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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗
NASA NTRS1997

JOVE Program

Coastal reef degradation and widespread bleaching of corals, i.e. loss of pigments and/or symbiotic zooxanthellae, is increasing globally. Remote sensing has great potential for assessing the extent of reef change. However, measuring reef change from remote platforms (boats, aircraft or satellites), requires ground-truth spectral algorithms characteristic of healthy and degraded reef populations. Our laboratory experiments demonstrated, for the first time, that healthy coral colonies emit characteristic fluorescence spectra in response to excitation with short wavelength (blue or ultraviolet) light. Furthermore, following stress, e.g. increased temperature, corals lose symbiotic algae and their health is compromised. We measured changes in coral fluorescence spectra along with pigment loss in response to temperature-induced stress. Following laboratory demonstration, we tested this approach in the field. The NASA P3 aircraft with the airborne oceanographic LIDAR system was used to map transects of coral reef in Hawaii. Ground truth samples of coral; were collected and analyzed for pigment density (pigments/surface area). Fluorescence spectra along transects showed consistent chlorophyll fluorescence peaks at 685 nm from the chlorophyll of the zooxanthellae and peaks between 400 and 570 nm believed to emanate from the coral tissue. Our results suggest that remote sensing of laser-induced fluorescence represents an efficient and effective approach to monitoring the health of coral reefs. Lists of papers, conferences, proposals awarded and a summary of student involvement is included in the appendices.

Hardy, John T.↗
NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗
NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗
NASA NTRS1987

U-238-U-234-Th-230-Th-232 systematics and the precise measurement of time over the past 500,000 years

A method is presented for the high-precision measurement of the Th-230 abundance in corals by isotope-dilution mass spectrometry using techniques developed by Chen and Wasserburg (1980, 1981) and Chen et al. (1986). It is shown that 6 x 10 to the 8th atoms of Th-230 can be measured to + or - 30 percent (2 sigma) and 2 x 10 to the 10th atoms of Th-230 to + or - 2 percent. The time over which useful age data on corals can be obtained ranges from a few years to about 500 ky, with the uncertainty in age ranging from 5 y for a 180-y-old coral, to 44 y for a 8294-y-old coral, to 1.1 ky for a 123.1-ky-old coral. Ages were determined with high analytical precision for several corals that grew during high sea-level stands about 120 ky ago, supporting the view that the dominant cause of Pleistocene climate change was Milankovitch forcing.

Edwards, R. Lawrence↗
NASA NTRS2018

NASA Fluid Lensing & MiDAR - Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

Piti's Tepungan Bay and Tumon Bay, two of five marine preserves in Guam, have not been mapped to a level of detail sufficient to support proposed management strategies. This project addresses this gap by providing high resolution maps to promote sustainable, responsible use of the area while protecting natural resources. Dr. Chirayath, a research scientist at the NASA Ames Laboratory, developed a theoretical model and algorithm called 'Fluid Lensing'. Fluid lensing removes optical distortions caused by moving water, improving the clarity of the images taken of the corals below the surface. We will also be using MiDAR, a next-generation remote sensing instrument that provides real-time multispectral video using an array of LED emitters coupled with NASA's FluidCam Imaging System, which may assist Guam's coral reef response team in understanding the severity and magnitude of coral bleaching events. This project will produce a 3D orthorectified model of the shallow water coral reef ecosystems in Tumon Bay and Piti marine preserves. These 3D models may be printed, creating a tactile diorama and increasing understanding of coral reefs among various audiences, including key decision makers. More importantly, the final data products can enable accurate and quantitative health assessment capabilities for coral reef ecosystems.

Aquatic↗
NASA NTRS1991

North-Australian tropical seas circulation study

This investigation is intended to fully address the stated objective of the TOPEX/POSEIDON mission (National Aeronautics and Space Administration, 1986). Hence, we intend to use TOPEX/POSEIDON altimetry data to study the large-scale circulation of the Coral Sea Basin and the Arafura Sea and the mass exchange between these and adjoining basins. We will obtain data from two such cruises in 1993 and 1994 and combine them with TOPEX/POSEIDON radar altimetry data to identify interannual and seasonal changes in: (1) the location of the major ocean currents and the South Equatorial Current bifurcation in the Coral Sea; (2) the source region of the South Tropical Counter Current (STCC); and (3) the water exchange between the Coral Sea and the adjoining seas. We will also estimate seasonal and interannual variations in the horizontal transport of mass and heat associated with near-surface geostrophic and wind-driven currents. In addition, the tidal components of the Coral Sea will be studied to provide a correction for altimetry subtidal sea level changes and to develop a regional numerical model for tidal forcing in the Great Barrier Reef (GBR) and Papua New Guinea Reef regions.

Burrage, Derek↗
NASA NTRS1994

Climatic, eustatic, and tectnoic controls on Quarternary deposits and landforms, Red Sea coast, Egypt

The degree to which local climatic variations, eustatic sea level fluctuations, and tectonic uplift have influenced the development of Quaternary marine and fluvial landforms and deposits along the Red Sea coast, Eastern Desert, was investigated using a combination of remote sensing and field data, age determinations of corals, and numerical simulations. False color composites generated from Landsat Thematic Mapper and SPOT image data, digital elevation models derived from sterophotogrammetric analysis of SPOT data, and field observations document that a approximately 10-km wide swath inland from the coast is covered in many places with coalescing alluvial fans of Quaternary age. Wadis cutting through the fans exhibit several pairs of fluvial terraces, and wadi walls expose alluvium interbedded with corraline limestone deposits Further, three distinct coral terraces are evident along the coatline. Climatic, eustatic, and tectonic uplift controls on the overall system were simulated using a cellular automata algorithm with the following characteristics: (1) uplift as a function of position and time, as defined by the elevations and ages of corals; (2) climatic variations driven by insolation changes associated with Milankovitch cycles; (3) sea level fluctuations based on U/Th ages of coral terraces and eustatic data; and (4) parametrized fluvial erosion and deposition. Results imply that the fans and coralline limestones were generated in a setting in which the tectonic uplift rate decreased over the Quarternary to negligible values at present. Coralline limestones formed furing eustatic highstands when alluvium was trapped uspstream and wadis filled with debris. During lowstands, wadis cut into sedimentary deposits; coupled with continuing uplift, fans were dissected, leaving remnant surfaces, and wadi-related terraces were generated by down cutting. Only landforms from the past three to four eustatic sea level cycles (i.e., approximately 300 to 400 kyr) are likely to have survived erosion and deposition associated with fluvial processes.

Arvidson, Raymond↗
NASA NTRS2019

Next-Generation Optical Sensing Technologies for Exploring Ocean Worlds - NASA FluidCam, MiDAR, and NeMO-Net

We highlight three emerging NASA optical technologies that enhance our ability to remotely sense, analyze, and explore ocean worlds–FluidCam and fluid lensing, MiDAR, and NeMO-Net. Fluid lensing is the first remote sensing technology capable of imaging through ocean waves without distortions in 3D at sub-cm resolutions. Fluid lensing and the purpose-built FluidCam CubeSat instruments have been used to provide refraction-corrected 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs). Results from repeat 2013 and 2016 airborne fluid lensing campaigns over coral reefs in American Samoa present a promising new tool for monitoring fine-scale ecological dynamics in shallow aquatic systems tens of square kilometers in area. MiDAR is a recently-patented active multispectral remote sensing and optical communications instrument which evolved from FluidCam. MiDAR is being tested on UAVs and autonomous underwater vehicles (AUVs) to remotely sense living and non-living structures in light-limited and analog planetary science environments. MiDAR illuminates targets with high-intensity narrowband structured optical radiation to measure an object’s spectral reflectance while simultaneously transmitting data. MiDAR is capable of remotely sensing reflectance at fine spatial and temporal scales, with a signal-to-noise ratio 10-10(exp 3) times higher than passive airborne and spaceborne remote sensing systems, enabling high-framerate multispectral sensing across the ultraviolet, visible, and near-infrared spectrum. Preliminary results from a 2018 mission to Guam show encouraging applications of MiDAR to imaging coral from airborne and underwater platforms whilst transmitting data across the air-water interface. Finally, we share NeMO-Net, the Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment. NeMO-Net is a machine learning technology under development that exploits high-resolution data from FluidCam and MiDAR for augmentation of low-resolution airborne and satellite remote sensing. NeMO-Net is intended to harmonize the growing diversity of 2D and 3D remote sensing with in situ data into a single open-source platform for assessing shallow marine ecosystems globally using active learning for citizen-science based training. Preliminary results from four-class Q17 coral classification have an accuracy of 94.4%. Together, these maturing technologies present promising scalable, practical, and cost-efficient innovations that address current observational and technological challenges in optical sensing of marine systems.

Ved Chirayath↗
NASA NTRS2003

Marine ecosystem appropriation in the Indo-Pacific: a case study of the live reef fish food trade

Our ecological footprint analyses of coral reef fish fisheries and, in particular, the live reef fish food trade (FT), indicate many countries' current consumption exceeds estimated sustainable per capita global, regional and local coral reef production levels. Hong Kong appropriates 25% of SE Asia's annual reef fish production of 135 260-286 560 tonnes (t) through its FT demand, exceeding regional biocapacity by 8.3 times; reef fish fisheries demand out-paces sustainable production in the Indo-Pacific and SE Asia by 2.5 and 6 times. In contrast, most Pacific islands live within their own reef fisheries means with local demand at < 20% of total capacity in Oceania. The FT annually requisitions up to 40% of SE Asia's estimated reef fish and virtually all of its estimated grouper yields. Our results underscore the unsustainable nature of the FT and the urgent need for regional management and conservation of coral reef fisheries in the Indo-Pacific.

Fishes↗
NASA NTRS1980

Global geochemical problems

Application of remote sensing techniques to the solution of geochemical problems is considered with emphasis on the 'carbon-cycle'. The problem of carbon dioxide sinks and the areal extent of coral reefs are treated. In order to assess the problems cited it is suggested that remote sensing techniques be utilized to: (1)monitor globally the carbonate and bicarbonate concentrations in surface waters of the world ocean; (2)monitor the freshwater and oceanic biomass and associated dissolved organic carbon; (3) inventory the coral reef areas and types and the associated oceanographic climatic conditions; and (4)measure the heavy metal fluxes from forested and vegetated areas, from volcanos, from different types of crustal rocks, from soils, and from sea surfaces.

Harriss, R. C.↗