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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Automatic commanding of the Mars Observer Camera

Mars Observer, launched in September 1992, was intended to be a 'survey-type' mission that acquired global coverage of Mars from a low, circular, near-polar orbit during an entire Martian year. As such, most of its instruments had fixed data rates, wide fields of view, and relatively low resolution, with fairly limited requirements for commanding. An exception is the Mars Observer Camera, or MOC. The MOC consists of a two-color Wide Angle (WA) system that can acquire both global images at low resolution (7.5 km/pixel) and regional images at commandable resolutions up to 250 m/pixel. Complementing the WA is the Narrow Angle (NA) system, that can acquire images at 8 resolutions from 12 m/pixel to 1.5 m/pixel, with a maximum crosstrack dimension of 3 km. The MOC also provides various forms of data compression (both lossless and lossy), and is designed to work at data rates from 700 bits per second (bps) to over 80k bps. Because of this flexibility, developing MOC command sequences is much more difficult than the routine mode-changing that characterizes other instrument operations. Although the MOC cannot be pointed (the spacecraft is fixed nadir-pointing and has no scan platform), the timing, downlink stream allocation, compression type and parameters, and image dimensions of each image must be commanded from the ground, subject to the constraints inherent in the MOC and the spacecraft. To minimize the need for a large operations staff, the entire command generation process has been automated within the MOC Ground Data System. Following the loss of the Mars Observer spacecraft in August 1993, NASA intends to launch a new spacecraft, Mars Global Surveyor (MGS), in late 1996. This spacecraft will carry the MOC flight spare (MOC 2). The MOC 2 operations plan will be largely identical to that developed for MOC, and all of the algorithms described here are applicable to it.

Caplinger, Michael↗
NASA NTRS1986

Optical and UV spectroscopy of the peculiar RS CVn system RT Lacertae

H-alpha and H-beta spectra of the peculiar double-lined RS CVn binary RT Lacertae have been obtained using the IUE, together with a ground-based coude-feed telescope at KPNO. The ground-based spectra show an asymmetry related to the orbital phase in the H-alpha profile. H-beta profiles showed excess emission in one hemisphere and excess absorption in the other, with a broad Gaussian emission component superposed on the excess H-alpha line. A radial velocity curve was derived to estimate the mass ratio and geometry of the system. It is shown that the component of RT Lac fills 80-90 percent of the equilibrium Roche surface. Low-resolution ultraviolet data show that the supposed cooler component is bluer than its companion, suggesting evidence of a scattering shell or a cloud produced by the splash of a gas stream. The phase behavior of the low resolution ultraviolet data support the conclusion that RT Lac is a mass transfer system and that mass transfer is the primary cause of its activity.

Huenemoerder, D. P.↗
NASA NTRS1986

Correcting observed stellar Lyman alpha profiles for the effects of interstellar absorption and geocoronal emission

Techniques to compensate for interstellar absorption and geocoronal emission in IUE studies of late stars atmospheres were developed. Thus it is possible to determine the Lyman alpha flux from nearby cool stars using the low-resolution spectra in the IUE archives. The accuracy of such a procedure depends fundamentally upon the assumptions regarding the shape of the intrinsic profile and the density and velocity structure of the local interstellar medium, not upon measurement uncertainties of the low-resolution spectra. Geocoronal emission and saturated spectra are fatal only to a one-dimensional spectral analysis. When both the spatial and the spectral dimensions are considered, the observed Lyman alpha flux can be recovered.

Neff, J. E.↗
NASA NTRS2004

First Solar System Results of the Spitzer Space Telescope

The Spitzer Space Telescope, formerly known as SIRTF, is now operational and delivers unprecedented sensitivity for the observation of Solar System targets. Spitzer's capabilities and first general results were presented at the January 2004 AAS meeting. In this poster, we focus on Spitzer's performance for moving targets, and the first Solar System results. Spitzer has three instruments, IRAC, IRS, and MIPS. IRAC (InfraRed Array Camera) provides simultaneous images at wavelengths of 3.6, 4.5, 5.8, and 8.0 microns. IRS (InfraRed Spectrograph) has 4 modules providing low-resolution (R=60-120) spectra from 5.3 to 40 microns, high-resolution (R=600) spectra from 10 to 37 m, and an autonomous target acquisition system (PeakUp) which includes small-field imaging at 15 m. MIPS (Multiband Imaging Photometer for SIRTF) does imaging photometry at 24, 70, and 160 m and low-resolution (R=15-25) spectroscopy (SED) between 55 and 96 microns. Guaranteed Time Observer (GTO) programs include the moons of the outer Solar System, Pluto, Centaurs, Kuiper Belt Objects, and comets

VanCleve, J.↗
DOE OSTI2020

A new spatially distributed added value index for regional climate models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles

The added value of using regional climate models (RCMs) to downscale data from general circulation models (GCMs) has often been questioned and researched. Although several studies have used different methods to identify (and in some cases quantify) the added value, there is still a need to find a general metric that quantifies the added value of any variable. This paper builds on past studies to propose a new metric of added value in the simulation of present-day climate which measures the difference in the probability density functions (PDFs) at each grid-cell between a model and an observation source, and then compares the results of the RCM and GCM in order to spatially compute the added value index. The same method is also adapted to quantify the climate change downscaling signal in a way that is consistent with the present-day metric. These new metrics are tested on the daily precipitation output from the EURO-CORDEX and CORDEX-CORE projection ensembles and reveal an overall positive added value of RCMs, especially at the tail-end of the distribution. Higher added value is obtained in areas of complex topography and coast-lines, as well as in tropical regions. Areas with large added value in present-day climate are consistent with areas of significant climate change downscaling signal in the RCP 8.5 far future simulations, and when the analysis is repeated at a low-resolution. The use of different resolution observations shows that the added value tends to decrease when models are compared to low-resolution observation datasets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Titan - 1.5 micron photometry and spectrophotometry and a search for variability

The first photometric measurements of Titan in the mid-IR free of possible contamination from long-wavelength filter leaks are reported. A low-resolution spectrum covering the last unobserved gap in Titan's near-IR spectrum from 3.1 to 5.1 micron is shown. A series of photometric measurements is reported that may lay the foundation for long-term searches for variations in the albedos. Low-resolution spectra of Ganymede, Callisto, and Europa are also reported along with marginal detections of Neptune at 4.8 micron and two 4.8 micron observations of Uranus.

Noll, Keith S.↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
DOE OSTI2021

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: a catalogue of strong galaxy–galaxy lens candidates

ABSTRACT We spectroscopically detected 838 likely, 448 probable, and 265 possible strong lens candidates within ≈2 million galaxy spectra contained within the extended Baryon Oscillation Spectroscopic Survey (eBOSS) from the sixteenth data release (DR16) of the Sloan Digital Sky Survey (SDSS). We apply the spectroscopic detection method of the Baryon Oscillation Spectroscopic Survey (BOSS) Emission-Line Lens Survey (BELLS) and add Gaussian fit information, grading, additional inspection observables, and additional inspection methods to improve our selection method. We observed 477 candidates with lensing evidence within low-resolution images from both the Legacy survey of SDSS-I/II and the DESI Legacy survey, which is $12{{\ \rm per\ cent}}$ higher than the percentage of BELLS candidates observed with similar lensing evidence. Our search within the latest and improved reductions of the BOSS survey yielded a $20{{\ \rm per\ cent}}$ increase in the number of lens candidates expected from searching all BOSS and eBOSS galaxies. The distribution of target and background redshifts of our candidates is similar to the candidates and confirmed lenses within the BELLS observations. We present our Spectroscopic Identification of Lensing Object candidates in a value-added catalogue in SDSS DR16. The examination of these lens candidates in follow-up high-resolution imaging may yield more than twice the lenses found in previous spectroscopic detection surveys within SDSS, which would extend the results of previous lens surveys within SDSS to higher redshifts, constrain models of mass structures in spiral galaxies, and test if including the identification of possible lensing features within low-resolution images has merit to spectroscopic detection programmes.

Talbot, Michael S.↗
DOE OSTI2026

ZTF-SEDm Type Ia supernova sample for Twins Embedding spectrophotometric standardization

Aims. This paper has two aims: the first aim is to build a large homogeneous spectrophotometric sample of Type Ia supernovae (SNe Ia) from the second data release of the Zwicky Transient Facility (ZTF DR2). We used the spectrum sample from the low-resolution ( R ∼ 100) SEDmachine (SEDm) Integral Field Spectrograph (IFS) that gathered 3069 spectra. This is one of the largest samples of such collections that can attempt to reproduce the Twins Embedding (TE) spectrophotometric standardization method. This is our second objective. The method was developed based on high-quality spectra from 200 SNe Ia of the Nearby Supernova factory (SNfactory) and led to an exceptionally low value of 0.073 mag for the intrinsic scatter. Methods. As the SEDm is not designed as a spectrophotometric instrument, we first improved the flux-calibration accuracy of the SN Ia spectrum sample using the ZTF photometric data, which were calibrated at the percent level. We corrected the spectra for second-order polynomials, fitted by comparing the synthetic photometry in the ZTF g , r , i filters with the light-curve (LC) data. We then applied the three steps of the TE parameterization to a subset of 783 ZTF SN spectra near maximum light while comparing results from SNfactory and ZTF. We finally analyzed the standardization methods based on the TE parameters. Results. The precision of the phase-correction model, which is the first step of the TE, is estimated at 0.01 mag in g band based on ZTF data. Despite the challenge posed by the spectrum-extraction pipeline associated with the SEDm (flux calibration, leftover host signal, low signal-to-noise ratio, and low resolution), we applied a first standardization in color based on the second step of the TE, called read between the lines (RBTL), to the ZTF sample. We reached a Hubble residual scatter of 0.153 mag, all in normalized median absolute deviation, which is to be compared to the ∼0.11 mag obtained with the SNfactory data. The SALT color and stretch standardization reaches a scatter of 0.164 mag for the same ZTF SN Ia sample, and its host steps are ∼0.1 mag and zero for RBTL. When considering the scatter due to the redshift error and flux calibration error, we estimated a RBTL scatter of ∼0.129 mag for this ZTF sample as an upper limit because we identified an additional contribution from a systematic error in color. We tested the standardization based on the nonlinear TE parameters, and, as expected from the low spectrum quality, it did not improve the overall dispersion. Conclusions. We release 1897 flux calibrated spectra of 1607 SNe Ia with an estimated photometric accuracy of 0.07 mag. We further demonstrate that some amount of spectrophotometric SN Ia standardization can be done with limited-quality spectra. The RBTL standardization is more efficient than that of SALT with one parameter less, and the resulting host steps are consistent with zero. This makes it less prone to astrophysical bias. For future spectroscopic surveys, targeting the extraction pipeline for a thorough flux calibration and good signal-to-noise ratio would enable us to compute the full TE standardization, which would further reduce the scatter in the distance estimate.

Ganot, C↗
DOE OSTI2024

Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model

Some ocean modeling studies have identified a potential tipping point from a low to a high basal melt regime beneath the Filchner–Ronne Ice Shelf (FRIS), Antarctica, with significant implications for subsequent Antarctic ice sheet mass loss. To date, investigation of the climate drivers and impacts of this possible event have been limited because ice-shelf cavities and ice-shelf melting are only now starting to be included in global climate models. Using a global ocean–sea-ice configuration of the Energy Exascale Earth System Model (E3SM) that represents both ocean circulations and melting within ice-shelf cavities, we explore freshwater triggers (iceberg melt and ice-shelf basal melt) of a transition to a high-melt regime at FRIS in a low-resolution (30 km in the Southern Ocean) global ocean–sea-ice model. We find that a realistic spatial distribution of iceberg melt fluxes is necessary to prevent the FRIS melt regime change from unrealistically occurring under historical-reanalysis-based atmospheric forcing. Further, improvement of the default parameterization for mesoscale eddy mixing significantly reduces a large regional fresh bias and weak Antarctic Slope Front structure, both of which precondition the model to melt regime change. Using two different stable model con figurations, we explore the sensitivity of FRIS melt regime change to regional ice-sheet freshwater fluxes. Through a series of sensitivity experiments prescribing incrementally increasing melt rates from the smaller, neighboring ice shelves in the eastern Weddell Sea, we demonstrate the potential for an ice-shelf melt “domino effect” should the upstream ice shelves experience increased melt rates. The experiments also reveal that modest ice-shelf melt biases in a model, especially at coarse ocean resolution where narrow continental shelf dynamics are not well resolved, can lead to an unrealistic melt regime change at downstream ice shelves. Thus, we find that remote connections between melt fluxes at different ice shelves are sensitive to baseline model conditions. Our results highlight both the potential and the peril of simulating prognostic Antarctic ice-shelf melt rates in a low-resolution global model.

58 GEOSCIENCES↗
DOE OSTI2024

Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model

Abstract. Some ocean modeling studies have identified a potential tipping point from a low to a high basal melt regime beneath the Filchner–Ronne Ice Shelf (FRIS), Antarctica, with significant implications for subsequent Antarctic ice sheet mass loss. To date, investigation of the climate drivers and impacts of this possible event have been limited because ice-shelf cavities and ice-shelf melting are only now starting to be included in global climate models. Using a global ocean–sea-ice configuration of the Energy Exascale Earth System Model (E3SM) that represents both ocean circulations and melting within ice-shelf cavities, we explore freshwater triggers (iceberg melt and ice-shelf basal melt) of a transition to a high-melt regime at FRIS in a low-resolution (30 km in the Southern Ocean) global ocean–sea-ice model. We find that a realistic spatial distribution of iceberg melt fluxes is necessary to prevent the FRIS melt regime change from unrealistically occurring under historical-reanalysis-based atmospheric forcing. Further, improvement of the default parameterization for mesoscale eddy mixing significantly reduces a large regional fresh bias and weak Antarctic Slope Front structure, both of which precondition the model to melt regime change. Using two different stable model configurations, we explore the sensitivity of FRIS melt regime change to regional ice-sheet freshwater fluxes. Through a series of sensitivity experiments prescribing incrementally increasing melt rates from the smaller, neighboring ice shelves in the eastern Weddell Sea, we demonstrate the potential for an ice-shelf melt “domino effect” should the upstream ice shelves experience increased melt rates. The experiments also reveal that modest ice-shelf melt biases in a model, especially at coarse ocean resolution where narrow continental shelf dynamics are not well resolved, can lead to an unrealistic melt regime change at downstream ice shelves. Thus, we find that remote connections between melt fluxes at different ice shelves are sensitive to baseline model conditions. Our results highlight both the potential and the peril of simulating prognostic Antarctic ice-shelf melt rates in a low-resolution global model.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

The NSO FTS database program and archive (FTSDBM)

Data from the NSO Fourier transform spectrometer is being re-archived from half inch tape onto write-once compact disk. In the process, information about each spectrum and a low resolution copy of each spectrum is being saved into an on-line database. FTSDBM is a simple database management program in the NSO external package for IRAF. A command language allows the FTSDBM user to add entries to the database, delete entries, select subsets from the database based on keyword values including ranges of values, create new database files based on these subsets, make keyword lists, examine low resolution spectra graphically, and make disk number/file number lists. Once the archive is complete, FTSDBM will allow the database to be efficiently searched for data of interest to the user and the compact disk format will allow random access to that data.

Lytle, D. M.↗
DOE OSTI2020

Super resolution for root imaging

Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

Ruiz‐Munoz, Jose F.↗
NASA NTRS2017

Low-Mass Planar Photonic Imaging Sensor

Continuing on the successful progress of NIAC (NASA Innovative Advanced Concepts) Phase I, this report summarizes the technical progress achieved under NIAC Phase II during the performance period September 19, 2014 to June 18, 2017. During this period, the research team has made the following accomplishments: designed and layout a silica photonic integrated circuit (PIC) as a two baselineinterferometric imager; constructed an experiment to utilize the two baselines for complex visibility measurementon a point source and a variable width slit; analyzed and studied the testbed results (in collaboration with Lockheed Martin); designed and layout Si3N4 PICs for the low-resolution and high-resolution SPIDER (Segmented Planar Imaging Detector for Electro-Optical Reconnaissance) telescope; fabricated the multi-layer Si3N4 PIC for low and high resolution SPIDER telescope; characterized the optical throughput and heater response for Si3N4 PIC for low and highresolution SPIDER telescopes; carried out imaging experiments using the Si3N4 PIC low-resolution version (in collaboration with Lockheed Martin); investigated signal-to-noise (SNR) ratio of SPIDER imager compared to the conventional panchromatic imager (in collaboration with Lockheed Martin); fulfilled the SNR simulation upon SPIDER imager (in collaboration with Lockheed Martin).

Yoo, S. J. Ben↗
NASA NTRS1994

A class of the van Leer-type transport schemes and its application to the moisture transport in a general circulation model

A generalized form of the second-order van Leer transport scheme is derived. Several constraints to the implied subgrid linear distribution are discussed. A very simple positive-definite scheme can be derived directly from the generalized form. A monotonic version of the scheme is applied to the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) for the moisture transport calculations, replacing the original fourth-order center-differencing scheme. Comparisons with the original scheme are made in idealized tests as well as in a summer climate simulation using the full GLA GCM. A distinct advantage of the monotonic transport scheme is its ability to transport sharp gradients without producing spurious oscillations and unphysical negative mixing ratio. Within the context of low-resolution climate simulations, the aforementioned characteristics are demonstrated to be very beneficial in regions where cumulus convection is active. The model-produced precipitation pattern using the new transport scheme is more coherently organized both in time and in space, and correlates better with observations. The side effect of the filling algorithm used in conjunction with the original scheme is also discussed, in the context of idealized tests. The major weakness of the proposed transport scheme with a local monotonic constraint is its substantial implicit diffusion at low resolution. Alternative constraints are discussed to counter this problem.

Lin, Shian-Jiann↗
NASA NTRS1996

Spectral Irradiance Calibration in the Infrared: New Composite Spectra, Comparison with Model Atmospheres, and Far-Infrared Extrapolations - Part 7

We present five new absolutely calibrated continuous stellar spectra constructed as far as possible from spectral fragments observed from the ground, the Kuiper Airborne Observatory (KAO), and the IRAS Low Resolution Spectrometer. These stars-alpha Boo, gamma Dra, alpha Cet, gamma Cru, and mu UMa-augment our six, published, absolutely calibrated spectra of K and early-M giants. All spectra have a common calibration pedigree. A revised composite for alpha Boo has been constructed from higher quality spectral fragments than our previously published one. The spectrum of gamma Dra was created in direct response to the needs of instruments aboard the Infrared Space Observatory (ISO); this star's location near the north ecliptic pole renders it highly visible throughout the mission. We compare all our low-resolution composite spectra with Kurucz model atmospheres and find good agreement in shape, with the obvious exception of the SiO fundamental, still lacking in current grids of model atmospheres. The CO fundamental seems slightly too deep in these models, but this could reflect our use of generic models with solar metal abundances rather than models specific to the metallicities of the individual stars. Angular diameters derived from these spectra and models are in excellent agreement with the best observed diameters. The ratio of our adopted Sirius and Vega models is vindicated by spectral observations. We compare IRAS fluxes predicted from our cool stellar spectra with those observed and conclude that, at 12 and 25 microns, flux densities measured by IRAS should be revised downwards by about 4.1% and 5.7%, respectively, for consistency with our absolute calibration. We have provided extrapolated continuum versions of these spectra to 300 microns, in direct support of ISO (PHT and LWS instruments). These spectra are consistent with IRAS flux densities at 60 and 100 microns.

Cohen, Martin↗
NASA NTRS1977

Probable distribution of large impact basins on Venus - Comparison with Mercury and the moon

The reported study is based on the 12.5 cm wavelength data of Rumsey et al. (1974). The considered low resolution (80 km) radar image covers an area equivalent to 19% of the surface of Venus. The study had the objective to map potential large impact structures and relate their size frequency distribution to those of Mercury and the moon. The Venus radar map was analyzed using a color television film density slicer system for enhancement of subtle changes and gross patterns of contrasting radar reflectivity. Analysis by this technique permitted the recognition of 12 possible basins with diameters exceeding 600 km on about 8% of the total surface area of the planet. The preliminary basin size frequency distribution determined for Venus from these low resolution data suggests that the cloud-covered planet could be more cratered per unit area by basins than either the moon or Mercury.

Schaber, G. G.↗
NASA NTRS2017

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

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗