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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Langley Automated Sensor Inter-calibration System (LASICS): Open Access Tools for Satellite Imager Inter-Calibration

Satellite imager calibration teams are tasked with maintaining stable measurement records to facilitate reliable monitoring of geophysical parameters and ensure dependable input for weather forecast models. Satellite imagers are neither uniformly calibrated nor radiometrically scaled to a common reference. Consistent inter-calibration between various earth-orbiting satellite imager pairs is a critical step in the creation of seamless earth-scene reflectance data records over time for input to higher level algorithms that retrieve earth system climate-sensitive properties. Each imager inherently by virtue of its optics (and associated properties like Spectral Response etc.) will have a unique measurement of the same earth-scene reflected signal. A key part of this is the identification and prediction of events where the imager pairs from their respective earth-orbits view the same stable terrestrial targets with nearly identical viewing and solar geometry. Langley Automated Sensor Inter-calibration System (LASICS) will provide the Earth remote sensing community with a foundation for the harmonization of these remote sensing records by the development of an intuitive, user-friendly, interactive web-based open access service that will leverage, an existing extensive and ever-growing database of earth-imager channel spectral response functions, on-demand capabilities for computation and visualization of spectral band adjustment factors using a variety of external hyper-spectral earth observation sources (e.g. SCIAMACHY, GOME-2 for VIS and IASI, AIRS for IR) and a variety of Solar Irradiance Spectra.

Arun Gopalan↗
NASA NTRSDate not supplied

Celestial Mapping System for Lunar Surface Mapping and Analytics

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

GIS system↗
NASA NTRS2022

An Advanced Open-Source Platform for Air Quality Analysis, Visualization, and Prediction

Ambient air pollution is the largest environmental health risk factor, leading to several million premature deaths globally per year. The challenge of combating poor air quality is exacerbated by growing urban populations, changing emissions, and a warming climate. While there have been many advances monitoring and modeling of atmospheric composition, reflected in the dramatic increase in archived Earth Observations, there is no single measurement or method that alone can provide an accurate depiction of the entire atmosphere. The rapidly growing collections of observational and modeling data require us to be smarter about what data to include, and how such data is used. In recent years, NASA has invested significantly in advancing the concepts for Analytics Collaborative Framework (ACF) [5] and New Observing Strategies (NOS) [4] to tackle our software infrastructure need for harmonized data management and dynamic acquisition of diverse measurements for on-demand, interactive, multivariate analysis, and access [3]. It is not enough to have a big data, standalone analytics solution; it is critical that we start integrating data from remote sensing, modeling, and in-situ networks in a harmonized manner that enables timely and data-driven decision-making for air quality management. This work presents the design and development of an Air Quality Analytics Collaborative Framework (AQ ACF), as part of NASA’s Advanced Information Systems Technology (AIST) effort, to establish a data, machine-learning, and numerically driven platform for air quality analysis, visualization, and prediction.

Liu, Qian↗
NASA NTRS1982

Structural analysis techniqes for remote sensing

The structural analysis of remotely sensed imagery is defined and basic techniques for implementing the process are described. Structural analysis uses knowledge of the properties of an entity, its parts and their relationships, and the relationships in which it participates at a higher level to locate and recognize objects in a visual scene. The representation of structural knowledge, the development of algorithms for using the knowledge to help analyze an image, and techniques for storage and retrieval of relational models are addressed.

Shapiro, L. G.↗
NASA NTRS2016

Landsat Program

Landsat initiated the revolution in moderate resolution Earth remote sensing in the 1970s. With seven successful missions over 40+ years, Landsat has documented - and continues to document - the global Earth land surface and its evolution. The Landsat missions and sensors have evolved along with the technology from a demonstration project in the analog world of visual interpretation to an operational mission in the digital world, with incremental improvements along the way in terms of spectral, spatial, radiometric and geometric performance as well as acquisition strategy, data availability, and products.

calibration↗
NASA NTRS1992

Exploring the remote sensing of foliar biochemical concentrations with AVIRIS data

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data shows promise for the estimation of foliar biochemical concentrations at the scale of the canopy. There are, however, several problems associated with the use of AVIRIS data in this way and these are detailed in recent Plant Biochemical Workshop Report. The research reported was concentrated upon three of these problems: field sampling of forest canopies, wet laboratory assay of foliar chemicals, and the visualization of AVIRIS data.

Smith, Geoffrey M.↗
NASA NTRS1975

A comparative interregional analysis of selected data from LANDSAT-1 and EREP for the inventory and monitoring of natural ecosystems

Comparative statistics were presented on the capability of LANDSAT-1 and three of the Skylab remote sensing systems (S-190A, S-190B, S-192) for the recognition and inventory of analogous natural vegetations and landscape features important in resource allocation and management. Two analogous regions presenting vegetational zonation from salt desert to alpine conditions above the timberline were observed, emphasizing the visual interpretation mode in the investigation. An hierarchical legend system was used as the basic classification of all land surface features. Comparative tests were run on image identifiability with the different sensor systems, and mapping and interpretation tests were made both in monocular and stereo interpretation with all systems except the S-192. Significant advantage was found in the use of stereo from space when image analysis is by visual or visual-machine-aided interactive systems. Some cost factors in mapping from space are identified. The various image types are compared and an operational system is postulated.

Poulton, C. E.↗
NASA NTRS1984

Irrigated rice area estimation using remote sensing techniques: Project's proposal and preliminary results

The development of a methodology for annual estimates of irrigated rice crop in the State of Rio Grande do Sul, Brazil, using remote sensing techniques is proposed. The project involves interpretation, digital analysis, and sampling techniques of LANDSAT imagery. Results are discussed from a preliminary phase for identifying and evaluating irrigated rice crop areas in four counties of the State, for the crop year 1982/1983. This first phase involved just visual interpretation techniques of MSS/LANDSAT images.

Parada, N. D. J.↗
NASA NTRS2018

Air Quality Satellite Monitoring by TROPOMI on Sentinel-5P

The recently launched Sentinel satellite mission, the Sentinel-5 Precursor (Sentinel-5P), is one of the European Space Agency's (ESA) new mission family – Sentinels. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), a nadir-viewing 108⁰ field-of-view push-broom grating hyperspectral spectrometer, covering the wavelengths of ultraviolet-visible (270 nm - 495 nm), near infrared (675 nm - 775 nm), and shortwave infrared (2305 nm - 2385 nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels, and is providing measurements of atmospheric chemistry, aerosols, and clouds at high spatial, temporal, and spectral resolution. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) supports over a thousand data collections in the focus areas of Atmospheric Composition, Water & Energy Cycles, and Climate Variability. Sentinel-5P TROPOMI Level-1B (L1B) and Level-2 (L2) products are curated at the GES DISC. Sentinel-5P data are provided by the European Union and the European Space Agency (ESA) through an agreement between ESA and NASA. Through its convenient and enhanced tools/services, such as OPeNDAP and L2 Subsetting, GES DISC offers the air quality remote sensing user community facile solutions for using complex Earth science data and applications. This presentation will demonstrate up-to-date TROPOMI products including EarthView (EV) radiance, solar irradiance, Aerosol Index, Carbon Monoxide, Total column Ozone, Nitrogen Dioxide, and cloud, as well as easy ways to access, visualize and subset TROPOMI data.

TROPOMI↗
NASA NTRS2021

Southern California Health & Air Quality: Using Remote Sensing to Detect the Frequency and Drivers of Red Tide Blooms in California to Assist in the Management of Human and Marine Exposure to Algal Toxins

In 2020, the dinoflagellate species Lingulodinium polyedra was measured at unprecedented levels off the southern California coast, raising concern for local communities. At high levels, L. polyedra can cause marine life mortality, food-borne illness, and respiratory-related health risks in humans. In partnership with the California Office of Environmental Health Hazard Assessment, the National Oceanic and Atmospheric Administration Southwest Fisheries Science Center, the California Department of Public Health, and the University of California San Diego’s Scripps Institution of Oceanography, this project utilized satellite imagery to visualize and analyze spatiotemporal trends of historical red tide events associated with L. polyedra. Using the Suomi National Polar-orbiting Partnership’s (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), Aqua’s Moderate Resolution Imaging Spectroradiometer (MODIS), and Global Change Observation Mission – Climate (GCOM-C) Second Generation Global Imager (SGLI), the team assessed the validity of using multiple sensors in detecting chlorophyll-a as a proxy for dinoflagellate dominated-algal blooms. The results suggest that VIIRS imagery processed using the Color Index algorithm from Hu et al. (2013), amongst all other algorithms and Earth observations assessed, shows the most promise in identifying L. polyedra blooms. The end products included an ArcGIS Dashboard and Google Earth Engine tool that when combined, provided users with spatial and temporal trends, interactive interfaces to analyze the effectiveness of various sensors and algorithms, and an overall contribution to aid in the management of human health and the economy impacted by harmful algal blooms.

Harmful algal bloom↗
NASA NTRSDate not supplied

Celestial Mapping System and Digital Lunar Library Initiative

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

3D Globe↗
NASA NTRS1981

Remote sensing applied to agriculture: Basic principles, methodology, and applications

The general principles of remote sensing techniques as applied to agriculture and the methods of data analysis are described. the theoretical spectral responses of crops; reflectance, transmittance, and absorbtance of plants; interactions of plants and soils with reflectance energy; leaf morphology; and factors which affect the reflectance of vegetation cover are dicussed. The methodologies of visual and computer-aided analyses of LANDSAT data are presented. Finally, a case study wherein infrared film was used to detect crop anomalies and other data applications are described.

Dejesusparada, N.↗
NASA NTRS1971

A survey of multispectral remote sensing techniques for earth resources applications.

Remote sensing for earth resources applications has as its objective the collection and interpretation of information on all environmentally significant features of the atmosphere, oceans, and land surfaces. This information is most effectively gathered by airborne and satellite borne imaging systems. These systems operate at a variety of wavelengths extending from the visual spectrum, through the infrared and into the centimeter wavelengths of the microwave band. A comparison is made of the signal characteristics at these spectrum regions. In particular, the ability of microwave radiometric imaging to augment visual and infrared imaging is discussed. Recent developments in electronically scanned microwave radiometric sensors are described, together with methods of optimizing microwave data display. Results achieved with integrated display systems for both microwave and optical data are presented, together with projections for future applications.-

Pascalar, H. G.↗
NASA NTRS1973

Initial evaluation of the geologic applications of ERTS-1 imagery for New Mexico

Coverage of approximately one-third of the test site, the state of New Mexico, had been received by January 31, 1973 and all of the images received were MSS products. Features noted during visual inspection of 91/2 x 91/2 prints include major structural forms, vegetation patterns, drainage patterns and outcrops of geologic formations having marked color contrasts. The Border Hills Structural Zone and the Y-O Structural Zone are prominently reflected in coverage of the Pecos Valley. A study of available maps and remote sensing material covering the Deming-Columbus area indicated that the limit of detection and the resolution of MSS products are not as good as those of aerial photographs, geologic maps, and manned-satellite photographs. The limit of detection of high contrast features on MSS prints in approximately 1000 feet or 300 meters for linear features and about 18 acres for roughly circular areas.

Vonderlinden, K.↗
NASA NTRSDate not supplied

Analysis of Spacecraft Materials Discrimination Using Color Indices for Remote Sensing for Space Situational Awareness

The increasing number of space missions have resulted in an augmented density of artificial objects positioned in orbital domains near Earth. Knowing the material composition of the resident space object can be of value in object identification and risk assessment using remote sensing techniques. To perform this task, it is increasingly imperative to optically characterize spacecraft materials to identify unique material-specific spectroscopic markers. In this work, a variety of materials frequently utilized by the aerospace industry in spacecraft design and construction were analyzed using reflectance spectroscopy. The collected data provide a spectral characterization baseline for modern-day and historical spacecraft materials. The color index was computed for standard astronomical and suggested theoretical filter passbands and compared to each other in their capability to discriminate materials belonging to different classes. The color index was calculated from reflectance spectra of common spacecraft materials in their pristine, as-received conditions that fell under different family groupings. Different color-index combinations were studied using color-color diagrams. Visual and quantitative analysis of the color-color diagrams were used to evaluate the possibility of discriminating materials from one another by means of optical measurements. Results of the analysis show that polyimide and photovoltaic materials are most easy to discriminate from all other materials via color indices using different filter passbands evaluated in this study.

spectral reflectance↗
NASA NTRS1973

Geological analysis and evaluation of ERTS-A imagery for the state of New Mexico

The author has identified the following significant results. Coverage of approximately one-third of the test site had been received by January 31, 1973 and all of the images received were MSS products. Images recorded during the first two months of the ERTS-1 mission were of poor quality, owing largely to high ground reflectance. Later images were of better quality and MSS bands 5 and 7 have proven to be particularly useful. Features noted during visual inspection of 9 1/2 x 9 1/2 prints include major structural forms, vegetation patterns, drainage patterns, and outcrops of geologic formations having marked color contrasts. The Border Hills Structural Zone and the Y-O Structural Zone are prominently reflected in coverage of the Pecos Valley. A study of available maps and remote sensing material covering the Deming-Columbus area indicated that the limit of detection and the resolution of MSS products are not as good as those of aerial photographs, geologic maps, and manned satellite photographs. The limit of detection of high contrast features on MSS prints is approximately 1000 feet or 300 meters for linear features and about 18 acres for roughly circular areas.

Kottlowski, F. E.↗