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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 91 records · Page 5
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NASA NTRS2020

NeMO-Net – The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗
NASA NTRS1977

Analysis of laser fluorosensor systems for remote algae detection and quantification

The development and performance of single- and multiple-wavelength laser fluorosensor systems for use in the remote detection and quantification of algae are discussed. The appropriate equation for the fluorescence power received by a laser fluorosensor system is derived in detail. Experimental development of a single wavelength system and a four wavelength system, which selectively excites the algae contained in the four primary algal color groups, is reviewed, and test results are presented. A comprehensive error analysis is reported which evaluates the uncertainty in the remote determination of the chlorophyll a concentration contained in algae by single- and multiple-wavelength laser fluorosensor systems. Results of the error analysis indicate that the remote quantification of chlorophyll a by a laser fluorosensor system requires optimum excitation wavelength(s), remote measurement of marine attenuation coefficients, and supplemental instrumentation to reduce uncertainties in the algal fluorescence cross sections.

Browell, E. V.↗
NASA NTRS1994

Mars ozone: Mariner 9 revisited

The efficacy of the UV spectroscopy technique used by Mariner 9 to remotely measure ozone abundance at Mars is discussed. Previously-inferred ozone abundances could be underestimated by as much as a factor of 3, and much of the observed variability in the ozone abundance could be due to temporal and spatial variability in cloud and dust amount.

Lindner, Bernhard Lee↗
NASA NTRS1995

Mars ozone: Mariner 9 revisited

The efficacy of the UV reflectance spectroscopy technique used by Mariner 9 to remotely measure ozone abundance at Mars is discussed. Due to temporal and spatial variability in cloud and dust amount, previously inferred ozone abundances could be underestimated by a factor of 3. Until the large uncertainty in cloud and dust scattering properties and opacities can be reduced, the ozone abundance inferred by the reflectance spectroscopy technique will always have significant uncertainty.

Lindner, Bernhard Lee↗
NASA NTRS1991

Chemistry and mineralogy of Martian dust: An explorer's primer

A summary of chemical and mineralogical properties of Martian surface dust is offered for the benefit of engineers or mission planners who are designing hardware or strategies for Mars surface exploration. For technical details and specialized explanations, references should be made to literature cited. Four sources used for information about Martian dust composition: (1) Experiments performed on the Mars surface by the Viking Landers 1 and 2 and Earth-based lab experiments attempting to duplicate these results; (2) Infrared spectrophotometry remotely performed from Mars orbit, mostly by Mariner 9; (3) Visible and infrared spectrophotometry remotely performed from Earth; and (4) Lab studies of the shergottite nakhlite chassignite (SNC) clan of meteorites, for which compelling evidence suggests origin on Mars. Source 1 is limited to fine grained sediments at the surface whereas 2 and 3 contain mixed information about surface dust (and associated rock) and atmospheric dust. Source 4 has provided surprisingly detailed information but investigations are still incomplete.

Gooding, James L.↗
NASA NTRS1972

Environmental application of remote sensing methods to coastal zone land use and marine resource management. Appendix F: User's guide for advection, convection prototype

A user's manual is provided for the environmental computer model proposed for the Richmond-Cape Henry Environmental Laboratory (RICHEL) application project for coastal zone land use investigations and marine resources management. The model was developed around the hydrologic cycle and includes two data bases consisting of climate and land use variables. The main program is described, along with control parameters to be set and pertinent subroutines.

Source record↗
NASA NTRS1994

SEQ-POINTER: Next generation, planetary spacecraft remote sensing science observation design tool

Since Mariner, NASA-JPL planetary missions have been supported by ground software to plan and design remote sensing science observations. The software used by the science and sequence designers to plan and design observations has evolved with mission and technological advances. The original program, PEGASIS (Mariners 4, 6, and 7), was re-engineered as POGASIS (Mariner 9, Viking, and Mariner 10), and again later as POINTER (Voyager and Galileo). Each of these programs were developed under technological, political, and fiscal constraints which limited their adaptability to other missions and spacecraft designs. Implementation of a multi-mission tool, SEQ POINTER, under the auspices of the JPL Multimission Operations Systems Office (MOSO) is in progress. This version has been designed to address the limitations experienced on previous versions as they were being adapted to a new mission and spacecraft. The tool has been modularly designed with subroutine interface structures to support interchangeable celestial body and spacecraft definition models. The computational and graphics modules have also been designed to interface with data collected from previous spacecraft, or on-going observations, which describe the surface of each target body. These enhancements make SEQ POINTER a candidate for low-cost mission usage, when a remote sensing science observation design capability is required. The current and planned capabilities of the tool will be discussed. The presentation will also include a 5-10 minute video presentation demonstrating the capabilities of a proto-Cassini Project version that was adapted to test the tool. The work described in this abstract was performed by the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

Boyer, Jeffrey S.↗
NASA NTRS2000

Hyperspectral Imaging Sensors and the Marine Coastal Zone

Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

Richardson, Laurie L.↗
NASA NTRS2023

Multi-Campaign Ship and Aircraft Observations of Marine Cloud Condensation Nuclei and Droplet Concentrations

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosolcloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.

Atmospheric chemistry↗
NASA NTRS1993

Emissions of sulfur gases from marine and freshwater wetlands of the Florida Everglades - Rates and extrapolation using remote sensing

Rates of emissions of the biogenic sulfur (S) gases carbonyl sulfide (COS), methyl mercaptan (MSH), dimethyl sulfide (DMS), and carbon disulfide (CS2) were measured in a variety of marine and freshwater wetland habitats in the Florida Everglades during a short duration period in October using dynamic chambers, cryotrapping techniques, and gas chromatography. The most rapid emissions of over 500 nmol/sq m/h occurred in red mangrove-dominated sites that were adjacent to open seawater and contained numerous crab burrows. Poorly drained red mangrove sites exhibited lower fluxes of about 60 nmol/sq m/h, which were similar to fluxes from the black mangrove areas which dominated the marine-influenced wetland sites in the Everglades. DMS was the dominant organo-S gas emitted especially in the freshwater areas. Spectral data from a scene from the Landsat TM were used to map habitats in the Everglades. Six vegetation categories were delineated using geographical information system software and S gas emissions were extrapolated for the entire Everglades National Park. The black mangrove-dominated areas accounted for the largest portion of S gas emissions to the area. The large area extent of the saw grass communities accounted for about 24 percent of the total S emissions.

Hines, Mark E.↗
NASA NTRS1992

Emissions of sulfur gases from marine and freshwater wetlands of the Florida Everglades: Rates and extrapolation using remote sensing

Rates of emissions of the biogenic sulfur (S) gases carbonyl sulfide (COS), methyl mercaptan (MSH), dimethyl sulfide (DMS), and carbon disulfide (CS2) were measured in a variety of marine and freshwater wetland habitats in the Florida Everglades during a short duration period in October using dynamic chambers, cryotrapping techniques, and gas chromatography. The most rapid emissions of greater than 500 nmol/m(sup -2)h(sup -1) occurred in red mangrove-dominated sites that were adjacent to open seawater and contained numerous crab burrows. Poorly drained red mangrove sites exhibited lower fluxes of approximately 60 nmol/m(sup -2)h(sup -1) which were similar to fluxes from the black mangrove areas which dominated the marine-influenced wetland sites in the Everglades. DMS was the dominant organo-S gas emitted especially in the freshwater areas. Spectral data from a scene from the Landsat thematic mapper were used to map habitats in the Everglades. Six vegetation categories were delineated using geographical information system software and S gas emission were extrapolated for the entire Everglades National Park. The black mangrove-dominated areas accounted for the largest portion of S gas emissions to the area. The large area extent of the saw grass communities (42 percent) accounted for approximately 24 percent of the total S emissions.

Hines, Mark E.↗
NASA NTRS1981

Superflux I, II, and III experiment design: Remote sensing aspects

The Chesapeake Bay plume study called Superflux is described. The study was initiated to incorporate the disciplines of both resources management and remote sensing in accomplishing the following objectives: (1) process oriented research to understand the impact of estuarine outflows on continental shelf ecosystems; (2) monitoring and assessment to delineate the role of remote sensing in future monitoring and assessment programs; and (3) remote sensing research: to advance the state of the art in remote sensing systems as applied to sensing of the marine environment, thereby hastening the day when remote sensing can be used operationally for monitoring and assessment and for process oriented research.

Campbell, J. W.↗
NASA NTRS1989

The remote sensing of oceanic primary productivity - A review

The ocean is a major sink for atmospheric carbon dioxide. This paper assesses the correctness of the present estimates of the marine primary productivity, obtained by remote sensing techniques, by modeling the physiological mechanisms of carbon assimilation by phytoplankton. The model uses, as the input, measurements of the ocean-surface pigments and data on the incident solar irradiance, and incorporates a description of the photosynthetically available and usable irradiance in the ocean, to describe the light field required for photosynthesis. A comparison of measured and estimated values of the water-column integrated primary marine productivity over large ocean regions yielded favorable results. These estimates do not appear to depend on regional or seasonal factors.

Collins, Donald J.↗
NASA NTRS2002

Ocean observing satellite study: instrument and satellite constellation architecture options

This paper provides: (1) an overview of the set of active and passive instruments identified by the IPO designed to make the ocean measurements including visible and infrared medium and high resolution imagers, radiometers, altimeters, and synthetic aperture radars and (2) the instrument and satellite constellation architecture options studied, and their ability to meet the set of measurement requirements.

remote sensing marine oceanology↗
NASA NTRS2020

Remote Sensing of Diatom Bloom Succession

Marine diatoms are major biogeochemical and ecological “influencers” that contribute to a large fraction of the carbon export and supplying fisheries (Falkowski 2015). The fluxes of carbon transfer to the food web or to the deep ocean vary according to the stage of a diatom bloom (Du Toit 2018). Stages can be determined using inherent optical properties that reflect their physiological state, such as the chlorophyll fluorescence to particulate backscattering ratio (ChlF/b(sub bp), Cetinic et al. 2015). Identifying the bloom stage can potentially improve biogeochemical models of carbon export and fishery management. However, it is not yet possible to adequately determine the stage of phytoplankton blooms using satellites. Satellite-derived remote sensing reflectance R(sub rs)(𝜆) allow for remote identification of diatom blooms in the open ocean (Sathyendranath et al. 2004), and there are techniques to estimate the fluorescence quantum yield (𝜑) that, when high, can indicate the nutrient limitation that often takes place when blooms start to senesce (Behrenfeld et al. 2009). The goal of this study is to use the ratio between the normalized fluorescence line height from R(sub rs)(𝜆) (nFLH) and the particulate backscattering (b(sub bp)(443)) provided by satellites to identify exponentially growing and senescent diatom blooms from space.

Lange, Priscila K.↗
NASA NTRS1983

Satellites for the study of ocean primary productivity

The use of remote sensing techniques for obtaining estimates of global marine primary productivity is examined. It is shown that remote sensing and multiplatform (ship, aircraft, and satellite) sampling strategies can be used to significantly lower the variance in estimates of phytoplankton abundance and of population growth rates from the values obtained using the C-14 method. It is noted that multiplatform sampling strategies are essential to assess the mean and variance of phytoplankton biomass on a regional or on a global basis. The relative errors associated with shipboard and satellite estimates of phytoplankton biomass and primary productivity, as well as the increased statistical accuracy possible from the utilization of contemporaneous data from both sampling platforms, are examined. It is shown to be possible to follow changes in biomass and the distribution patterns of biomass as a function of time with the use of satellite imagery.

Smith, R. C.↗
NASA NTRS2003

Stray-Light Correction of the Marine Optical Buoy

In ocean-color remote sensing, approximately 90% of the flux at the sensor originates from atmospheric scattering, with the water-leaving radiance contributing the remaining 10% of the total flux. Consequently, errors in the measured top-of-the atmosphere radiance are magnified a factor of 10 in the determination of water-leaving radiance. Proper characterization of the atmosphere is thus a critical part of the analysis of ocean-color remote sensing data. It has always been necessary to calibrate the ocean-color satellite sensor vicariously, using in situ, ground-based results, independent of the status of the pre-flight radiometric calibration or the utility of on-board calibration strategies. Because the atmosphere contributes significantly to the measured flux at the instrument sensor, both the instrument and the atmospheric correction algorithm are simultaneously calibrated vicariously. The Marine Optical Buoy (MOBY), deployed in support of the Earth Observing System (EOS) since 1996, serves as the primary calibration station for a variety of ocean-color satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Japanese Ocean Color Temperature Scanner (OCTS) , and the French Polarization and Directionality of the Earth's Reflectances (POLDER). MOBY is located off the coast of Lanai, Hawaii. The site was selected to simplify the application of the atmospheric correction algorithms. Vicarious calibration using MOBY data allows for a thorough comparison and merger of ocean-color data from these multiple sensors.

Brown, Steven W.↗