SEARCH · Search NASA

Results for “Remote Sensing; Data Storage;”

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.

SourceResearch connectionFrom yearThrough year

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

At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Smart Composite Pressure Vessels (SCPV) with Integrated Health Monitoring

The U.S. Department of Energy (DOE) is promoting and developing more energy efficient and environmentally friendly technologies that will enable America to use less petroleum. Hydrogen fuel cells – which directly convert the chemical energy in hydrogen to electricity with only water and heat as byproducts – are a very attractive solution that can enable this to happen. To date, DOE's efforts have culminated in commercial demonstration of on-board vehicular hydrogen storage systems that can allow for a driving range of greater than 300 miles. This requires storing 5 Kgs of hydrogen onboard a light vehicle. In order to store this quantity of hydrogen, the hydrogen gas needs to be stored in a composite overwrapped pressure vessel (COPV) at a very high internal pressure. The objective of the program was to demonstrate continuous and predictable health-monitoring of composite pressure vessels. A higher confidence in the operational safety of the vessels will lead to reduced burst factor of safety imposed by regulatory standards and hence will help reduce the structural wall thickness that drives the cost of the vessel. Highly optimized Type III (metal lined) and Type IV (polymer lined) COPVs that are manufactured using filament winding process have been designed and qualified for the above mentioned application. However, the main structural component of the COPVs is carbon fiber and the high cost of carbon fiber composite in a pressure vessel is a primary challenge in reducing the cost of gaseous hydrogen storage. Continuous and remote monitoring of structural health of the COPVs as well as optimization of the strength translation of carbon fibers have the potential to allow for reduced factor of safety, thereby reduced amount of carbon and associated cost of the vessel. In the current program, the project team including Steelhead Composites (SHC), University of Tennessee, Knoxville (UTK), Teijin Carbon America, Oak Ridge National Laboratory (ORNL) and LUNA designed, fabricated, and tested smart composite pressure vessels with integrated sensors. Iterative loops of design and testing using coupons, subscale STEB vessels and full size vessels proved that a new generation of high performance carbon fiber can be used for efficient design of Type 3 vessels for H2 storage. Novel analysis techniques were developed to predict the initiation and propagation of interlaminar damage inside the composite shell due to impact damage, a real threat in practical operation. Such an analysis scheme is typically not used in tank design but is an essential tool for health monitoring of composite vessels. Remote sensing of the key signatures of the tank’s operating parameters such as pressure, acceleration and humidity was demonstrated using a unique device that can wirelessly transmit and stream the data to a remote server. Fiber optic sensors were successfully integrated during fabrication of the tanks. These sensors provide a wealth of information regarding the structural health of the vessel when it is subsequently pressurized or subjected to impact damage. Excellent correlation was demonstrated between the fiber optic sensor and mechanical strain gage data, and between the measurements and analytical predictions.

08 HYDROGEN↗

NASA NTRS1997

Biogeochemistry of DMS in Surface Waters

Dimethylsulfide (DMS) is important in influencing the formation of aerosols in the troposphere over large areas of the world's oceans. Understanding the dynamics of aerosols is important to understanding the earth's radiation balance. In evaluating the factors controlling DMS in the troposphere it is vital to understand the dynamics of DMS in the surface ocean. The biogeochemical processes controlling DMS concentration in seawater are myriad; modeling and theoretical estimation are problematic. At the beginning of this project we believed that we were on the verge of simplifying the ship-track measurement of DMS, and we proposed to deploy such a system to develop a database relating high frequency DMS measurements to biological and physicochemical and optical properties of surface water that can be quantified by remote sensing techniques. We designed a system to measure DMS concomitantly with other basic chemical and biological data in a flow-through system. The project was collaborative between Woods Hole Oceanographic Institution (WHOI) and Bermuda Biological Station for Research (BBSR). The project on which we are reporting was budgeted for only one year with a one year no-cost extension. At WHOI our effort was directed towards designing traps which would be used to concentrate DMS from seawater and allow storage for subsequent analysis. At that time, GC systems were too large for easy long-term deployment on a research vessel like R/V Weatherbird, so we focused on simplifying the shipboard sampling procedure. Initial studies of sample recovery with high levels of DMS suggested that Carboxen 1000, a relatively new carbon molecular sieve, could be used as a stable storage medium. The affinity of Carboxen for DMS is several orders of magnitude higher than gold wool (another adsorbent used for DMS collection) on a weight or volume basis. Furthermore, Carboxen's affinity for DMS is also far less susceptible to humidity than gold wool. Unfortunately, further experiments with low level DMS indicated that recovery of DMS after storage was not quantitative. The material has proven to be completely acceptable for short term storage and has been incorporated into a micro-GC system. Since working on this project, we have collaborated with RVM Scientific in Santa Barbara in the design and construction of small portable micro-GC's that will make feasible at-sea measurement in moving ships, making rapid gas analysis and quantification feasible in a ship-track mode. Throughout this period at both WHOI and BBSR, we continued to analyze field data to understand that patterns of time and space variability in DMS and the processes that govern it. These insights will be crucial to determining the specifications for our automated sampling program. The data from this, the longest continuous sampling program for ocean DMS, provided insights into year to year and short-term variability.

Dacey, J. W. H.↗

NASA NTRS1982

Application of future remote sensing systems to irrigation

Area estimates of irrigated crops and knowledge of crop type are required for modeling water consumption to assist farmers, rangers, and agricultural consultants in scheduling irrigation for distributed management of crop yields. Information on canopy physiology and soil moisture status on a spatial basis is potentially available from remote sensors, so the questions to be addressed relate to: (1) timing (data frequency, instantaneous and integrated measurement); and scheduling (widely distributed spatial demands); (2) spatial resolution; (3) radiometric and geometric accuracy and geoencoding; and (4) information/data distribution. This latter should be overnight, with no central storage, onsite capture, and low cost.

Miller, L. D.↗

NASA NTRS2011

Remote Sensing of Terrestrial Water Storage with GRACE and Future Gravimetry Missions

The Gravity Recovery and Climate Experiment (GRACE) has demonstrated that satellite gravimetry can be a valuable tool for regional to global water cycle observation. Studies of ice sheet and glacier mass losses, ocean bottom pressure and circulation, and variability of water stored on and in the land including groundwater all have benefited from GRACE observations, and the list of applications and discoveries continues to grow. As the mission approaches its tenth anniversary of launch on March 12,2012, it has nearly doubled its proposed lifetime but is showing some signs of age. In particular, degraded battery capacity limits the availability of power in certain orbital configurations, so that the accelerometers must be turned off for approximately one month out of six. The mission managers have decided to operate the spacecrafts in a manner that maximizes the remaining lifetime, so that the longest possible climate data record is available from GRACE. Nevertheless, it is not unlikely that there will be a data gap between GRACE and the GRACE Follow On mission, currently proposed for launch in 2016. In this presentation we will describe recent GRACE enabled science, GRACE mission health, and plans for GRACE Follow On and other future satellite gravimetry missions.

Rodell, Matt↗

NASA NTRS2010

The Use of Remote Sensing Data for Advancing America's Energy Policy

After briefly reviewing America's Energy Policy laid out by the Obama Administration, we outline how a Global Carbon Observing System designed to monitor Carbon from space can provide the necessary data and tools to equip decision makers with the knowledge necessary to formulate effective energy use and practices policy. To stabilize greenhouse gas emissions in the atmosphere in a manner that it does not interfere with the Earth's climate system (which is one of the goals of United Nations Framework for Convention on Climate Change) requires vastly improved prediction of the atmospheric carbon dioxide (CO2) concentrations. This in torn requires a robust understanding of the carbon exchange mechanisms between atmosphere, land, and oceans and a clear understanding of the sources and sinks (i.e. uptake and storage) of CO2. We discuss how the Carbon Observing System from space aids in better understanding of the connection between the carbon cycle and climate change and provides more accurate predictions of atmospheric CO2 concentration. It also enables implementation of greenhouse gas (GHG) mitigation policies such as cap and trade programs, international climate treaties, as well as formulation of effective energy use policies.

Valinia, Azita↗

NASA NTRS1981

Generic functional requirements for a NASA general-purpose data base management system

Generic functional requirements for a general-purpose, multi-mission data base management system (DBMS) for application to remotely sensed scientific data bases are detailed. The motivation for utilizing DBMS technology in this environment is explained. The major requirements include: (1) a DBMS for scientific observational data; (2) a multi-mission capability; (3) user-friendly; (4) extensive and integrated information about data; (5) robust languages for defining data structures and formats; (6) scientific data types and structures; (7) flexible physical access mechanisms; (8) ways of representing spatial relationships; (9) a high level nonprocedural interactive query and data manipulation language; (10) data base maintenance utilities; (11) high rate input/output and large data volume storage; and adaptability to a distributed data base and/or data base machine configuration. Detailed functions are specified in a top-down hierarchic fashion. Implementation, performance, and support requirements are also given.

Lohman, G. M.↗

NASA NTRS2025

Integrating the Interconnections Between Groundwater and Land Surface Processes Through the Coupled NASA Land Information System and ParFlow Environment

Understanding the interactions between the atmosphere, the land, and the subsurface is fundamental to hydrology and is critical for a better assessment of the impacts of climate change and human management on hydrological systems. However, many land surface models simplify the subsurface hydrology and thereby these interactions. In this study, we couple the land surface model Noah-MP included in the NASA Land Information System (LIS) with the integrated hydrologic model ParFlow (ParFlow-LIS) using the Earth System Modeling Framework (ESMF) and the National United Operational Prediction Capability (NUOPC). This coupling improves the simulation of water and energy cycle processes by adding the three-dimensional variably saturated and heterogeneous flow in the subsurface using sophisticated and nonlinear physics-based equations as well as the advances in satellite remote sensing-based data assimilation of the land surface, thereby benefiting the integrated hydrologic modeling and data assimilation community. We use the High Plains aquifer, located in the central United States, as a testbed to evaluate the coupled ParFlow-LIS system. The new ParFlow-LIS system accounts for the effects of topographically driven flows on the land surface, producing more fine-scale patterns of land surface states and fluxes than standalone LIS. In addition, ParFlow-LIS enables the consideration of the effect of subsurface water storage on evapotranspiration. This is particularly important in areas and times with dry soils, such as during drought conditions or in the presence of a cone of depression due to pumping.

land surface modeling↗

NASA NTRS1987

Study of pre-storm environment by using rawinsonde and satellite observations

Rawinsonde and satellite remote sensing data were utilized to examine the prestorm environment and mechanisms for the initiation of four groups of severe storms. The storms in Altus, Oklahoma, Pampas, Texas, Bennett, Colorado, and Red River Valley, Oklahoma are described. The geographical distributions of the areas of high moisture concentration and variations of tropopause heights for the storm groups are analyzed. It is detected that in the area of a low-level high concentration of moisture, the local tropopause height is lowest at the time of the storm cloud formation and development, and the potential energy storage per unit areas for the overshootiong clouds penetrating above the tropopause is related to the intensity of the storms produced. Numerical cloud modeling was performed for the storms. The model data are compared with the satellite and rawinsonde observations, and it is noted that the data correlate well.

Hung, R. J.↗

DOE OSTI2024

Watching the Grand Ethiopian Renaissance Dam from a distance: Implications for sustainable water management of the Nile water

Increased demands for sustainable water and energy resources in densely populated basins have led to the construction of dams, which impound waters in artificial reservoirs. In many cases, scarce field data led to the development of models that underestimated the seepage losses from reservoirs and ignored the role of extensive fault networks as preferred pathways for groundwater flow. We adopt an integrated approach (remote sensing, hydrologic modeling, and field observations) to assess the magnitude and nature of seepage from such systems using the Grand Ethiopian Renaissance Dam (GERD), Africa's largest hydropower project, as a test site. The dam was constructed on the Blue Nile within steep, highly fractured, and weathered terrain in the western Ethiopian Highlands. The GERD Gravity Recovery and Climate Experiment Terrestrial Water Storage (GRACETWS), seasonal peak difference product, reveals significant mass accumulation (43 ± 5 BCM) in the reservoir and seepage in its surroundings with progressive south-southwest mass migration along mapped structures between 2019 and 2022. Seepage, but not a decrease in inflow or increase in outflow, could explain, at least in part, the observed drop in the reservoir's water level and volume following each of the three fillings. Using mass balance calculations and GRACETWS observations, we estimate significant seepage (19.8 ± 6 BCM) comparable to the reservoir's impounded waters (19.9 ± 1.2 BCM). Investigating and addressing the seepage from the GERD will ensure sustainable development and promote regional cooperation; overlooking the seepage would compromise hydrological modeling efforts on the Nile Basin and misinform ongoing negotiations on the Nile water management.

GRACE and GRACE-FO↗

DOE OSTI2020

Improving Land Cover Classification Using Extended Multi-Attribute Profiles (EMAP) Enhanced Color, Near Infrared, and LiDAR Data

Hyperspectral (HS) data have found a wide range of applications in recent years. Researchers observed that more spectral information helps land cover classification performance in many cases. However, in some practical applications, HS data may not be available, due to cost, data storage, or bandwidth issues. Instead, users may only have RGB and near infrared (NIR) bands available for land cover classification. Sometimes, light detection and ranging (LiDAR) data may also be available to assist land cover classification. A natural research problem is to investigate how well land cover classification can be achieved under the aforementioned data constraints. In this paper, we investigate the performance of land cover classification while only using four bands (RGB+NIR) or five bands (RGB+NIR+LiDAR). A number of algorithms have been applied to a well-known dataset (2013 IEEE Geoscience and Remote Sensing Society Data Fusion Contest). One key observation is that some algorithms can achieve better land cover classification performance by using only four bands as compared to that of using all 144 bands in the original hyperspectral data with the help of synthetic bands generated by Extended Multi-attribute Profiles (EMAP). Moreover, LiDAR data do improve the land cover classification performance even further.

58 GEOSCIENCES↗

NASA NTRS2001

SIMBIOS Data Product and Algorithm Validation with Emphasis on the Biogeochemical and Inherent Optical Properties

The purpose of our component of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program is to address and quantify the relative accuracy of the various ocean color remote sensing products by means of product and algorithm validation. In order to accomplish these goals, we have been collaborating in an international research program in the Gulf of California designed to examine the spatial and temporal bio-optical variability in this region. In addition, we participated in various cruises of opportunity to supplement our validation data set. Our long-term objectives are to: (1) collect optical and biochemical data in oceanic and coastal regions of interest; (2) provide collected data to the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) Bio-Optical Archive and Storage System (SeaBASS) database, the SIMBIOS project office, and other interested users; (3) maintain and update instrumentation and data archiving and dissemination systems; and (4) determine spatial and temporal error fields for the biological and geophysical data products from the various ocean color missions.

Zaneveld, J. Ronald V.↗

NASA NTRS2007

Simple, Script-Based Science Processing Archive

The Simple, Scalable, Script-based Science Processing (S4P) Archive (S4PA) is a disk-based archival system for remote sensing data. It is based on the data-driven framework of S4P and is used for data transfer, data preprocessing, metadata generation, data archive, and data distribution. New data are automatically detected by the system. S4P provides services such as data access control, data subscription, metadata publication, data replication, and data recovery. It comprises scripts that control the data flow. The system detects the availability of data on an FTP (file transfer protocol) server, initiates data transfer, preprocesses data if necessary, and archives it on readily available disk drives with FTP and HTTP (Hypertext Transfer Protocol) access, allowing instantaneous data access. There are options for plug-ins for data preprocessing before storage. Publication of metadata to external applications such as the Earth Observing System Clearinghouse (ECHO) is also supported. S4PA includes a graphical user interface for monitoring the system operation and a tool for deploying the system. To ensure reliability, S4P continuously checks stored data for integrity, Further reliability is provided by tape backups of disks made once a disk partition is full and closed. The system is designed for low maintenance, requiring minimal operator oversight.

Lynnes, Christopher↗

NASA NTRS1992

System of Experts for Intelligent Data Management (SEIDAM)

It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗

NASA NTRS1993

System of experts for intelligent data management (SEIDAM)

A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗

NASA NTRSDate not supplied

Characterizing Martian Volcanic Provinces’ Magmatic Evolution and Chemistry through Equations of State Modeling Initial Study

Here we discuss a novel interdisciplinary approach to investigating igneous compositions of large volcanic provinces on Mars using remote sensing data sets (Mars Odyssey Gamma Ray and neutron Spectrometer suite--GRS, and gravity) to inform petrologic and thermoelastic modeling. Martian volcanic provinces, starting from Noachian to Amazonian age, including Elysium (EVP), are locations of great geologic interest which have been active over long time scales from Hesperian to Amazonian. Regional scale change in eruptive processes are poorly understood. Compared to large igneous provinces on Earth, the martian volcanic activity has persisted for orders of magnitude longer. Therefore, changes in mantle chemistry, pressure, and temperature during lithospheric cooling are expected to produce significant changes in the conditions of magma production, storage and ascent, affecting the degree of fractional crystallization and crustal contamination. In this study, we perform a detailed modeling to test the hypothesis that compositional variability within volcanic provinces resulted from spatiotemporal changes in the depth of magma formation and present initial results. Our methods include constraining the pressure and temperature conditions of EVP as a case study of geologically recent magmatic evolution on Mars using GRS informed surface chemistry constraints and pMELTS modeling. Second, we place constraints on the density and seismic velocities of the EVP melt through thermoelastic modeling with a local gravity analysis. This analysis is also extended to Noachian aged volcanic provinces on Mars initial results estimates mantle pressure for each sub-region is 16 kbar pressure, whereas, degree of partial melting is low and varies between 10 to 12. This study aims to validate our theoretical model and develop a perspective view of spatiotemporal changes at the interior of Mars throughout the time.

Martian science, Mars, geology, geophysics↗

NASA NTRS2021

An Evaluation of Remotely Sensed and In-Situ Data Sufficiency for SGMA-Scale Groundwater Studies in the Central Valley, California

California’s Central Valley aquifer is a critical freshwater resource for the state, providing drinking water to 6.5 million residents and irrigation water for more than half of the nation’s produce. Increasing demands have led to a steady decline of aquifer water levels, leading to irreversible compaction and land subsidence. The Sustainable Groundwater Management Act of California (SGMA), instituted in 2014, requires high-priority regions to establish sustainability plans by 2020-2022 that mitigate groundwater depletion and land subsidence. Many regions within the Central Valley lack groundwater monitoring wells or continuous well data, rendering in-situ monitoring challenging. When combined with other data, NASA’s Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) missions provide valuable information about groundwater storage changes at a sub-basin scale. Interferometric Surface Aperture Radar (InSAR) measurements can map land subsidence, and Global Positioning System (GPS) can be used to estimate crustal uplift. Yet, all of these measurements have differences in resolution, coverage, discretization, and record length. Here we assess the various datasets that are potentially useful for Central Valley sub-basin groundwater monitoring and provide an analysis of gaps and other issues in regard to their suitability for SGMA-related analysis. Finally, we offer next steps and recommendations on data treatment and integration.

Kyra H Kim↗

NASA NTRS2010

Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation, this book chapter has 3 main objectives: a) To describe in detail the field methodologies used to derive accurate estimates of biomass in mangrove forests b) To explain how mangrove forest biomass can be measured using several remote sensing techniques and datasets c) To give a detailed explanation of the measurement challenges and errors that arise in each estimate of forest biomass

Fatoyinbo, Temilola E.↗

NASA NTRS1990

Field testing of thermal canopy models in a spruce-fir forest

Recent advances in remote sensing technology allow the use of the thermal infrared region to gain information about vegetative surfaces. Extending existing models to account for thermal radiance transfers within rough forest canopies is of paramount importance. This is so since all processes of interest in the physical climate system and biogeochemical cycles are thermally mediated. Model validation experiments were conducted at a well established boreal forest; northern hardwood forest ecotone research site located in central Maine. Data was collected to allow spatial and temporal validation of thermal models. Emphasis was placed primarily upon enhancing submodels of stomatal behavior, and secondarily upon enhancing boundary layer resistance submodels and accounting for thermal storage in soil and vegetation.

Source record↗