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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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Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. This is the post-processing results and final analysis results of applying target detection algorithms and then fusing the results.
An experimental Fraunhofer Line Discriminator (FLD) can differentiate and measure solar-stimulated luminescence when viewed against a background of reflected light. Key elements are two extremely sensitive photomultipliers, two glass-spaced Fabry-Perot filters having a bandwidth less than 1 A, and an analog computer. As in conventional fluorometers, concentration of a fluorescent substance is measured by comparison with standards. Quantitative use is probably accurate only at low altitudes but detection of luminescent substances should be possible from any altitude. Applications of the present FLD include remote sensing of fluorescent dyes used in studies of current dynamics. The basic technique is applicable to detection of oil spills, monitoring of pollutants, and sensing over land areas.
The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.
Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.
Conservation tillage practices can bring benefits to agricultural sustainability. Accurate spatial and temporal resolved information of field-scale crop residue cover, which reflects tillage intensity, is highly valuable for evaluating the outcomes of government conservation programs and voluntary ecosystem service markets, as well as facilitating agroecosystem modeling to quantify cropland biogeochemical processes. Remote sensing has the potential to cost-effectively detect crop residue cover, however, existing regional-scale studies were limited by insufficient ground truth data, scale mismatch between coarse satellite pixels and ground data, and the lack of key spectral data for detecting crop residues. Therefore, this study developed an innovative cross-sensing framework to integrate proximal sensing, airborne hyperspectral imaging, and satellite Earth Observation through deep learning to quantify field-level crop residue cover fractions at the regional scale. Specifically, we have collected intensive ground orthographic photos and conducted airborne hyperspectral surveys at corn and soybean fields of Champaign and nearby counties in Illinois, the heartland of the U.S. Corn Belt. Through semi-automatic labeling aided by ResNet-50 and superpixel image segmentation, we obtained 6719 records of ground residue fractions. With these ground data, we developed the 1-dimensional convolution neural network (CNN) model using airborne hyperspectral reflectance, which has 0.5m spatial resolution and 3–5 nm spectral resolution from 400 to 2400 nm, to predict residue fractions. By applying the CNN model to airborne pixels, we augmented “ground truth” data of crop residues and further combined them with Harmonized Landsat and Sentinel-2 (HLS) satellite data to quantify regional residue fractions at 30 m resolution. Results show that airborne hyperspectral imagery with CNN can accurately detect residue fractions (R 2 = 0.82, relative RMSE = 11.73%) to effectively generate quasi “ground truth” data to support satellite upscaling to all fields. With independent ground data for testing, we found that the ground-airborne-satellite integrative framework achieved better predictions in estimating crop residue cover (R 2 = 0.67, relative RMSE = 17.53%) than the conventional ground-satellite upscaling (R 2 = 0.22, relative RMSE = 32.09%). Here we also found that the shortwave infrared wavelengths, particularly 2100–2300 nm, are vital for predicting crop residue cover. Sentinel-2 and Landsat-8 data have a comparable capability to track residue fractions due to similar shortwave infrared wavelengths. This study highlights the high accuracy of hyperspectral imaging to detect agroecosystem tillage management practices and the advantages of cross-scale sensing to cost-effectively integrate multi-source data to quantify field-level agroecosystem variables across scales.
Benzene detection has been reported in Titans atmosphere both in the stratosphere at ppb levels by remote sensing and in the thermosphere at ppm levels by the Cassini's Ion and Neutral Mass Spectrometer. This detection supports the idea that aromatic and heteroaromatic reaction pathways may play an important role in Titans atmospheric chemistry, especially in the formation of aerosols. Indeed, aromatic molecules are easily dissociated by ultraviolet radiation and can therefore contribute significantly to aerosol formation. It has been shown recently that aerosol analogs produced from a gas mixture containing a low concentration of aromatic and/or heteroaromatic molecules (benzene, naphthalene, pyridine, quinoline and isoquinoline) have spectral signatures below 500/cm, a first step towards reproducing the aerosol spectral features observed by Cassini's Composite InfraRed Spectrometer (CIRS) in the far infrared. In this work we investigate the influence of environmental temperature on the absorption spectra of such aerosol samples, simulating the temperature range to which aerosols, once formed, are exposed during their transport through Titans stratosphere. Our results show that environmental temperature does not have any major effect on the spectral shape of these aerosol analogs in the far-infrared, which is consistent with the CIRS observations.
Feasibility of detecting sulfur dioxide in earth atmosphere from orbital altitudes
The project is reported for studying the application of remote sensing in land use classification and delineation of major tectonic lineaments in Nebraska. Other research reported include the use of aircraft and ERTS-1 satellite imagery in detecting and estimating the acreage of irrigated land, and the application of remote sensing in estimating evapotranspiration in the Platte River Basin.
Instruments for land tract scanning and fire detection include: temperature sensor capable of detecting distant match flame; elevated television camera with automatic controls for light balance, position, filter, and focus; and scanner equipped with photocell to sense intensity of flying spot brought to it by sweep-and-scan mechanism.
Multitemporal satellite data have application in the detection and quantification of drought through the ability of these data to estimate the photosynthetic capacity of the terrestrial surface and record microwave surface brightness at the 37 GHz frequency. With proper calibration and registration, comparisons can be made between and among years for specific months using the photosynthetic capacity and the 37 GHz microwave surface brightness for selected time periods or growing seasons. This technology has application in identifying and quantifying areas experiencing drought.
Satellite passive-microwave sensors provide a sensitive means of studying ice-sheet surface processes that assists ice-core interpretation and can extend local observations across regional scales. Analysis of special sensor microwave/imager (SSM/I) brightness temperature (TB) data supports ice-core research in two specific ways. First, the summer hoar complex layers used to date the Holocene portion of the Greenland Ice Sheet Project 2 ice core can be defined temporally and spatially by SSM/I 37-GHz vertically (V) and horizontally (H) polarized B ratio (V/H) trends. Second, comparison of automatic weather station temperatures to SSM/I 37-GHz V TB data shows that they are an effective proxy temperature record in this region. Also, the TB data can be correlated with proxy temperature trends from stable-isotope-ratio (delta O-18 and delta-D) profiles from snow pits and this allows the assignment of dates to specific snow depths.
THz spectroscopy of the atmosphere has been driven by the need to make remote sensing measurements of OH. While the THz region can be used for sensitive detection on many atmospheric molecules, the THz region is the best region for measuring the diurnal behavior of stratospheric OH by remote sensing. The infrared region near 3 microns suffers from chemiluminescence and from spectral contamination due to water. The ultraviolet region near 300 nm requires solar illumination. The three techniques for OH emission measurements in the THz region include Fourier Transform interferometry, Fabry-Perot interferometry, and heterodyne radiometry. The first two use cryogenic direct detectors while the last technique uses a local oscillator and a mixer to down convert the THz signal to GHz frequencies. All techniques have been used to measure stratospheric OH from balloon platforms. OH results from the Fabry-Perot based FILOS instrument will be given. Heterodyne measurement of OH at 2.5 THz has been selected to be a component of the Microwave Limb Sounder on the Earth Observing System CHEM-1 polar satellite. The design of this instrument will be described. A balloon-based prototype heterodyne 2.5 THz radiometer had its first flight on, 24 May 1998. Results form this flight will be presented.
The NASA Moderate Resolution Imaging Spectrometer (MODIS) on the Terra Spacecraft has been collecting scientific data since February of 2000. MODIS is a major facility instrument for remote sensing of the atmosphere, land surfaces, and ocean color. On the MODIS instruments, there are five channels located within and around the .0.94 micron water vapor band absorption region for remote sensing of atmospheric water vapor. There is also a channel located at 1.375 micron for detecting thin cirrus clouds. We will describe the basic principles for using these near-IR channels for remote sensing of water vapor and high clouds. Based on our analysis of two years# measurements with these channels, we have found that reliable observations of water vapor and high clouds on regional and global scales can be made. We will present results on daily, seasonal and annual variations of water vapor and high clouds.
From June to July 2009 more than thirty different in-situ and remote sensing instruments from all over the world participated in the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). The campaign took place at KNMI's Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Its main objectives were to determine the accuracy of state-ofthe- art ground-based measurement techniques for the detection of atmospheric nitrogen dioxide (both in-situ and remote sensing), and to investigate their usability in satellite data validation. The expected outcomes are recommendations regarding the operation and calibration of such instruments, retrieval settings, and observation strategies for the use in ground-based networks for air quality monitoring and satellite data validation. Twenty-four optical spectrometers participated in the campaign, of which twenty-one had the capability to scan different elevation angles consecutively, the so-called Multi-axis DOAS systems, thereby collecting vertical profile information, in particular for nitrogen dioxide and aerosol. Various in-situ samplers and lidar instruments simultaneously characterized the variability of atmospheric trace gases and the physical properties of aerosol particles. A large data set of continuous measurements of these atmospheric constituents has been collected under various meteorological conditions and air pollution levels. Together with the permanent measurement capability at the CESAR site characterizing the meteorological state of the atmosphere, the CINDI campaign provided a comprehensive observational data set of atmospheric constituents in a highly polluted region of the world during summertime. First detailed comparisons performed with the CINDI data show that slant column measurements of NO2, O4 and HCHO with MAX-DOAS agree within 5 to 15%, vertical profiles of NO2 derived from several independent instruments agree within 25% of one another, and MAX-DOAS aerosol optical thickness agrees within 20-30% with AERONET data. For the in-situ NO2 instrument using a molybdenum converter, a bias was found as large as 5 ppbv during day time, when compared to the other in-situ instruments using photolytic converters.
The Forward-Looking Interferometer (FLI) is a new instrument concept for obtaining the measurements required to alert flight crews to potential weather hazards to safe flight. To meet the needs of the commercial fleet, such a sensor should address multiple hazards to warrant the costs of development, certification, installation, training, and maintenance. The FLI concept is based on high-resolution Infrared Fourier Transform Spectrometry (FTS) technologies that have been developed for satellite remote sensing. These technologies have also been applied to the detection of aerosols and gases for other purposes. The FLI concept is being evaluated for its potential to address multiple hazards including clear air turbulence (CAT), volcanic ash, wake vortices, low slant range visibility, dry wind shear, and icing during all phases of flight (takeoff, cruise, and landing). The research accomplished in this second phase of the FLI project was in three major areas: further sensitivity studies to better understand the potential capabilities and requirements for an airborne FLI instrument, field measurements that were conducted in an effort to provide empirical demonstrations of radiometric hazard detection, and theoretical work to support the development of algorithms to determine the severity of detected hazards
In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.
Clouds have a critical role in many studies such as weather- and climate-related investigations. However, they represent a source of errors in many applications, and the presence of cloud contamination can hinder the use of satellite data. In addition, sending cloudy data to ground stations can result in an inefficient utilization of the communication bandwidth. This requires satellite on-board cloud detection capability to mask out cloudy pixels from further processing. Remote sensing satellite missions have always required smaller size, lower cost, more flexibility, and higher computational power. Reconfigurable Computers (RCs) combine the flexibility of traditional microprocessors with the power of Field Programmable Gate Arrays (FPGAs). Therefore, RCs are a promising candidate for on-board preprocessing. This paper presents the design and implementation of an RC-based real-time cloud detection system. We investigate the potential of using RCs for on-board preprocessing by prototyping the Landsat 7 ETM+ ACCA algorithm on one of the state-of-the-art reconfigurable platforms, SRC-6. It will be shown that our work provides higher detection accuracy and over one order of magnitude improvement in performance when compared to previously reported investigations.
A detailed study of circumstellar gas associated with young, intermediate-mass stars has demonstrated that, far from being unique or an infrequently occurring phenomenon, beta Pic-like infall activity is routinely observed in stars younger than 10-50 Myr when the observer's line of sight lies within 15 degrees of the disk mid-plane. Detailed studies of 2 Herbig Ae/Be stars, AB Aur and HD 163296 demonstrate that enhanced infall episodes last 20-60 hours, comparable to the duration of similar episodes in beta Pictoris. The infall activity is consistent with detection of the comae of swarms of star-grazing bodies of asteroidal to cometary composition. Episodic fluctuations in the infall activity are clearly present by approximately 6 Myr, and may indicate the presence of massive planets within the disk. This study has therefore, directly contributed to NASA's Origins of Planetary Systems theme by identifying under what conditions extra-solar planetesimals can be remotely sensed, indicating that such bodies appear to be routinely detectable among young stars in the 1-10 Myr range, and suggesting that temporal studies of spectroscopic variability may provide a means of identifying those systems harboring massive planets. This study has resulted in 2 refereed review papers, 13 other refereed papers, and 17 conference papers.