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The Mars Reconnaissance Orbiter will deliver to Mars orbit a payload to conduct remote sensing science observations, characterize sites for future landers, and provide critical telecom/navigation relay capability for follow-on missions.
Typically, data collected by a spacecraft is downlinked to Earth and pre-processed before any analysis is performed. We have developed classifiers that can be used onboard a spacecraft to identify high priority data for downlink to Earth, providing a method for maximizing the use of a potentially bandwidth limited downlink channel. Onboard analysis can also enable rapid reaction to dynamic events, such as flooding, volcanic eruptions or sea ice break-up. Four classifiers were developed to identify cryosphere events using hyperspectral images. These classifiers include a manually constructed classifier, a Support Vector Machine (SVM), a Decision Tree and a classifier derived by searching over combinations of thresholded band ratios. Each of the classifiers was designed to run in the computationally constrained operating environment of the spacecraft. A set of scenes was hand-labeled to provide training and testing data. Performance results on the test data indicate that the SVM and manual classifiers outperformed the Decision Tree and band-ratio classifiers with the SVM yielding slightly better classifications than the manual classifier.
Cassini and Huygens have made exciting discoveries at Titan and Enceladus, and at the same time made us aware of how little we understand about these bodies. For example, the source, and/or recycling mechanism, of methane in Titan's atmosphere is still puzzling. Indeed, river beds (mostly dry) and lakes have been spotted, and occasional clouds have been seen, but the physics to explain the observations is still mostly lacking, since our "image" of Titan is still sketchy and quite incomplete. Enceladus, only -500 km in extent, is even more puzzling, with its fiery plumes of vapor, dust and ice emanating from its south polar region, "feeding" Saturn's E ring. Long term variability of magnetospheric plasma, neutral gas, E-ring ice grain density, radio emissions, and corotation of Saturn's planetary magnetic field in response to Enceladus plume activity are of great interest for Saturn system science. Both Titan and Enceladus are bodies of considerable astrobiological interest in view of high organic abundances at Titan and potential subsurface liquid water at Enceladus. We propose to develop a new mission to Titan and Enceladus, the Titan Orbiter Aerorover Mission with Enceladus Science (TOAMES), to address these questions using novel new technologies. TOAMES is a multi-faceted mission that starts with orbit insertion around Saturn using aerobraking with Titan's extended atmosphere. We then have an orbital tour around Saturn (for 1-2 years) and close encounters with Enceladus, before it goes into orbit around Titan (via aerocapture). During the early reconnaissance phase around Titan, perhaps 6 months long, the orbiter will use altimetry, radio science and remote sensing instruments to measure Titan's global topography, subsurface structure and atmospheric winds. This information will be used to determine where and when to release the Aerorover, so that it can navigate safely around Titan and identify prime sites for surface sampling and analysis. In situ instruments will sample the upper atmosphere which may provide the seed population for the complex organic chemistry on the surface. The Aerorover will probably use a "hot air" Montgolfier balloon concept using the waste heat from the MMRTG 1-2 kwatts. New technologies will need to be developed and miniaturization will be required to maintain functionality while controlling mass, power and cost. Duty cycling will be used. The Aerorover will have all the instruments needed to sample Titan's atmosphere and surface with possible methane lakes-rivers. It will e.g., use multi-spectral imagers and for last 6 months of mission, balloon payload will land on surface at predetermined site to take core samples of the surface and use seismometers to help probe the interior. All remote (and active) sensors on the orbiter will share a - 1 meter telescope, called MIDAS (Multiple Instrument Distributed Aperture Sensor). MIDAS observations in stable orbit at Titan can provide full global maps of Titan's surface and could additionally provide long term observations of the Saturn system including Enceladus for extended mission phases over many years, potentially for decades. Experience from the Hubble Space Telescope has shown strong public interest and commitment to exciting generational missions.
A major challenge for remote sensing science researchers is searching and acquiring relevant data files for their research projects based on content, space and time constraints. Several structured query (SQ) and hierarchical navigation (HN) search interfaces have been develop ed to satisfy this requirement, yet the dominant search engines in th e general domain are based on free-text search. The Goddard Earth Sci ences Data and Information Services Center has developed a free-text search interface named Mirador that supports space-time queries, inc luding a gazetteer and geophysical event gazetteer. In order to compe nsate for a slightly reduced search precision relative to SQ and HN t echniques, Mirador uses several search optimizations to return result s quickly. The quick response enables a more iterative search strateg y than is available with many SQ and HN techniques.
A submillimeter-wave monolithic integrated- circuit (S-MMIC) amplifier has been designed and fabricated using an indium phosphide (InP) 35-nm gate-length high electron mobility transistor (HEMT) device, developed at Northrop Grumman Corporation. The HEMT device employs two fingers each 15 micrometers wide. The HEMT wafers are grown by molecular beam epitaxy (MBE) and make use of a pseudomorphic In0.75Ga0.25As channel, a silicon delta-doping layer as the electron supply, an In0.52Al0.48As buffer layer, and an InP substrate. The three-stage design uses coplanar waveguide topology with a very narrow ground-to-ground spacing of 14 micrometers. Quarter-wave matching transmission lines, on-chip metal-insulator-metal shunt capacitors, series thin-film resistors, and matching stubs were used in the design. Series resistors in the shunt branch arm provide the basic circuit stabilization. The S-MMIC amplifier was measured for S-parameters and found to be centered at 320 GHz with 13-15-dB gain from 300-345 GHz. This chip was developed as part of the DARPA Submillimeter Wave Imaging Focal Plane Technology (SWIFT) program (see figure). Submillimeter-wave amplifiers could enable more sensitive receivers for earth science, planetary remote sensing, and astrophysics telescopes, particularly in radio astronomy, both from the ground and in space. A small atmospheric window at 340 GHz exists and could enable ground-based observations. However, the submillimeter-wave regime (above 300 GHz) is best used for space telescopes as Earth s atmosphere attenuates most of the signal through water and oxygen absorption. Future radio telescopes could make use of S-MMIC amplifiers for wideband, low noise, instantaneous frequency coverage, particularly in the case of heterodyne array receivers.
The cover image incorporates high resolution stereo pairs acquired from the DigitalGlobe(R) QuickBird sensor. It shows a digital elevation model of Meteor Crater, Arizona at approximately 1.3 meter point-spacing. Image analysts used the Leica Photogrammetry Suite to produce the DEM. The outside portion was computed from two QuickBird panchromatic scenes acquired October 2006, while an Optech laser scan dataset was used for the crater s interior elevations. The crater s terrain model and image drape were created in a NASA Constellation Program project focused on simulating lunar surface environments for prototyping and testing lunar surface mission analysis and planning tools. This work exemplifies NASA s Scientific Data Purchase legacy and commercial high resolution imagery applications, as scientists use commercial high resolution data to examine lunar analog Earth landscapes for advanced planning and trade studies for future lunar surface activities. Other applications include landscape dynamics related to volcanism, hydrologic events, climate change, and ice movement.
Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.
Topics include: Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector; Surface-Enhanced Raman Scattering Using Silica Whispering-Gallery Mode Resonators; 3D Hail Size Distribution Interpolation/Extrapolation Algorithm; Color-Changing Sensors for Detecting the Presence of Hypergolic Fuels; Artificial Intelligence Software for Assessing Postural Stability; Transformers: Shape-Changing Space Systems Built with Robotic Textiles; Fibrillar Adhesive for Climbing Robots; Using Pre-Melted Phase Change Material to Keep Payloads in Space Warm for Hours without Power; Development of a Centrifugal Technique for the Microbial Bioburden Analysis of Freon (CFC-11); Microwave Sinterator Freeform Additive Construction System (MS-FACS); DSP/FPGA Design for a High-Speed Programmable S-Band Space Transceiver; On-Chip Power-Combining for High-Power Schottky Diode-Based Frequency Multipliers; FPGA Vision Data Architecture; Memory Circuit Fault Simulator; Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination; Regolith Advanced Surface Systems Operations Robot Excavator; Magnetically Actuated Seal; Hybrid Electrostatic/Flextensional Mirror for Lightweight, Large-Aperture, and Cryogenic Space Telescopes; System for Contributing and Discovering Derived Mission and Science Data; Remote Viewer for Maritime Robotics Software; Stackfile Database; Reachability Maps for In Situ Operations; JPL Space Telecommunications Radio System Operating Environment; RFI-SIM: RFI Simulation Package; ION Configuration Editor; Dtest Testing Software; IMPaCT - Integration of Missions, Programs, and Core Technologies; Integrated Systems Health Management (ISHM) Toolkit; Wind-Driven Wireless Networked System of Mobile Sensors for Mars Exploration; In Situ Solid Particle Generator; Analysis of the Effects of Streamwise Lift Distribution on Sonic Boom Signature; Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments; Towed Subsurface Optical Communications Buoy; High-Collection-Efficiency Fluorescence Detection Cell; Ultra-Compact, Superconducting Spectrometer-on-a-Chip at Submillimeter Wavelengths; UV Resonant Raman Spectrometer with Multi-Line Laser Excitation; Medicine Delivery Device with Integrated Sterilization and Detection; Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME; Airborne Tomographic Swath Ice Sounding Processing System; flexplan: Mission Planning System for the Lunar Reconnaissance Orbiter; Estimating Torque Imparted on Spacecraft Using Telemetry; PowderSim: Lagrangian Discrete and Mesh-Free Continuum Simulation Code for Cohesive Soils; Multiple-Frame Detection of Subpixel Targets in Thermal Image Sequences; Metric Learning to Enhance Hyperspectral Image Segmentation; Basic Operational Robotics Instructional System; Sheet Membrane Spacesuit Water Membrane Evaporator; Advanced Materials and Manufacturing for Low-Cost, High-Performance Liquid Rocket Combustion Chambers; Motor Qualification for Long-Duration Mars Missions.
Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.
NASA's Earth Observing System Data and Information System (EOSDIS) has been in operation since August 1994, and serving a diverse user community around the world with Earth science data from satellites, aircraft, field campaigns and research investigations. The ESDIS Project, responsible for EOSDIS is a Network Member of the International Council for Sciences (ICSU) World Data System (WDS). Nine of the 12 Distributed Active Archive Centers (DAACs), which are part of EOSDIS, are Regular Members of the ICSUWDS. This poster presents the EOSDIS mission objectives, key characteristics of the DAACs that make them world class Earth science data centers, successes, challenges and best practices of EOSDIS focusing on the years 2014-2016, and illustrates some highlights of accomplishments of EOSDIS. The highlights include: high customer satisfaction, growing archive and distribution volumes, exponential growth in number of products distributed to users around the world, unified metadata model and common metadata repository, flexibility provided to uses by supporting data transformations to suit their applications, near-real-time capabilities to support various operational and research applications, and full resolution image browse capabilities to help users select data of interest. The poster also illustrates how the ESDIS Project is actively involved in several US and international data system organizations.
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Since launch, Terra and Aqua MODIS have produced an unprecedentedly large amount of high quality data products and supported a broad range of applications by the remote sensing science community and users worldwide. Constant and dedicated efforts have been made to continue instrument normal operation, to monitor and characterize changes in sensor responses, and to update calibration parameters to maintain the quality of MODIS data products. This paper provides an overview of instrument operation and calibration activities, and performance. On-orbit changes in sensor responses are illustrated. Also discussed are challenging issues, calibration strategies, and future efforts.
On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and record flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds and by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts.
Dam construction in the Mekong Basin has many cascading effects on the ecology, economy, and hydrology of the surrounding region. The focus of this study is to utilize the Soil Water Assessment Tool (SWAT), developed at Texas A & M, a rainfall-runoff hydrologic model to determine change in sedimentation in the Mekong Basin after the construction of dams. This study uses land cover land use and reservoir datasets created by the NASA SERVIR-Mekong Regional Land Cover Monitoring System and Dam Inundation Mapping Tool as inputs into the model. The study also builds on the capabilities of the SWAT model by using the sediment trapping efficiency (STE) equation from Brune (1953), rewritten by Kummu & Varis (2007), to calculate STE of dams and estimate change in sediment concentration downstream. The outputs from this study can be used to inform dam operation policies, study the correlation between dams and delta subsidence, and study the impact of dams on river fisheries, which are all pressing issues in the Mekong region.
NASA AFRC is a United States government entity that conducts the integration and operation of new and unproven technologies into proven flight vehicles as well as the flight test of one-of-a-kind experimental aircraft. AFRC also maintains and operates several platform aircraft that allow the integration of a wide range of sensors to conduct airborne remote sensing, science observations and airborne infrared astronomy. To support these types of operations AFRC has the organization, facilities and tools to support the experimental flight test of unique vehicles and conduct airborne sensing/observing.