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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

A Method for Correlating Forward-Looking Remote Sensor Measurements with In-Situ Measurements on Flying Platforms

A method is described for correlating measurements from a forward looking remote sensor with measurements made by in-situ instruments installed on the same flying platform. This method assumes that remote measurements are made within a volume of space in advance of the aircraft and that in-situ measurements provide representative values for discrete segments along the flight path. This correlation method can be applied to multiple sensors and makes no assumptions about the type of remote sensor or in-situ instrument, nor what either measures. It may be applied to recorded data during post-flight analysis based on known 4-D location (geospacial position and time) measurements.

Justin K. Strickland↗
NASA NTRS1975

Spectral measurements and analyses of atmospheric effects on remote sensor data

The radiance as measured by a satellite remote sensor is determined by a number of different factors, including the intervening atmosphere, the target reflectivity characteristics, the characteristics of the total incident solar irradiance, and the incident solar irradiance/sensor viewing geometry. Measurement techniques and instrumentation are considered, taking into account total and diffuse solar irradiance, target reflectance/radiance, atmospheric optical depth/transmittance, and atmospheric path radiance.

Hulstrom, R. L.↗
NASA NTRS1977

Atmospheric transformation of multispectral remote sensor data

The author has identified the following significant results. The effects of earth's atmosphere were accounted for, and a simple algorithm, based upon a radiative transfer model, was developed to determine the radiance at earth's surface free of atmospheric effects. Acutal multispectral remote sensor data for Lake Erie and associated optical thickness data were used to demonstrate the effectiveness of the atmospheric transformation algorithm. The basic transformation was general in nature and could be applied to the large scale processing of multispectral aircraft or satellite remote sensor data.

Turner, R. E.↗
NASA NTRS1973

A technique for interpretation of multispectral remote sensor data

The author has identified the following significant results. The U.S. Army Engineer Waterways Experiment Station is engaged in a study to detect from ERTS-1 satellite data alterations to the absorption and scattering properties caused by movement of suspended particles and solutes in selected areas of the Chesapeake Bay and to correlate the data to determine the feasibility of delineating flow patterns, flushing action of the estuary, and sediment and pollutant dispersion. As a part of this study, ADP techniques have been developed that permit automatic interpretation of data from any multispectral remote sensor with computer systems which have limited memory capacity and computing speed. The multispectral remote sensor is considered as a reflectance spectrophotometer. The data which define the spectral reflectance characteristics of a scene are scanned pixel by pixel. Each pixel whose spectral reflectance matches a reference spectrum is identified, and the results are shown in a map that identifies the locations where spectrum matches were detected and spectrum that was matched. The interpretation technique is described and an example of interpreted data from ERTS-1 is presented.

Williamson, A. N.↗
NASA NTRS1976

Performance modeling of earth resources remote sensors

A technique is presented for constructing a mathematical model of an earth resources remote sensor. The technique combines established models of electronic and optical components with formulated models of scan and vibration effects, and it includes a model of the radiation effects of the earth's atmosphere. The resulting composite model is useful for predicting in-flight sensor performance, and a descriptive set of performance parameters is derived in terms of the model. A method is outlined for validating the model for each sensor of interest. The validation for one airborne infrared scanning system is accomplished in part by a satisfactory comparison of predicted response with laboratory data for that sensor.

Kidd, R. H.↗
NASA NTRS1977

High-resolution spectropolarimetry - A new atmospheric remote sensor

Polarimetry within a spectral line or band is proposed as a new atmospheric remote sensor, particularly for clouds and hazes. The limitations of conventional absorption/emission spectroscopy and photopolarimetry are discussed. The selective formation and behavior of intensity and polarization lines is analyzed under a variety of atmospheric and scattering conditions. The technique, limitations and advantages of Fourier Transform Spectroscopy are reviewed as a prelude to the proposed approach. Experimental results obtained at the telescope for the planet Venus are presented as evidence for the existence, behavior and effects of line polarization. Fourier Transform Spectropolarimetry provides means for separating the effects of scattering from those of absorption, probing the internal properties of clouds and hazes, and studying the detailed wavelength dependence of polarization with variable spectral resolutions from low to high.

Fymat, A. L.↗
NASA NTRS1989

A multi-sensor remote sensing approach for measuring primary production from space

It is proposed to develop a multi-sensor remote sensing method for computing marine primary productivity from space, based on the capability to measure the primary ocean variables which regulate photosynthesis. The three variables and the sensors which measure them are: (1) downwelling photosynthetically available irradiance, measured by the VISSR sensor on the GOES satellite, (2) sea-surface temperature from AVHRR on NOAA series satellites, and (3) chlorophyll-like pigment concentration from the Nimbus-7/CZCS sensor. These and other measured variables would be combined within empirical or analytical models to compute primary productivity. With this proposed capability of mapping primary productivity on a regional scale, we could begin realizing a more precise and accurate global assessment of its magnitude and variability. Applications would include supplementation and expansion on the horizontal scale of ship-acquired biological data, which is more accurate and which supplies the vertical components of the field, monitoring oceanic response to increased atmospheric carbon dioxide levels, correlation with observed sedimentation patterns and processes, and fisheries management.

Gautier, Catherine↗
NASA NTRS1982

In situ ozone data for comparison with laser absorption remote sensor: 1980 PEPE/NEROS program

Several sets of in situ ozone (O3) measurements were made by a NASA aircraft in support of the laser absorption spectrometer (LAS) remote sensor. These measurements were designed to provide comparative O3 data for the LAS sensor. The LAS, which was flown on a second aircraft, remotely measured the vertical burden of O3 from the aircraft to the surface. In situ results of the air quality (O3 and B sub scat) and meteorological (temperature and dewpoint) parameters for three correlative missions are presented. The aircraft flight plans, in situ concentration profiles and vertical burdens, and measurement errors are summarized.

Mcdougal, D. S.↗
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 ↗