Arising” (Yu et al., Ratcliffe et al.). In response to Yu et al., we provide additional clarification of how data from the Neotoma Paleoecological Database (NPD) are stored and used. We also repeated our quantification of northern peat carbon stocks using only radiocarbon data vetted by other publications. However, our conclusions are unchanged by the elimination of the additional data. We respond to Ratcliffe et al. by addressing the conflict between the “time-history” and “inventory methods.” We calculated northern peatland carbon stocks by the inventory method using our dataset and carefully quantify the uncertainties. We find that while the mean values for carbon stock differ by twofold, the uncertainties around those means are larger than previously acknowledged and are overlapping. This result emphasizes the need for continued work by the carbon cycle science community to understand and quantify uncertainty in terrestrial carbon stock estimates.

Peatlands↗

Relevance of ERTS to the State of Ohio

The author has identified the following significant results. The ability to delineate and inventory strip mined areas using ERTS-1 imagery has been established. This gives Ohio a method to rapidly gain an up-to-date inventory of strip mined lands for state planning purposes, which has not been available previously. Smoke plume detection and sedimentation patterns in Sandusky Bay have also been determined from initial analysis of ERTS-1 data.

Sweet, D. C.↗

Use of satellite imagery for wildland resource evaluation

The author has identified the following significant results. Crested wheatgrass seedings have been quantified for the state of Nevada, and have been broken down by county and land status. The wide coverage of ERTS-1 has been found to be extremely useful for putting these seeded areas in the proper perspective for inventory. In the same manner, water bodies are being inventoried and changes relating to time are being monitored. Water resources are critical in Nevada, and this should prove useful to land owners and land managers throughout the state.

Tueller, P. T.↗

Relevance of ERTS-1 to the state of Ohio

The author has identified the following significant results. To date, only one significant result has been reported for the Ohio ERTS program. This result relates to the proven usefulness of ERTS-1 imagery for mapping and inventorying strip-mined areas in southeastern Ohio. ERTS provides a tool for rapidly and economically acquiring an up-to-date inventory of strip-mined lands for state planning purposes which was not previously possible.

Sweet, D. C.↗

Field Data Collection: an Essential Element in Remote Sensing Applications

Field data collected in support of remote sensing projects are generally used for the following purposes: (1) calibration of remote sensing systems, (2) evaluation of experimental applications of remote sensing imagery on small test sites, and (3) designing and evaluating operational regional resource studies and inventories which are conducted using the remote sensing imagery obtained. Field data may be used to help develop a technique for a particular application, or to aid in the application of that technique to a resource evaluation or inventory problem for a large area. Scientists at the Forestry Remote Sensing Laboratory have utilized field data for both purposes. How meaningful field data has been collected in each case is discussed.

Pettinger, L. R.↗

Remote sensing applied to land-use studies in Wyoming

Impending development of Wyoming's vast fuel resources requires a quick and efficient method of land use inventory and evaluation. Preliminary evaluations of ERTS-1 imagery have shown that physiographic and land use inventory maps can be compiled by using a combination of visual and automated interpretation techniques. Test studies in the Powder River Basin showed that ERTS image interpretations can provide much of the needed physiographic and land use information. Water impoundments as small as one acre were detected and water bodies larger than five acres could be mapped and their acreage estimated. Flood plains and irrigated lands were successfully mapped, and some individual crops were identified and mapped. Coniferous and deciduous trees were mapped separately using color additive analysis on the ERTS multispectral imagery. Gross soil distinctions were made with the ERTS imagery, and were found to be closely related to the bedrock geology. Several broad unstable areas were identified. These were related to specific geologic and slope conditions and generally extended through large regions. Some new oil fields and all large open-cut coal mines were mapped. The most difficult task accomplished was that of mapping urban areas. Work in the urban areas provides a striking example of snow enhancement and the detail available from a snow enhanced image.

Breckenridge, R. M.↗

A comparison of land-use determinations using data from ERTS-1 and high altitude aircraft

A manual interpretation of ERTS-1 MSS system corrected imagery has been performed on a study area within the Houston Area Test Site to classify land use using the Level 1 categories proposed by the Department of the Interior. The two types of imagery used included: (1) black and white transparencies of each band enlarged to a scale of approximately 1:250,000 and (2) color transparencies composited from the computer compatible tapes using the film recorder on a multispectral data analysis station. The results of this interpretation have been compared with the 1970 land use inventory of HATS which was compiled using color ektachrome imagery from high altitude aircraft (scale 1:120,000). Urban data from the same scene was also analyzed using a computer-aided (clustering) technique. The resulting clusters, representing areas of similar content, were compared with existing land use patterns in Houston. A technique was developed to correlate the spectral clusters to specific urban features on aircraft imagery by the location of specific, high contrast objects in particular resolution elements. It was concluded that ERTS-1 data could be used to develop Level 1 and many Level 2 land use categories for regional inventories and perhaps to some degree on a local level.

Lundelius, M. A.↗

Remote sensing in Iowa agriculture: Identification and classification of Iowa crop lands using ERTS-1 and complimentary underflight imagery

The author has identified the following significant results. Results of the continuing analysis of ERTS-1 imagery covering Iowa during 1972 and periods during 1973 are covered. Emphasis is placed on the identification and classification of major crop types at two test sites in Iowa. Standard photointerpretive methods were used in this analysis including the direct enlargement of black and white single-band products and additive color multi-band procedures using a miniadcol system. The use of sequential coverage during the crop growing season is emphasized as a means to improve the effectiveness of ERTS-1 photointerpretations of crop land acreage estimates in Iowa. Illustrative black and white and color prints of both ERTS-1 and underflight imagery are included. In addition, forest land inventories at one test site are reported. A new method for the inventory of forest lands using ERTS-1 imagery is reported and compared with estimates obtained using earlier underflight imagery.

Mahlstede, J. P.↗