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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 NTRS2004

Remote Sensing Capabilities to Detect Maritime Vessels in Distress

The National Aeronautics and Space Administration (NASA) has the responsibility for conducting research and development for search and rescue as charged under the National Search and Rescue Plan. For over two decades this task has been undertaken by the Search and Rescue Mission Office at the NASA Goddard Space Flight Center (GSFC). The technology used by the highly successful beacon locating satellite system, Cospas-Sarsat, was conceived and developed at GSFC and is managed by the National Oceanographic and Atmospheric Administration (NOAA). Using beacon-less remote sensing to find people and vessels in distress complements the demonstrated life saving capabilities of this satellite system. The Search and Rescue Mission Office has been investigating the use of fully polarimetric synthetic aperture radar to locate crashed aircraft. An overview of this effort and potential maritime applications of Search and Rescue Synthetic Aperture Radar (SAR) will be presented. The Mission Office has also developed a Laser search and rescue system called L-SAR. The prototype instrument was designed and built by SenSyTech Inc. It specifically targets the location of novel retro-reflective material easily applied to rescue equipment and vessels in distress. An overview of this effort will also be presented.

Larsen, Rudolph K.↗
DOE OSTI2025

Optimizing Deep Learning Models for Climate-Related Natural Disaster Detection from UAV Images and Remote Sensing Data

This research study utilized artificial intelligence (AI) to detect natural disasters from aerial images. Flooding and desertification were two natural disasters taken into consideration. The Climate Change Dataset was created by compiling various open-access data sources. This dataset contains 6334 aerial images from UAV (unmanned aerial vehicles) images and satellite images. The Climate Change Dataset was then used to train Deep Learning (DL) models to identify natural disasters. Four different Machine Learning (ML) models were used: convolutional neural network (CNN), DenseNet201, VGG16, and ResNet50. These ML models were trained on our Climate Change Dataset so that their performance could be compared. DenseNet201 was chosen for optimization. All four ML models performed well. DenseNet201 and ResNet50 achieved the highest testing accuracies of 99.37% and 99.21%, respectively. This research project demonstrates the potential of AI to address environmental challenges, such as climate change-related natural disasters. This study’s approach is novel by creating a new dataset, optimizing an ML model, cross-validating, and presenting desertification as one of our natural disasters for DL detection. Three categories were used (Flooded, Desert, Neither). Our study relates to AI for Climate Change and Environmental Sustainability. Drone emergency response would be a practical application for our research project.

AI↗
NASA NTRS1973

Remote sensing in the detection of regional change.

Investigation of the impact of the California State Water Project on the west side of the San Joaquin Valley, using aerial photo mosaics and high-altitude photography for 1957 and 1971. Particular attention is paid to a determination of gross land use change and to the detection of specific patterns of development emerging from this change. Information derived from the mapping and tabulating of data acquired in this study indicates a definite trend toward the development of an agricultural landscape and increasing intensification of land use on the west side of the San Joaquin Valley. The introduction of water into this arid region is resulting in large acreages of land being brought under cultivation. Consequently, cropland is assuming a more dominant position with respect to areal extent.

Estes, J. E.↗
NASA NTRS1973

Analysis of remotely sensed data for detecting soil limitations

During 1971 and 1972 a detailed study was conducted on a fallow field in the proposed Oahe Irrigation Project to determine the relationship between the tonal variation observed on aerial photographs and the properties of eroded soil. Correlation and regression analysis of digitized, multiemulsion, color infrared film (2443) data and detailed field data revealed a highly significant correlation between film transmittance and several soil properties indicative of the erosion limitation. Computer classification of the multiemulsion film data resulted in maps portraying the eroded soil and the normal soil. Both correlation and computer classification results were best using the reflectance data from the red spectral band. The results showed film transmittance was actually measuring the reflectivity of the soil surface which was increased by the incorporation of the light colored, calcareous parent material exposed by erosion or tillage on soils with thin surface horizons.

Benson, L. A.↗
NASA NTRS1989

Using passive, thermal remote sensing techniques for detecting subsurface gravel accumulations in vegetated, unconsolidated sedimentary terrains

Multiband radiometric data from an airborne imaging thermal scanner are being studied for use in finding buried gravel deposits. The techniques are based on measuring relative differences in the thermal properties between gravel-laden targets and the surrounding gravelless background. These properties are determined from modeling the spectral radiant emittance recorded over both types of surfaces in conjunction with ground measurements of the most significant heat flows above and below the surface. Thermodynamic properties of sampled materials from control sites are determined, and diurnal and annual subsurface heat waves are recorded. Thermal models that account for heat exchange at the surface, as well as varying levels of soil moisture, humidity, and vegetation, are needed for adaptation and modification to simulate the physical and radiative environments of this region.

Burns, Gregory S.↗
NASA NTRS1974

Infrared differential absorption for atmospheric pollutant detection

Progress made in the generation of tunable infrared radiation and its application to remote pollutant detection by the differential absorption method are summarized. It is recognized that future remote pollutant measurements depended critically on the availability of high energy tunable transmitters. Futhermore, due to eye safety requirements, the transmitted frequency must lie in the 1.4 micron to 13 micron infrared spectral range.

Byer, R. L.↗
NASA NTRS1985

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Pelletier, R. E.↗
DOE OSTI2021

Pandora Thermal Subsystem Systems Engineering Class Project

Thousands of planets orbiting stars outside our solar system have been discovered, revealing an incredible diversity of planetary systems. One of the key questions in astrophysics is whether any of these distant worlds have atmospheres that could potentially support life. The presence of life can significantly alter the makeup of our atmosphere (as on Earth), leaving unique spectral fingerprints that can be detected via remote sensing. Life outside of our solar system may leave detectable traces in the atmospheres of distant exoplanets. Exoplanet transmission spectroscopy is a proven technique to probe the atmospheres of exoplanets that cross in front of—or transit—their star. During a transit, starlight filters through the planet’s atmosphere and that spectrum can reveal the atmosphere’s chemical makeup.

42 ENGINEERING↗
DOE OSTI2021

Feature Extraction: Improving Remote Sensor Classification of Non-Proliferation

This research focuses on developing algorithms for nuclear non-proliferation detection using remote sensor modeling. To improve the performance of classification models, we implemented a data pipeline with feature extraction. This pipeline takes raw data and transforms it into smaller data points called features that still describe the model. Improving this classification works towards the departments of energy’s missions of ensuring American’s security and prosperity by creating technology that addresses nuclear challenges. To conduct this analysis, we used the Python programming language and some key packages, including tsfresh and TSFEL. Originally tsfresh was selected because it has the most statistical features out of all the packages. Later TSFEL was incorporated due to the additional features it can extract from data, such as temporal and spectral. However, feature extraction becomes challenging in the presence of missing values. In this case, two additional Python packages were added to our workflow, NumPy and pandas, allowing for the feature extraction process to handle unknown values. Our data pipeline was tested on data collected from a simulation that describes the process state of a physical example. The results show the pipeline’s capability to consume and extract a total 17 features from tabular data. Future work includes producing classifications using decision tree-based models such as XGBoost and improving data collection by analyzing feature importance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1976

Procedure for detection and measurement of interfaces in remotely acquired data using a digital computer

A technique for the detection and measurement of surface feature interfaces in remotely acquired data was developed and evaluated. A computer implementation of this technique was effected to automatically process classified data derived from various sources such as the LANDSAT multispectral scanner and other scanning sensors. The basic elements of the operational theory of the technique are described, followed by the details of the procedure. An example of an application of the technique to the analysis of tidal shoreline length is given with a breakdown of manpower requirements.

Faller, K. H.↗
NASA NTRS2000

Applications in Bioastronautics and Bioinformatics: Early Radiation Cataracts Detected by Noninvasive, Quantitative, and Remote Means

Human exploration of Mars is a key goal in NASA's exploration planning in the next 20 years. Maintaining crew health and good vision is certainly an important aspect of achieving a successful mission. Continuous radiation exposure is a risk factor for radiation-induced cataracts in astronauts because radiation exposure in space travel has the potential of accelerating the aging process (ref. 1). A patented compact device (ref. 2) based on the technique of dynamic light scattering (DLS) was designed for monitoring an astronaut's ocular health during long-duration space travel. This capability of early diagnosis, unmatched by any other clinical technique in use today, may enable prompt initiation of preventive/curative therapy. An Internet web-based system integrating photon correlation data and controlling the hardware to monitor cataract development in vivo at a remote site in real time (teleophthalmology) is currently being developed. The new technology detects cataracts very early (at the molecular level). Cataract studies onboard the International Space Station will be helpful in quantifying any adverse effect of radiation to ocular health. The normal lens in a human eye, situated behind the cornea, is a transparent tissue. It contains 35 wt % protein and 65 wt % water. Aging, disease (e.g., diabetes), smoking, dehydration, malnutrition, and exposure to ultraviolet light and ionizing radiation can cause agglomeration of the lens proteins. Protein aggregation can take place anywhere in the lens, causing lens opacity. The aggregation and opacification could produce nuclear (central portion of the lens) or cortical (peripheral) cataracts. Nuclear and posterior subcapsular (the membrane's capsule surrounds the whole lens) cataracts, being on the visual optical axis of the eye, cause visual impairment that can finally lead to blindness. The lens proteins, in their native state, are small in size. As a cataract develops, this size grows from a few nanometers (transparent) to several micrometers (cloudy). Ansari and Datiles have shown that DLS can detect cataracts at least two to three orders of magnitude earlier noninvasively and quantitatively than the best imaging (Scheimpflug) techniques in clinical use today (ref. 3).

Ansari, Rafat R.↗
NASA NTRS1975

Application of remote sensing for prediction and detection of thermal pollution, phase 2

The development of a predictive mathematical model for thermal pollution in connection with remote sensing measurements was continued. A rigid-lid model has been developed and its application to far-field study has been completed. The velocity and temperature fields have been computed for different atmospheric conditions and for different boundary currents produced by tidal effects. In connection with the theoretical work, six experimental studies of the two sites in question (Biscayne Bay site and Hutchinson Island site) have been carried out. The temperature fields obtained during the tests at the Biscayne Bay site have been compared with the predictions of the rigid-lid model and these results are encouraging. The rigid-lid model is also being applied to near-field study. Preliminary results for a simple case have been obtained and execution of more realistic cases has been initiated. The development of a free-surface model also been initiated. The governing equations have been formulated and the computer programs have been written.

Veziroglu, T. N.↗
NASA NTRS1991

A passive infrared ice detection technique for helicopter applications

A technique has been developed, and successfully tested, to detect icing remotely on helicopter rotor blades. Using passive infrared (IR) thermometry it is possible to detect the warming caused by latent heat released as supercooled water freezes. During icing, the ice accretion region on the leading edge of the blade is found to be warmer than the uniced trailing edge resulting in a chordwise temperature profile characteristic of icing. Preliminary tests, using an IR Thermal video system, were conducted on a static model in the NASA Icing Research Tunnel (IRT) for a variety of wet (glaze) and dry (rime) ice conditions. A prototype detector system was built consisting of a single point IR pyrometer, and experiments were run on a small scale rotor model. Using this prototype detector, the characteristic chordwise temperature profiles were again observed for a range of icing conditions. Several signal processing methods were investigated, to allow automatic recognition of the icing signature. Additionally, several implementation issues were considered. Based on both the static and subscale rotor tests, where ice was successfully detected, the passive IR technique appears to be promising for rotor ice detection.

Dershowitz, Adam L.↗
NASA NTRS1982

Analysis of remote sensing data collected for detection and mapping of oil spills: Reduction and analysis of multi-sensor airborne data of the NASA Wallops oil spill exercise of November 1978

Airborne, remotely sensed data of the NASA Wallops controlled oil spill were corrected, reduced and analysed. Sensor performance comparisons were made by registering data sets from different sensors, which were near-coincident in time and location. Multispectral scanner images were, in turn, overlayed with profiles of correlation between airborne and laboratory-acquired fluorosensor spectra of oil; oil-thickness contours derived (by NASA) from a scanning fluorosensor and also from a two-channel scanning microwave radiometer; and synthetic aperture radar X-HH images. Microwave scatterometer data were correlated with dual-channel (UV and TIR) line scanner images of the oil slick.

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