Search NASA⌕ Search

SEARCH · Search NASA

Results for “Resource Management Software”

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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Benchmarking Near-Surface Winds in the HRRR Analyses Using Multisource Observations over Complex Terrain in the Southeastern United States

Wind energy plays a crucial role in sustainable power generation, yet its full potential in the southeast United States (SEUS) remains underexplored. This study advances wind resource assessment in the SEUS using existing regional modeling and multisource observations. We find that terrain complexity, influenced by orography and forest canopy, significantly impacts the accuracy of modeled wind speed. While the High-Resolution Rapid Refresh (HRRR) model effectively simulates wind profiles over flat, nonforested terrain, larger errors are produced above forest canopies, and particularly for those stands in hilly and mountainous terrain where there are no observations aloft that could be used by HRRR’s data assimilation software. Seasonal variations, e.g., changes in the leaf area index, further complicate the relationship between terrain complexity and simulation errors. Here, our findings emphasize the critical need for comprehensive wind profile measurements, extending from below the canopy to height above the canopy and through the lower planetary boundary layer, to fully quantify model performance over and near forests, and for improving wind resource assessment, planning, and management. This study provides valuable insights not only for further model development but also for future field campaign deployment with the goal of further improving our understanding of wind resources in the region.

Complex terrain↗
DOE OSTI2025

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Vibroacoustic Payload Environment Prediction System (VAPEPS): VAPEPS management center remote access guide

A Vibroacoustic Payload Environment Prediction System (VAPEPS) Management Center was established at the JPL. The center utilizes the VAPEPS software package to manage a data base of Space Shuttle and expendable launch vehicle payload flight and ground test data. Remote terminal access over telephone lines to the computer system, where the program resides, was established to provide the payload community a convenient means of querying the global VAPEPS data base. This guide describes the functions of the VAPEPS Management Center and contains instructions for utilizing the resources of the center.

Fernandez, J. P.↗
DOE OSTI2017

Offshore Storage Resource Assessment - Final Scientific/Technical Report

The DOE developed volumetric equation for estimating Prospective Resources (CO 2 storage) in oil and gas reservoirs was utilized on each depleted field in the Federal GOM. This required assessment of the in-situ hydrocarbon fluid volumes for the fields under evaluation in order to apply the DOE equation. This project utilized public data from the U.S. Department of the Interior, Bureau of Ocean Energy Management (BOEM) Reserves database and from a well reputed, large database (250,000+ wells) of GOM well and production data marketed by IHS, Inc. IHS interpreted structure map files were also accessed for a limited number of fields. The databases were used along with geological and petrophysical software to identify depleted oil and gas fields in the Federal GOM region. BOEM arranged for access by the project team to proprietary reservoir level maps under an NDA. Review of the BOEM’s Reserves database as of December 31, 2013 indicated that 675 fields in the region were depleted. NITEC identified and rank these 675 fields containing 3,514 individual reservoirs based on BOEM’s estimated OOIP or OGIP values available in the Reserves database. The estimated BOEM OOIP or OGIP values for five fields were validated by an independent evaluation using available petrophysical, geologic and engineering data in the databases. Once this validation was successfully completed, the BOEM ranked list was used to calculate the estimated CO 2 storage volume for each field/reservoir using the DOE CO 2 Resource Estimate Equation. This calculation assumed a range for the CO 2 efficiency factor in the equation, as it was not known at that point in time. NITEC then utilize reservoir simulation to further enhance and refine the DOE equation estimated range of CO 2 storage volumes. NITEC used a purpose built, publically available, 4-component, compositional reservoir simulator developed under funding from DOE (DE-FE0006015) to assess CO 2 -EOR and CO 2 storage in 73 fields/461 reservoirs. This simulator was fast and easy to utilize and provided a valuable enhanced assessment and refinement of the estimated CO 2 storage volume for each reservoir simulated. The user interface was expanded to allow for calculation of a probability based assessment of the CO 2 storage volume based on typical uncertainties in operating conditions and reservoir properties during the CO 2 injection period. This modeling of the CO 2 storage estimates for the simulated reservoirs resulted in definition of correlations applicable to all reservoir types (a refined DOE equation) which can be used for predictive purposes using available public data. Application of the correlations to the 675 depleted fields yielded a total CO 2 storage capacity of 4,748 MM tons. The CO 2 storage assessments were supplemented with simulation modeling of eleven (11) oil reservoirs that quantified the change in the stored CO 2 storage volume with the addition of CO 2 -EOR (Enhanced Oil Recovery) production. Application of CO 2 -EOR to oil reservoirs resulted in higher volumes of CO 2 storage.

02 PETROLEUM↗
NASA NTRS1993

ADP Analysis project for the Human Resources Management Division

The ADP (Automated Data Processing) Analysis Project was conducted for the Human Resources Management Division (HRMD) of NASA's Langley Research Center. The three major areas of work in the project were computer support, automated inventory analysis, and an ADP study for the Division. The goal of the computer support work was to determine automation needs of Division personnel and help them solve computing problems. The goal of automated inventory analysis was to find a way to analyze installed software and usage on a Macintosh. Finally, the ADP functional systems study for the Division was designed to assess future HRMD needs concerning ADP organization and activities.

Tureman, Robert L., Jr.↗
NASA NTRS1991

Landsat Legacy

The Landsat resources survey system spawned a number of companies engaged in commercial applications of remote sensing, among them International Imaging Systems (I2S). With initial NASA assistance, I2S has provided remote sensing hardware and software to several foreign countries, developed meteorological analysis systems, medical diagnostic software and scanning equipment for government and commercial use. Latest product is an advanced image-based photogrammetric system employing digital technology - not optical or mechanical systems - to generate terrain elevation data and other processing functions. Called PRI2SM, it compensates automatically for topographic relief displacement, is cheaper, faster, and easier to use and maintain. Company product line includes four major areas: image processing equipment for Earth Resources Management; meteorological analysis systems; satellite ground processing systems; and digital photogrammetric mapping systems.

Source record↗
NASA NTRS2004

Tree-mendous Timber Evaluation

Funded and administered by NASA, the Affiliated Research Center (ARC) program transfers geospatial technologies from the Space Agency and participating universities to commercial companies, non-profit and trade organizations, and tribal governments. The origins of the ARC program date back to 1988, when NASA's Stennis Space Center initiated the Visiting Investigator Program to bring industry closer to spatial information technologies. The success of this trial program led to an expansion into the ARC program, whose goal is to enhance competitiveness of U.S. industries through more efficient use of remote sensing and related technologies. NASA's ARC program served as the foundation for the development of International Hardwood Resources, which then grew into Falcon Informatics with the acquisition of a technology from a European software company and a change of business models. Doylestown, Pennsylvania-based Falcon Informatics is now a world-leading information services company that combines in-depth timber industry experience with state-of-the-art software to serve the needs of national governments, international paper companies, and timber-investment management organizations.

Source record↗
DOE OSTI2018

FY 2018 ARM Radar Plan

The fundamental objective of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility radar facility is to provide high-quality radar observations to the scientific user community with an overarching goal of improving the treatment of clouds and precipitation in climate models. Historically, ARM has operated zenith-profiling cloud radars at millimeter wavelengths at five of its facilities. Since 2010, 16 scanning systems have been added to the radar facility. The ARM radar facility has 33 radars in its possession at three fixed sites and three mobile facilities. A breakdown of the ARM radar assets is given below: 8 Scanning ARM Clouds Radar Systems (SACR: two radars on single pedestal; six 1st- and two 2nd- generation) 7 Ka-band ARM Zenith profiling Radar (KAZR: five 1st- and two 2nd-generation) 5 X-band Scanning ARM precipitation Radar (XSAPR: four 1st- and one 2nd-generation) 3 C-band Scanning ARM precipitation Radar (CSAPR: two 1st- and one 2nd-generation) 1 W-band ARM Cloud Radar (WACR) 1 Marine W-band ARM Cloud Radar (MWACR: configured to be deployed on a stable table or scanning pedestal). Of these radars, all but six (two SACRs [accounting for four radars], one KAZR, and one 1st-generation CSAPR) have operational assignments. Therefore, the current measurement strategy involves operating 27 radars, not including radar wind profilers (RWPs). This array of instruments represents a combination of scanning and profiling radars at ARM’s sites. In addition to the scanning capabilities, the radars at each site differ in operating frequency, technology, and complexity, but all are complex systems. Some of them were custom designed and built specifically for ARM. Typically, newer systems take a few years to reach operational maturity with adequate characterization, calibration, testing, and quality control. Due to various factors, not all of the radars have achieved an operationally mature status sufficient to provide high-quality data in a research environment. In addition, these radars are often deployed in remote locations and harsh environments to meet science needs. The remoteness of such complex systems is a considerable challenge for continuous operations. Tools needed for a research-level operational radar are not readily available from vendors, and many of the necessary system management tools, both hardware and software, to manage these systems must be developed in-house for such deployments. Based on experience over the past seven years, including conclusions from the first phase of the radar plan, implemented in mid-2016, it is clear that ARM cannot support the operation of all 27 currently deployed radars and expect to provide research-quality data (including higher-order products) with the current resources. Experience from the first phase of the radar plan has provided a better indication than has been available previously of what size radar network is reasonable. A preliminary proposal for what that radar network could look like is provided here. The plan presented here uses the available resources to best support this proposed network.

ARM Mobile Facility↗
NASA NTRS2004

Telescience Resource Kit Software Capabilities and Future Enhancements

The Telescience Resource Kit (TReK) is a suite of PC-based software applications that can be used to monitor and control a payload on board the International Space Station (ISS). This software provides a way for payload users to operate their payloads from their home sites. It can be used by an individual or a team of people. TReK provides both local ground support system services and an interface to utilize remote services provided by the Payload Operations Integration Center (POIC). by the POIC and to perform local data functions such as processing the data, storing it in local files, and forwarding it to other computer systems. TReK can also be used to build, send, and track payload commands. In addition to these features, work is in progress to add a new command management capability. This capability will provide a way to manage a multi- platform command environment that can include geographically distributed computers. This is intended to help those teams that need to manage a shared on-board resource such as a facility class payload. The environment can be configured such that one individual can manage all the command activities associated with that payload. This paper will provide a summary of existing TReK capabilities and a description of the new command management capability. For example, 7'ReK can be used to receive payload data distributed

Schneider, Michelle↗
DOE OSTI2025

NFPA Distributed Energy Resources Safety Training (DERST) For Emergency Responders

The National Fire Protection Association, with support from the Department of Energy, executed a multi-year initiative to develop, enhance, and disseminate Distributed Energy Resources Safety Training (DERST) tools for U.S. emergency responders. As Distributed Energy Resources (DER)—such as solar photovoltaics, battery energy storage systems (ESS), electric vehicles (EVs), and associated infrastructure—become increasingly prevalent, the NFPA identified a critical need for up-to-date standardized, accessible, and effective safety training tailored for the fire service and related public safety professionals. The project delivered a comprehensive suite of educational resources to improve responders’ abilities to safely manage DER-related incidents. This included: • Revised Modular Training Courses: Updated classroom-based DER safety courses, now modular and accessible nationwide through fire academies and the North American Fire Training Directors (NAFTD) network. • Live Burn Testing & Research: A full-scale controlled burn of a DER-equipped residential structure provided real-world data and insights, forming the basis for updated best practices. • A Gamified Simulation Tool – Firefighters Incident Response Simulation Tool (FIRST): A first-of-its-kind, multiplayer, scenario-based simulation using the Unreal Engine 5.0 to train responders in a realistic virtual, multi-DER incident environment. • Field Familiarization Software Tools & Prop Guide: Digital DER field familiarization evolutions software guide and a prop development manual to support field-based DER training exercises, enhancing responders' hands-on familiarity with DER infrastructure and collaboration on virtual incident responses. • National Dissemination Strategy: Strategic partnerships with NAFTD, Vector Solutions, and others enabled wide-scale distribution, with over 5,000 departments accessing resources and 1,100+ departments adopting the simulator in the first seven months. Also provided a web portal for easy access to all training and simulation programs developed under this grant for the U.S. responder community. Key findings from the project—particularly from the burn test—led to paradigm shifts in fire response tactics. For example, traditional approaches to garage fires may be hazardous if DERs are present, due to explosive off gassing and thermal runaway risks. The new training emphasizes scene assessment, stand-off approaches, thermal imaging verification, and careful post-incident cooling of DER components to prevent reignition. This initiative has had a significant national impact, raising awareness, enhancing preparedness, and supporting safer DER incident response practices. Significant engagement from the media, public safety organizations, and PBS coverage has further amplified the reach and adoption of NFPA’s DER safety training, tools, and simulations.

14 SOLAR ENERGY↗
NASA NTRS2005

Diagnosis and Prognosis of Weapon Systems

The Prognostics Framework is a set of software tools with an open architecture that affords a capability to integrate various prognostic software mechanisms and to provide information for operational and battlefield decision-making and logistical planning pertaining to weapon systems. The Prognostics NASA Tech Briefs, February 2005 17 Framework is also a system-level health -management software system that (1) receives data from performance- monitoring and built-in-test sensors and from other prognostic software and (2) processes the received data to derive a diagnosis and a prognosis for a weapon system. This software relates the diagnostic and prognostic information to the overall health of the system, to the ability of the system to perform specific missions, and to needed maintenance actions and maintenance resources. In the development of the Prognostics Framework, effort was focused primarily on extending previously developed model-based diagnostic-reasoning software to add prognostic reasoning capabilities, including capabilities to perform statistical analyses and to utilize information pertaining to deterioration of parts, failure modes, time sensitivity of measured values, mission criticality, historical data, and trends in measurement data. As thus extended, the software offers an overall health-monitoring capability.

Nolan, Mary↗
NASA NTRS1998

Autonomous Satellite Command and Control through the World Wide Web: Phase 3

NASA's New Millenium Program (NMP) has identified a variety of revolutionary technologies that will support orders of magnitude improvements in the capabilities of spacecraft missions. This program's Autonomy team has focused on science and engineering automation technologies. In doing so, it has established a clear development roadmap specifying the experiments and demonstrations required to mature these technologies. The primary developmental thrusts of this roadmap are in the areas of remote agents, PI/operator interface, planning/scheduling fault management, and smart execution architectures. Phases 1 and 2 of the ASSET Project (previously known as the WebSat project) have focused on establishing World Wide Web-based commanding and telemetry services as an advanced means of interfacing a spacecraft system with the PI and operators. Current automated capabilities include Web-based command submission, limited contact scheduling, command list generation and transfer to the ground station, spacecraft support for demonstrations experiments, data transfer from the ground station back to the ASSET system, data archiving, and Web-based telemetry distribution. Phase 2 was finished in December 1996. During January-December 1997 work was commenced on Phase 3 of the ASSET Project. Phase 3 is the subject of this report. This phase permitted SSDL and its project partners to expand the ASSET system in a variety of ways. These added capabilities included the advancement of ground station capabilities, the adaptation of spacecraft on-board software, and the expansion of capabilities of the ASSET management algorithms. Specific goals of Phase 3 were: (1) Extend Web-based goal-level commanding for both the payload PI and the spacecraft engineer; (2) Support prioritized handling of multiple PIs as well as associated payload experimenters; (3) Expand the number and types of experiments supported by the ASSET system and its associated spacecraft; (4) Implement more advanced resource management, modeling and fault management capabilities that integrate the space and ground segments of the space system hardware; (5) Implement a beacon monitoring test; (6) Implement an experimental blackboard controller for space system management; (7) Further define typical ground station developments required for Internet-based remote control and for full system automation of the PI-to-spacecraft link. Each of those goals is examined in the next section. Significant sections of this report were also published as a conference paper.

Cantwell, Brian↗
DOE OSTI2018

Moving Beyond Data Paralysis to Effective use of Building Analytics

As digital controls and smart meters become commonplace in commercial buildings, facilities teams have access to overwhelming amounts of data. This data does not typically lead to insights and corrective actions unless it is analyzed and prioritized in automated ways. Analytic software has been commercially available for over 20 years, but only recently have these tools seen increased adoption. This monitoring infrastructure helps uncover hidden operational opportunities, which is enticing for decision makers looking for short paybacks. Rather than single project savings, monitoring-based commissioning (MBCx) provides tools and processes to implement persistent, continuous improvement. What was formerly a data onslaught is now becoming a controlled resource for improved energy management. In 2016, a Research and Industry Partnership program was launched to support the use of analytics and diagnostics technologies and MBCx practices. This program couples technical assistance to owners to help increase adoption with a data collection effort to inform industry. It includes the most comprehensive data available nationally on analytics installation and use. The first-year results are in, with data from 46 organizations representing over 185 million square feet and 2,300 buildings. These organizations have achieved a median year-over-year energy savings of $0.20/sq ft with a median first year technology implementation cost of $0.12/sq ft. The paper summarizes attributes of successful analytics and MBCx installations, and cost-effectiveness results. The research provides insight for utilities considering adopting analytics technologies into incentive programs, for analytics developers to improve the performance of their solutions, and for commercial building facility staff considering these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Power Grid Simulation Testbed for Transactive Energy Management Systems

To effectively engage demand-side and distributed energy resources (DERs) for dynamically maintaining the electric power balance, the challenges of controlling and coordinating building equipment and DERs on a large scale must be overcome. Although several control techniques have been proposed in the literature, a significant obstacle to applying these techniques in practice is having access to an effective testing platform. Performing tests at scale using real equipment is impractical, so simulation offers the only viable route to developmental testing at scales of practical interest. Existing power-grid testbeds are unable to model individual residential end-use devices for developing detailed control formulations for responsive loads and DERs. Furthermore, they cannot simulate the control and communications at subminute timescales. To address these issues, this paper presents a novel power-grid simulation testbed for transactive energy management systems. Detailed models of primary home appliances (e.g., heating and cooling systems, water heaters, photovoltaic panels, energy storage systems) are provided to simulate realistic load behaviors in response to environmental parameters and control commands. The proposed testbed incorporates software as it will be deployed, and enables deployable software to interact with various building equipment models for end-to-end performance evaluation at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

The application of automated operations at the Institutional Processing Center

The JPL Institutional and Mission Computing Division, Communications, Computing and Network Services Section, with its mission contractor, OAO Corporation, have for some time been applying automation to the operation of JPL's Information Processing Center (IPC). Automation does not come in one easy to use package. Automation for a data processing center is made up of many different software and hardware products supported by trained personnel. The IPC automation effort formally began with console automation, and has since spiraled out to include production scheduling, data entry, report distribution, online reporting, failure reporting and resolution, documentation, library storage, and operator and user education, while requiring the interaction of multi-vendor and locally developed software. To begin the process, automation goals are determined. Then a team including operations personnel is formed to research and evaluate available options. By acquiring knowledge of current products and those in development, taking an active role in industry organizations, and learning of other data center's experiences, a forecast can be developed as to what direction technology is moving. With IPC management's approval, an implementation plan is developed and resources identified to test or implement new systems. As an example, IPC's new automated data entry system was researched by Data Entry, Production Control, and Advance Planning personnel. A proposal was then submitted to management for review. A determination to implement the new system was made and elements/personnel involved with the initial planning performed the implementation. The final steps of the implementation were educating data entry personnel in the areas effected and procedural changes necessary to the successful operation of the new system.

Barr, Thomas H.↗
NASA NTRS1998

Autonomous Satellite Command and Control Through the World Wide Web

The Automated Space System Experimental Testbed (ASSET) system is a simple yet comprehensive real-world operations network being developed. Phase 3 of the ASSET Project was January-December 1997 and is the subject of this report. This phase permitted SSDL and its project partners to expand the ASSET system in a variety of ways. These added capabilities included the advancement of ground station capabilities, the adaptation of spacecraft on-board software, and the expansion of capabilities of the ASSET management algorithms. Specific goals of Phase 3 were: (1) Extend Web-based goal-level commanding for both the payload PI and the spacecraft engineer. (2) Support prioritized handling of multiple (PIs) Principle Investigators as well as associated payload experimenters. (3) Expand the number and types of experiments supported by the ASSET system and its associated spacecraft. (4) Implement more advanced resource management, modeling and fault management capabilities that integrate the space and ground segments of the space system hardware. (5) Implement a beacon monitoring test. (6) Implement an experimental blackboard controller for space system management. (7) Further define typical ground station developments required for Internet-based remote control and for full system automation of the PI-to-spacecraft link. Each of those goals are examined. Significant sections of this report were also published as a conference paper. Several publications produced in support of this grant are included as attachments. Titles include: 1) Experimental Initiatives in Space System Operations; 2) The ASSET Client Interface: Balancing High Level Specification with Low Level Control; 3) Specifying Spacecraft Operations At The Product/Service Level; 4) The Design of a Highly Configurable, Reusable Operating System for Testbed Satellites; 5) Automated Health Operations For The Sapphire Spacecraft; 6) Engineering Data Summaries for Space Missions; and 7) Experiments In Automated Health Assessment And Notification For The Sapphire Microsatellite.

Cantwell, Brian↗
NASA NTRS1972

Natural Resource Information System. Volume 1: Overall description

A prototype computer-based Natural Resource Information System was designed which could store, process, and display data of maximum usefulness to land management decision making. The system includes graphic input and display, the use of remote sensing as a data source, and it is useful at multiple management levels. A survey established current decision making processes and functions, information requirements, and data collection and processing procedures. The applications of remote sensing data and processing requirements were established. Processing software was constructed and a data base established using high-altitude imagery and map coverage of selected areas of SE Arizona. Finally a demonstration of system processing functions was conducted utilizing material from the data base.

Source record↗