Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “No system information”

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
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Mocko, David M.↗
NASA NTRS1977

An evaluation of coding methodologies for potential use in the Alabama Resource Information System (ARIS)-transportation study for the state of Alabama

Procedures developed for digitizing the transportation arteries, airports, and dock facilities of Alabama and placing them in a computerized format compatible with the Alabama Resource Information System are described. The time required to digitize by the following methods: (a) manual, (b) Telereadex 29 with film reading and digitizing system, and (c) digitizing tablets was evaluated. A method for digitizing and storing information from the U. T. M. grid cell base which was compatible with the system was developed and tested. The highways, navigable waterways, railroads, airports, and docks in the study area were digitized and the data stored. The manual method of digitizing was shown to be best for small amounts of data, while the graphic input from the digitizing tablets would be the best approach for entering the large amounts of data required for an entire state.

Montgomery, O. L.↗
NASA NTRS2012

Provenance Representation in the Global Change Information System (GCIS)

Global climate change is a topic that has become very controversial despite strong support within the scientific community. It is common for agencies releasing information about climate change to be served with Freedom of Information Act (FOIA) requests for everything that led to that conclusion. Capturing and presenting the provenance, linking to the research papers, data sets, models, analyses, observation instruments and satellites, etc. supporting key findings has the potential to mitigate skepticism in this domain. The U.S. Global Change Research Program (USGCRP) is now coordinating the production of a National Climate Assessment (NCA) that presents our best understanding of global change. We are now developing a Global Change Information System (GCIS) that will present the content of that report and its provenance, including the scientific support for the findings of the assessment. We are using an approach that will present this information both through a human accessible web site as well as a machine readable interface for automated mining of the provenance graph. We plan to use the developing W3C PROV Data Model and Ontology for this system.

Tilmes, Curt↗
DOE OSTI2024

Geographic Information System Mapping Tool for Rainwater Harvesting in the United States

The Rainwater Harvesting Tool is a publicly available web-based geographic information system tool developed using geospatial analysis in combination with historic ZIP Code level monthly average precipitation and evapotranspiration data across the United States to help select potential locations for harvesting rainwater. Rainwater harvesting can provide a key source of alternative water for a variety of uses including landscape irrigation, vehicle wash, cooling tower makeup, dust suppression, and toilet flushing. Rainwater harvesting can help support institutional, commercial, and residential buildings in diversifying water sources and offset the use of freshwater. This tool aims to help organizations strategically target locations to implement rainwater harvesting systems. The metric used in the tool is called the rainwater harvesting potential, which is a normalized metric, measured in inches per year. The rainwater harvesting potential describes the amount of rainwater that can be reasonably collected and stored at a specific location. This metric was used to rank areas delineated by ZIP Codes across the US, from lowest to highest to show the relative availability of rainwater for harvesting. Two mapping layers are included in the tool that show the general rainwater harvesting potential for all applications and a layer that specifically shows the potential for harvesting rainwater to supply irrigation The Rainwater Harvesting Tool allows users to view overall trends across the United States, while also allowing the user to zoom in to a scale where ZIP Code boundaries are clearly delineated. The tool can be used to help organizations with buildings located in multiple regions to strategically identify where to install rainwater harvesting systems and prioritize locations that may be optimal for rainwater harvesting.

47 OTHER INSTRUMENTATION↗
NASA NTRS2001

National Environmental Change Information System Case Study

The Global Hydrology and Climate Center and NASA's Marshall Space Flight Center conducted a fact-finding case study for the Data Management Working Group (DMWG), now referred to as the Data and Information Working Group (DIWG), of the U.S. Global Change Research Program (USGCRP) to determine the feasibility of an interagency National Environmental Change Information System (NECIS). In order to better understand the data and information needs of policy and decision makers at the national, state, and local level, the DIWG asked the case study team to choose a regional water resources issue in the southeastern United States that had an impact on a diverse group of stakeholders. The southeastern United States was also of interest because the region experiences interannual climatic variations and impacts due to El Nino and La Nina. Jointly, with input from the DIWG, a focus on future water resources planning in the Apalachicola-Chattahoochee-Flint (ACF) River basins of Alabama, Georgia, and Florida was selected. A tristate compact and water allocation formula is currently being negotiated between the states and U.S. Army Corps of Engineers (COE) that will affect the availability of water among competing uses within the ACF River basin. All major reservoirs on the ACF are federally owned and operated by the U.S. Army COE. A similar two-state negotiation is ongoing that addresses the water allocations in the adjacent Alabama-Coosa-Tallapoosa (ACT) River basin, which extends from northwest Georgia to Mobile Bay. The ACF and ACT basins are the subject of a comprehensive river basin study involving many stakeholders. The key objectives of this case study were to identify specific data and information needs of key stakeholders in the ACF region, determine what capabilities are needed to provide the most practical response to these user requests, and to identify any limitations in the use of federal data and information. The NECIS case study followed the terms of reference developed by the interagency DIWG. The case study "lessons learned" and "key findings" offer guidelines and considerations to the DMWG for the development and implementation of a NECIS that would support the data and information needs of policy and decision makers at the national, state, and local level.

Goodman, S. J.↗
NASA NTRS1986

The Johnson Space Center Management Information Systems (JSCMIS). 1: Requirements Definition and Design Specifications for Versions 2.1 and 2.1.1. 2: Documented Test Scenario Environments. 3: Security Design and Specifications

The Johnson Space Center Management Information System (JSCMIS) is an interface to computer data bases at NASA Johnson which allows an authorized user to browse and retrieve information from a variety of sources with minimum effort. This issue gives requirements definition and design specifications for versions 2.1 and 2.1.1, along with documented test scenario environments, and security object design and specifications.

Source record↗
NASA NTRS1990

Information systems requirements for the microgravity science and applications program

NASA's Microgravity Science and Applications (MSAD) Program is presented. Additionally, the types of information produced within the program and the anticipated growth in information system requirements as the program transitions to Space Station Freedom utilization are discussed. Plans for payload operations support in the Freedom era are addressed, as well as current activities to define research community requirements for data and sample archives.

Kicza, M. E.↗
NASA NTRS1991

Information systems requirements for the Microgravity Science and Applications Program

NASA's Microgravity Science and Applications (MSAD) Program is presented. Additionally, the types of information produced wiithin the program and the anticipated growth in information system requirements as the program transitions to Space Station Freedom utilization are discussed. Plans for payload operations support in the Freedom era are addressed, as well as current activities to define research community requirements for data and sample archives.

Kicza, M. E.↗
NASA NTRS1973

Unsupervised classification techniques as components of a data and information system

The phenomenal increase in the amount of data and information being generated by remote sensing systems is stressed. A total system design approach as a solution to this problem is discussed with specific reference to the data and information system needs for Sortie Lab - a multiple use payload for the Shuttle. The development of a multispectral data processing system as a needed component of such a system is reviewed with emphasis on unsupervised multispectral classification techniques developed and presently in use at Marshall Space Flight Center.

Cummings, R. E.↗
NASA NTRS1993

The development of a natural language interface to a geographical information system

This paper will discuss a two and a half year long project undertaken to develop an English-language interface for the geographical information system GRASS. The work was carried out for NASA by a small business, Netrologic, based in San Diego, California, under Phase 1 and 2 Small Business Innovative Research contracts. We consider here the potential value of this system whose current functionality addresses numerical, categorical and boolean raster layers and includes the display of point sets defined by constraints on one or more layers, answers yes/no and numerical questions, and creates statistical reports. It also handles complex queries and lexical ambiguities, and allows temporarily switching to UNIX or GRASS.

Toledo, Sue Walker↗
NASA NTRS1991

Traditional anthropology and geographical information systems in the collaborative study of Cassava in Africa

Cross-cultural, village-level, and farmer surveys have been used with a geographical information system to describe the distribution and relative importance of cassava (manioc, yuca, Manihot esculenta) in its cultural, economic, and ecological contexts. It presents examples of data management for mapping, sample selection, cross-tabulation of characteristics, combination of data types for indices and hypothesis testing. The methods used are reviewed, and some of the main conclusions of the study are presented.

Romanoff, Steven↗
NASA NTRS1994

A survey of geographical information systems applications for the Earth Science and Applications Division, Space Sciences Laboratory, Marshall Space Flight Center

The purpose of this document is to introduce Geographical Information System (GIS) terminology and summarize interviews conducted with scientists in the Earth Science and Applications Division (ESAD). There is a growing need in ESAD for GIS technology. With many different data sources available to the scientists comes the need to be able to process and view these data in an efficient manner. Since most of these data are stored in vastly different formats, specialized software and hardware are needed. Several ESAD scientists have been using a GIS, specifically the Man-computer Interactive Data Access System (MCIDAS). MCIDAS can solve many of the research problems that arise, but there are areas of research that need more powerful tools; one such example is the multispectral image analysis which is described in this document. Given the strong need for GIS in ESAD, we recommend that a requirements analysis and implementation plan be developed using this document as a basis for further investigation.

Rickman, D.↗
DOE OSTI2025

The Risk Assessment Information System Compendium of Ecological Screening Benchmarks for Chemicals and Radionuclides (2025) (Volume I – Text, Radionuclides for all Media, Chemicals for Air and Biota)

The Risk Assessment Information System Ecological Benchmark Tool compiles screening level benchmark values for assessing potential ecological risks posed by chemical and radionuclide contaminants. Drawing from a wide array of federal, state, and international sources, it consolidates benchmarks across environmental media, including soil, water, sediment, air, and biota, and presents values for a broad range of receptors and exposure pathways. The tool includes both effect-based and no-effect thresholds, with media- and organism-specific guidance derived from peer-reviewed literature and regulatory frameworks. By integrating diverse benchmark types into a unified reference, the tool supports consistent, scientifically grounded evaluations in ecological risk assessments and environmental management practices.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Analysis of Summer Thunderstorms in Central Alabama Using the NASA Land Information System

Forecasters have difficulty predicting "random" afternoon thunderstorms during the summer months. Differences in soil characteristics could be a contributing factor for storms. The NASA Land Information System (LIS) may assist forecasters in predicting summer convection by identifying boundaries in land characteristics. This project identified case dates during the summer of 2009 by analyzing synoptic weather maps, radar, and satellite data to look for weak atmospheric forcing and disorganized convective development. Boundaries in land characteristics that may have lead to convective initiation in central Alabama were then identified using LIS.

James, Robert↗
NASA NTRS2014

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Data Assimilation↗
NASA NTRS1993

Geographic information system for fusion and analysis of high-resolution remote sensing and ground data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System (GIS), integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a boreal forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case 1) calibrated DC-8 SAR (Synthetic Aperture Radar) data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case 2) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗
NASA NTRS2012

Workshop on the Development of an Experimental Global Drought Information System (GDIS): Overview of Workshop Goals

Among the key recommendations of a recent WCRP Workshop on Drought Predictability and Prediction in a Changing Climate is the development of an experimental global drought information system (GDIS). The timeliness of such an effort is evidenced by the wide aITay of relevant ongoing national and international (as well as regional and continental scale) efforts to provide drought information, including the US and North American drought monitors, and various integrating activities such as GEO and the Global Drought Portal. The workshop will review current capabilities and needs, and focus on the steps necessary to develop a GDIS that will build upon the extensive worldwide investments that have already been made in developing drought monitoring (including new space-based observations), drought risk management, and climate prediction capahilities.

Schubert, Siegfried↗
NASA NTRS1992

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗