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For remote sensing of ocean surface wind, Ku-band scatterometer technology has been demonstrated and will be used to monitor global ocean wind fields from spaceborne sensors such as the NASA Scatterometer (NSCAT). Algorithms for wind velocity retrieval from scatterometer data utilize absolute radar returns and relative azimuth modulations of backscatter. The NUSCAT-SWADE data base is used.
Space program goals that NASA can best achieve by the construction of a space station in keeping with the 1958 directive to maintain U.S. pre-eminence in space technology are discussed. Science goals that can be satisfied by a suitable equipped space station include a deeper understanding of the earth/sun system and the earth as a planet, the acquisition of new data on the evolution of the solar system, of life, and of the universe, and the extended study of the laws governing the state of matter and energy. Application goals that can be pursued with a space station include assaying all renewable and nonrenewable earth resources, predicting environment, weather, and climatic changes, studying ocean dynamics, using space to develop new processes and materials, and using space for information transmission on a global basis. The space station can serve as a waypoint for voyages by manned or unmanned spacecraft, as a laboratory, observation platform, and technology proving station, and as a base for deployment and repair of other spacecraft.
We have developed an instrument concept that combines a conventional nadir altimeter with a radar interferometer to meet the above requirements. In this paper, we describe the overall mission concept and the interferometric radar design. We also describe several new technology developments that facilitate the inclusion of this instrument on a small, inexpensive spacecraft bus. Those include ultra-light, deployable reflectarray antennas for the radar interferometer; a novel five frequency feed horn for the radiometer and altimeter; a lightweight, low power integrated three frequency radiometer; and a field programmable gate array-based onboard data processor. Finally, we discuss recent algorithm developments for the onboard date processing, and present the expected instatements performance improvements over previously reported results.
Cyanobacterial harmful algal blooms (cyanoHAB) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and sh kills, and taste and odor problems. CyanoHABs are a particular concern in both recreational waters and drinking water sources because of their dense biomass and the risk of exposure to toxins. Successful cyanoHAB assessment using satellites may provide an indicator for human and ecological health protection. In this study, methods were developed to assess the utility of satellite technology for detecting cyanoHAB frequency of occurrence at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent series of Sentinel-3 Ocean and Land Colour Imagers (OLCI) launched in 2016 as part of the Copernicus program. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, the continental United States contains 275,897 lakes and reservoirs greater than 1 ha in area. Results from this study show that 5.6% of waterbodies were resolvable by satellites with 300 m single-pixel resolution and 0.7% of waterbodies were resolvable when a three by three pixel (3 x 3-pixel) array was applied based on minimum Euclidian distance from shore. Satellite data were spatially joined to U.S. public water surface intake (PWSI) locations, where single-pixel resolution resolved 57% of the PWSI locations and a 3 x 3-pixel array resolved 33% of the PWSI locations. Recreational and drinking water sources in Florida and Ohio were ranked from 2008 through 2011 by cyanoHAB frequency above the World Health Organizations (WHO) high threshold for risk of 100,000 cells m/L. The ranking identified waterbodies with values above the WHO high threshold, where Lake Apopka, FL (99.1%) and Grand Lake St. Marys, OH (83%) had the highest observed bloom frequencies per region. The method presented here may indicate locations with high exposure to cyanoHABs and therefore can be used to assist in prioritizing management resources and actions for recreational and drinking water sources.
NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This presentation will discuss the instrumentation selected for LOFTID to capture the HIAD performance during the high-energy orbital reentry flight test, provide examples of data products, and snippets of the spectacular reentry video.
NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This paper will discuss the instrumentation selected for LOFTID, a summary of sensor in-flight performance, and will provide examples of data products from the post-flight analysis effort.
NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This paper will discuss the instrumentation selected for LOFTID, a summary of sensor in-flight performance, and will provide examples of data products from the post-flight analysis effort.
The Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) is a NASA/NRL mission studying clouds and aerosols with the NASA P-3B aircraft, a Learet and an ocean research vessel. The mission is based in the Philippines from late August through early October 2019. This presentation is aimed at 8-12th grade students in the Philippines for education/outreach purposes to expose students to NASA Earth and Airborne Science research, the CAMP2Ex mission, and careers in science, technology, engineering and math (STEM).The presentation starts with an overview of NASA Earth science, including discussing how and why NASA studies the earth using satellites, airplanes, and sensors on the ground. We discuss the NASA Airborne Science Program and how NASA uses airplanes to study the Earth from the equator to the poles. We discuss the CAMP2Ex mission specifically, including mission science goals and why we are based in the Philippines. We will discuss basic cloud physics and remote sensing using demonstrations and activities. Finally, we discuss careers in STEM and at NASA, giving personal examples of the career paths of scientists, engineers and pilots on the CAMP2Ex mission.
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%.
An assessment of Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) sea ice concentrations under winter conditions using ice concentrations derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery obtained during the March 2003 Arctic sea ice validation field campaign is presented. The National Oceanic and Atmospheric Administration Environmental Technology Laboratory's Airborne Polarimetric Scanning Radiometer Measurements, which were made from the National Aeronautics and Space Administration P 3B aircraft during the campaign, were used primarily as a diagnostic tool to understand the comparative results and to suggest improvements to the AMSR-E ice concentration algorithm. Based on the AMSR-E/ETM+ comparisons, a good overall agreement with little bias (approx. 1%) for areas of first year and young sea ice was found. Areas of new ice production result in a negative bias of about 5% in the AMSR-E ice concentration retrievals, with a root mean square error of 8%. Some areas of deep snow also resulted in an underestimate of the ice concentration (approx. 10%). For all ice types combined and for the full range of ice concentrations, the bias ranged from 0% to 3%, and the rms errors ranged from 1% to 7%, depending on the region. The new-ice and deep-snow biases are expected to be reduced through an adjustment of the new-ice and ice-type C algorithm tie points.
Water vapor is one of the most important atmospheric trace gas species and influences radiation, climate, cloud formation, surface evaporation, precipitation, storm development, transport, dynamics, and chemistry. For improvements in NWP (numerical weather prediction) and climate studies, global water vapor measurements with higher accuracy and vertical resolution are needed than are currently available. Current satellite sensors are challenged to characterize the content and distribution of water vapor in the Boundary Layer (BL) and particularly near the first few hundred meters above the surface within the BL. These measurements are critically needed to infer surface evaporation rates in cloud formation and climate studies. The NASA Langley Research Center Lidar Atmospheric Sensing Experiment (LASE) system, which uses the Differential Absorption Lidar (DIAL) technique, has demonstrated the capability to provide high quality water vapor measurements in the BL and across the troposphere. A new retrieval technique is investigated to extend these DIAL water vapor measurements to the surface. This method uses signals from both atmospheric backscattering and the strong surface returns (even over low reflectivity oceanic surfaces) using multiple gain channels to cover the large signal dynamic range. Measurements can be made between broken clouds and in presence of optically thin cirrus. Examples of LASE measurements from a variety of conditions encountered during NASA hurricane field experiments over the Atlantic Ocean are presented. Comparisons of retrieved water vapor profiles from LASE near the surface with dropsonde measurements show very good agreement. This presentation also includes a discussion of the feasibility of developing space-based DIAL capability for high resolution water vapor measurements in the BL and above and an assessment of the technology needed for developing this capability.
Measurements of tropospheric CO2 abundance with global-coverage, a few hundred km spatial and monthly temporal resolution are needed to quantify processes that regulate CO2 storage by the land and oceans. The Orbiting Carbon Observatory (OCO) is the first space mission focused on atmospheric CO2 for measuring total column CO, and O2 by detecting the spectral absorption in reflected sunlight. The OCO mission is an essential step, and will yield important new information about atmospheric CO2 distributions. However there are unavoidable limitations imposed by its measurement approach. These include best accuracy only during daytime at moderate to high sun angles, interference by cloud and aerosol scattering, and limited signal from CO2 variability in the lower tropospheric CO2 column. We have been developing a new laser-based technique for the remote measurement of the tropospheric CO2 concentrations from orbit. Our initial goal is to demonstrate a lidar technique and instrument technology that will permit measurements of the CO2 column abundance in the lower troposphere from aircraft. Our final goal is to develop a space instrument and mission approach for active measurements of the CO2 mixing ratio at the 1-2 ppmv level. Our technique is much less sensitive to cloud and atmospheric scattering conditions and would allow continuous measurements of CO2 mixing ratio in the lower troposphere from orbit over land and ocean surfaces during day and night. Our approach is to use the 1570nm CO2 band and a 3-channel laser absorption spectrometer (i.e. lidar used an altimeter mode), which continuously measures at nadir from a near polar circular orbit. The approach directs the narrow co-aligned laser beams from the instrument's lasers toward nadir, and measures the energy of the laser echoes reflected from land and water surfaces. It uses several tunable fiber laser transmitters which allowing measurement of the extinction from a single selected CO2 absorption line in the 1570 nm band. This band is free from interference from other gases and has temperature insensitive absorption lines. During the measurement the lasers are tuned on- and off- a selected CO2 line near 1572 nm and a selected O2 line near 768 nm in the Oxygen A band at kHz rates. The lasers use tunable diode seed lasers followed by fiber amplifiers, and have spectral widths much narrower than the gas absorption lines. The receiver uses a 1-m diameter telescope and photon counting detectors and measures the background light and energies of the laser echoes from the surface. The extinction and column densities for the CO2 and O2 gases are estimated from the ratio of the on and offline surface echo via the differential optical absorption technique. Our technique rapidly alternates between several on-line wavelengths set to the sides of the selected gas absorption lines. It exploits the atmospheric pressure broadening of the lines to weight the measurement sensitivity to the atmospheric column below 5 km. This maximizes sensitivity to CO2 in the boundary layer, where variations caused by surface sources and sinks are largest. Simultaneous measurements of O2 column will use an identical approach with an O2 line. Thee laser frequencies are tunable and have narrow (MHz) line widths. In combination with sensitive photon counting detectors these enables much higher spectral resolution and precision than is possible with passive spectrometer. 1aser backscatter profiles are also measured, which permits identifying measurements made to cloud tops and through aerosol layers. The measurement approach using lasers in common-nadir-zenith path allows retrieving CO2 column mixing ratios in the lower troposphere irrespective of sun angle. Pulsed laser signals, time gated receiver and a narrow receiver field-of-view are used to isolate the surface laser echo signals and to exclude photons scattered from clouds and aerosols. Nonetheless, the optical absorption change due to a change of a few ppO2 is small, <1 % which makes achieving the needed measurement sensitivities and stabilities quite challenging. Measurement SNRs and stabilities of >600:1 are needed to estimate CO2 mixing ratio at the 1-2 ppm level. We have calculated characteristics of the technique and have demonstrated aspects of the laser, detector and receiver approaches in th e laboratory We have also measured O2 in an absorption cell, and made C02 measurements over a 400 m long (one way) horizontal path using a sensor breadboard. We will describe these and more details of our approach in the paper.
There are many vital issues which are impacting our daily lives and will continue to haunt us as long as we live on this planet of ours. These issues range from food supply availability, drought, coastal zone erosion, volcanoes, hurricanes, terrorism, global warming, earthquakes, water resources, air quality, public health, and agriculture production. Such societal needs are directly linked to our geometric population growth, and abundance of automobiles, industrial emissions, industrial waste and extensive fishing of our oceans and elimination of our ecology. The questions which require serious thoughts, research, coordination, and resources to understand, plan and strike a sensible balance in our daily lives and the above issues are tough to deal with. However, with the advent of remote sensing technologies, tremendous progress has been made in applying space-based and airborne data and products in solving real societal problems. Several of these problems, such as coastal zone erosion, air quality, severe weather, water availability and quality, public health, fires, land slides and others are intricately related; and in the long run can have serious consequences if not properly addressed by scientists, regulatory bodies and policy makers. Although it is a much involved and tangled web to unravel, nevertheless we have an excellent start in understanding some of the phenomena and hopefully can mitigate some of the severe effects by advancing our scientific knowledge. This paper briefly discusses the applications of remote sensing data from Terra, Aqua, and other NASA satellites how to deal with such complex problems; it provides an excellent start.
This presentation discusses use of 4 kilometer satellite-based sea surface temperature (SST) data to monitor and assess coral reef areas of the Florida Keys. There are growing concerns about the impacts of climate change on coral reef systems throughout the world. Satellite remote sensing technology is being used for monitoring coral reef areas with the goal of understanding the climatic and oceanic changes that can lead to coral bleaching events. Elevated SST is a well-documented cause of coral bleaching events. Some coral monitoring studies have used 50 km data from the Advanced Very High Resolution Radiometer (AVHRR) to study the relationships of sea surface temperature anomalies to bleaching events. In partnership with NOAA's Office of National Marine Sanctuaries and the University of South Florida's Institute for Marine Remote Sensing, this project utilized higher resolution SST data from the Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR. SST data for 2000-2010 was employed to compute sea surface temperature anomalies within the study area. The 4 km SST anomaly products enabled visualization of SST levels for known coral bleaching events from 2000-2010.
This presentation introduces and discusses the development of the CubeSub submersible concept, an Autonomous Underwater Vehicle (AUV) designed around the CubeSat satellite form factor. The presented work is part of the author's MSc thesis in Aerospace Engineering at the Royal Institute of Technology, Stockholm, Sweden, and was performed during an internship at the Mission Design Division of the NASA Ames Research Center, Moffett Field, CA. Still in the early stages of its development, the CubeSub is to become a submersible test-bed for technology qualified for underwater and space environments. With the long-term goal of exploring the underwater environments in outer space, such as the alleged subsurface ocean of Jupiter's moon Europa, a number of technology and operational procedures must be developed and matured. To assist in this, the CubeSub platform is introduced as a tool to allow engineers and scientists to easily test qualified technology underwater. A CubeSat is a class of miniaturized satellite built to a standardized size. The base size is 1U (U for unit), corresponding to a 100 x 100 x 113.5 cu mm cube. A 1U CubeSat can in other words easily be held in one hand. Stacking units give larger satellite sizes such as the also commonly used 1.5U, 2U and 3U. The CubeSat standard is in itself already well established and hundreds of CubeSats have to date been launched into space. Compatible technology is readily available and the know-how exists in the space industry, all of which makes it a firm ground to stand on for the CubeSub. The rationale behind using the CubeSat form factor is to make use of this pre-existing foundation, making the CubeSub easy to develop, modular and readily available. It will thereby aid in the process of maturing the concept of a fully space qualified submersible headed for outer space. As a further clarification, the CubeSub is itself not meant for outer space, but to facilitate development of such a vessel. Along with its uses as a testbed, the CubeSub also holds the potential to become a useful tool for exploration and experimentation here on Earth. A highly standardized system utilizing well-known hardware can reduce the cost and required work load for researchers wishing to perform experiments and exploration. Users could design sensors and experiments to comply with the already well established CubeSat standard, which are then carried by the CubeSub to the region of interest. This in turn means that the end users can focus more on formulating the experiment itself and less about how to get it where they want it. The CubeSub is designed to be built up by modules, which can be assembled in different configurations to fulfill different needs. Each module will be powered individually and intermodular communication will be wireless, removing the need for wiring. The inside of the cylindrical hull will be flooded with ambient water to enhance the interaction between payloads and surrounding environment. The overall torpedo-like shape is similar to that of a conventional AUV, slender and smooth. This is to make for a low drag, reduce the risk of snagging on surrounding objects and make it possible to deploy through an ice sheet via a narrow borehole or navigate in tight areas. To keep costs low and further accelerate development, rapid prototyping is utilized wherever possible. Full-scale prototypes are being constructed through 3D-printing and using COTS (Commercial Off-The-Shelf) components. 3D-printing is used both for the largest hull components and the relatively small and delicate propellers. Arduino boards are used for control and internal communication
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.
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.
A solar power generation station on a mountaintop near the moon's North or South pole can receive sunlight 708 hours per lunar day, for continuous power generation. Power can be beamed from this station over long distances using a laser-based wireless power transmission system and a photo-voltaic receiver. This beamed energy can provide warmth, electricity, and illumination for a robotic rover to perform scientific experiments in cold, dark craters where no other power source is practical. Radio-frequency power transmission may also be demonstrated in lunar polar applications to locate and recover sub-surface deposits of volatile material, such as water ice. High circular polarization ratios observed in data from Clementine spacecraft and Arecibo radar reflections from the moon's South pole suggest that water ice is indeed present in certain lunar polar craters. Data from the Lunar Prospector spacecraft's epi-thermal neutron spectrometer also indicate that hydrogen is present at the moon's poles. Space Solar Power technology enables investigation of these craters, which may contain a billion-year-old stratigraphic record of tremendous scientific value. Layers of ice, preserved at the moon's poles, could help us determine the sequence and composition of comet impacts on the moon. Such ice deposits may even include distinct strata deposited by secondary ejecta following significant Earth (ocean) impacts, linked to major extinctions of life on Earth. Ice resources at the moon's poles could provide water and air for human exploration and development of space as well as rocket propellant for future space transportation. Technologies demonstrated and matured via lunar polar applications can also be used in other NASA science missions (Valles Marineris. Phobos, Deimos, Mercury's poles, asteroids, etc.) and in future large-scale SSP systems to beam energy from space to Earth. Ground-based technology demonstrations are proceeding to mature the technology for such a near-term scientific mission to the moon. This paper reviews the progress to date in demonstrating this technology on Earth and details the plans for near-term applications, to meet NASA's needs, in the moon's polar regions.