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NASA NTRS2011

ISS Has an Attitude! Determining ISS Attitude at the ISS Window Observational Research Facility (WORF) Using Landmarks

Universities and secondary schools can help solve a real issue for remote sensing from the ISS WORF through hands-on engineering and activities. Remote sensing technology is providing scientists with higher resolution, higher sensitivity sensors. Where is it pointing? - To take full advantage of these improved sensors, space platforms must provide commensurate improvements in attitude determination

Runco, Susan K.↗
NASA NTRS2011

Modeling the Height of Young Forests Regenerating from Recent Disturbances in Mississippi using Landsat and ICESat data

Many forestry and earth science applications require spatially detailed forest height data sets. Among the various remote sensing technologies, lidar offers the most potential for obtaining reliable height measurement. However, existing and planned spaceborne lidar systems do not have the capability to produce spatially contiguous, fine resolution forest height maps over large areas. This paper describes a Landsat-lidar fusion approach for modeling the height of young forests by integrating historical Landsat observations with lidar data acquired by the Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation (ICESat) satellite. In this approach, "young" forests refer to forests reestablished following recent disturbances mapped using Landsat time-series stacks (LTSS) and a vegetation change tracker (VCT) algorithm. The GLAS lidar data is used to retrieve forest height at sample locations represented by the footprints of the lidar data. These samples are used to establish relationships between lidar-based forest height measurements and LTSS-VCT disturbance products. The height of "young" forest is then mapped based on the derived relationships and the LTSS-VCT disturbance products. This approach was developed and tested over the state of Mississippi. Of the various models evaluated, a regression tree model predicting forest height from age since disturbance and three cumulative indices produced by the LTSS-VCT method yielded the lowest cross validation error. The R(exp 2) and root mean square difference (RMSD) between predicted and GLAS-based height measurements were 0.91 and 1.97 m, respectively. Predictions of this model had much higher errors than indicated by cross validation analysis when evaluated using field plot data collected through the Forest Inventory and Analysis Program of USDA Forest Service. Much of these errors were due to a lack of separation between stand clearing and non-stand clearing disturbances in current LTSS-VCT products and difficulty in deriving reliable forest height measurements using GLAS samples when terrain relief was present within their footprints. In addition, a systematic underestimation of about 5 m by the developed model was also observed, half of which could be explained by forest growth that occurred between field measurement year and model target year. The remaining difference suggests that tree height measurements derived using waveform lidar data could be significantly underestimated, especially for young pine forests. Options for improving the height modeling approach developed in this study were discussed.

Li, Ainong↗
NASA NTRS2011

Lidar Remote Sensing for Characterizing Forest Vegetation - Special Issue. Foreword

The Silvilaser 2009 conference held in College Station, Texas, USA, was the ninth conference in the Silvilaser series, which started in 2002 with the international workshop on using lidar (Light Detection and Ranging) for analyzing forest structure, held in Victoria, British Columbia, Canada. Following the Canadian workshop, subsequent forestry-lidar conferences took place in Australia, Sweden, Germany, USA, Japan, Finland, and the United Kingdom (UK). By the time this Silvilaser 2009 special issue of PE&RS is published, the 10th international conference will have been held in Freiburg, Germany, and planning will be ongoing for the 11th meeting to take place in Tasmania, Australia, in October 2011. Papers presented at the 2005 conference held in Blacksburg, Virginia, USA, were assembled in a special issue of PE&RS published in December 2006. Other special issues resulting from previous conferences were published in journals such as the Canadian Journal of Remote Sensing (2003), the Scandinavian Journal of Forest Research (2004), and Japan s Journal of Forest Planning (2008). Given the conference history and the much longer record of publications on lidar applications for estimating forest biophysical parameters, which dates back to the early 1980s, we may consider lidar an established remote sensing technology for characterizing forest canopy structure and estimating forest biophysical parameters. Randy Wynne, a professor at Virginia Tech and the final keynote speaker at Silvilaser 2009, made the case that it was time to push 30 years of research into operations, along the lines of what has already been done to good effect in the Scandinavian countries. In Randy s words, it s time to "Just do it!" This special issue includes a selection of papers presented during the 2009 Silvilaser conference, which consisted of eight sections as follows: (1) biomass and carbon stock estimates, (2) tree species and forest type classification, (3) data fusion and integration, (4, 5, and 6) forest inventory, (7) silvicultural and ecological applications, and (8) terrestrial lidar applications. Within the constraint limiting the number of papers that could be fitted into the special issue we attempted to select those papers that best represented these conference topics and sections, giving special consideration to studies using forestry lidar data collected from each of the three platforms -- terrestrial, airborne, and spaceborne. Reflecting the international participation and reach of the conference, the studies presented here took place in the USA, Canada, Taiwan, the UK, and China.

Popescu, Sorin C.↗
NASA NTRS2012

Optical Breath Gas Sensor for Extravehicular Activity Application

The function of the infrared gas transducer used during extravehicular activity (EVA) in the current space suit is to measure and report the concentration of carbon dioxide (CO2) in the ventilation loop. The next generation Portable Life Support System (PLSS) requires next generation CO2 sensing technology with performance beyond that presently in use on the Shuttle/International Space Station extravehicular mobility unit (EMU). Accommodation within space suits demands that optical sensors meet stringent size, weight, and power requirements. A laser diode (LD) spectrometer based on wavelength modulation spectroscopy (WMS) is being developed for this purpose by Vista Photonics, Inc. Two prototype devices were delivered to NASA Johnson Space Center (JSC) in September 2011. The sensors incorporate a laser diode based CO2 channel that also includes an incidental water vapor (humidity) measurement and a separate oxygen (O2) channel using a vertical cavity surface emitting laser (VCSEL). Both prototypes are controlled digitally with a field-programmable gate array (FPGA)/microcontroller architecture. Based on the results of the initial instrument development, further prototype development and testing of instruments leveraging the lessons learned were desired. The present development extends and upgrades the earlier hardware to the Advanced PLSS 2.0 test article being constructed and tested at JSC. Various improvements to the electronics and gas sampling are being advanced by this project. The combination of low power electronics with the performance of a long wavelength laser spectrometer enables multi-gas sensors with significantly increased performance over that presently offered in the EMU. .

Wood, William R.↗
NASA NTRS2012

A Brief Overview of NASA Glenn Research Center Sensor and Electronics Activities

Aerospace applications require a range of sensing technologies. There is a range of sensor and sensor system technologies being developed using microfabrication and micromachining technology to form smart sensor systems and intelligent microsystems. Drive system intelligence to the local (sensor) level -- distributed smart sensor systems. Sensor and sensor system development examples: (1) Thin-film physical sensors (2) High temperature electronics and wireless (3) "lick and stick" technology. NASA GRC is a world leader in aerospace sensor technology with a broad range of development and application experience. Core microsystems technology applicable to a range of application environmentS.

Hunter, Gary W.↗
NASA NTRS2013

Optical Breath Gas Sensor for Extravehicular Activity Application

The function of the infrared gas transducer used during extravehicular activity in the current space suit is to measure and report the concentration of carbon dioxide (CO2) in the ventilation loop. The next generation portable life support system (PLSS) requires next generation CO2 sensing technology with performance beyond that presently in use on the Space Shuttle/International Space Station extravehicular mobility unit (EMU). Accommodation within space suits demands that optical sensors meet stringent size, weight, and power requirements. A laser diode spectrometer based on wavelength modulation spectroscopy is being developed for this purpose by Vista Photonics, Inc. Two prototype devices were delivered to NASA Johnson Space Center (JSC) in September 2011. The sensors incorporate a laser diode-based CO2 channel that also includes an incidental water vapor (humidity) measurement and a separate oxygen channel using a vertical cavity surface emitting laser. Both prototypes are controlled digitally with a field-programmable gate array/microcontroller architecture. The present development extends and upgrades the earlier hardware to the Advanced PLSS 2.0 test article being constructed and tested at JSC. Various improvements to the electronics and gas sampling are being advanced by this project. The combination of low power electronics with the performance of a long wavelength laser spectrometer enables multi-gas sensors with significantly increased performance over that presently offered in the EMU.

Wood, William R.↗
NASA NTRS2013

Cryogenics Research and Engineering Experience

Energy efficient storage, transfer and use of cryogens and cryogenic propellants on Earth and in space have a direct impact on NASA, government and commercial programs. Research and development on thermal insulation, propellant servicing, cryogenic components, material properties and sensing technologies provides industry, government and research institutions with the cross-cutting technologies to manage low-temperature applications. Under the direction of the Cryogenic Testing Lab at Kennedy Space Center, the work experience acquired allowed me to perform research, testing, design and analysis of current and future cryogenic technologies to be applied in several projects.

Toro Medina, Jaime A.↗
NASA NTRS2014

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Light Detection & Ranging (LIDAR)↗
NASA NTRS2014

Physiologically Modulating Videogames or Simulations which use Motion-Sensing Input Devices

New types of controllers allow players to make inputs to a video game or simulation by moving the entire controller itself. This capability is typically accomplished using a wireless input device having accelerometers, gyroscopes, and an infrared LED tracking camera. The present invention exploits these wireless motion-sensing technologies to modulate the player's movement inputs to the videogame based upon physiological signals. Such biofeedback-modulated video games train valuable mental skills beyond eye-hand coordination. These psychophysiological training technologies enhance personal improvement, not just the diversion, of the user.

Pope, Alan T.↗
NASA NTRS2011

3D Vegetation Mapping Using UAVSAR, LVIS, and LIDAR Data Acquisition Methods

The overarching objective of this ongoing project is to assess the role of vegetation within climate change. Forests capture carbon, a green house gas, from the atmosphere. Thus, any change, whether, natural (e.g. growth, fire, death) or due to anthropogenic activity (e.g. logging, burning, urbanization) may have a significant impact on the Earth's carbon cycle. Through the use of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA's Laser Vegetation Imaging Sensor (LVIS), which are airborne Light Detection and Ranging (LIDAR) remote sensing technologies, we gather data to estimate the amount of carbon contained in forests and how the content changes over time. UAVSAR and LVIS sensors were sent all over the world with the objective of mapping out terrain to gather tree canopy height and biomass data; This data is in turn used to correlate vegetation with the global carbon cycle around the world.

Uninhabited Aerial Vehicle Synthetic Aperture Rada↗
NASA NTRS2011

The Winter 2010 and 2011 FRONT/NIRSS In-Flight Icing Hazard Detection Project

The NASA Icing Remote Sensing System (NIRSS) deploys a vertically-pointing K-band radar, a lidar ceiliometer, and a profiling microwave radiometer to obtain measurements for diagnosing local inflight icing conditions. RAL is working with NASA GRC to develop algorithms and data ingest and display software for the system. NASA has an ongoing activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. As part of that effort NASA teamed with NCAR to develop software that fuses data from multiple instruments into a single detected icing condition product. The multiple instrument approach, which is the current emphasis of this activity, utilizes a K-band vertical staring radar, a microwave radiometer that detects twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed in C++ program with a Java-based web display of resultant supercooled LWC profile and aircraft hazard identification. In 2010, a multi-channel scanning radiometer, designed and built by Radiometrics, Inc. under a SBIR grant,,was added to the system to assess its utility in improving icing diagnoses.

Serke, David↗
NASA NTRS2016

Optical Breath Gas Extravehicular Activity Sensor for the Advanced Portable Life Support System

The function of the infrared gas transducer used during extravehicular activity (EVA) in the current space suit is to measure and report the concentration of carbon dioxide (CO2) in the ventilation loop. The next generation portable life support system (PLSS) requires highly accurate CO2 sensing technology with performance beyond that presently in use on the International Space Station extravehicular mobility unit (EMU). Further, that accuracy needs to be provided over the full operating pressure range of the suit (3 to 25 psia). Accommodation within space suits demands that optical sensors meet stringent size, weight, and power requirements. A laser diode (LD) sensor based on infrared absorption spectroscopy is being developed for this purpose by Vista Photonics, Inc. Version 1.0 prototype devices were delivered to NASA Johnson Space Center (JSC) in September 2011. The prototypes were upgraded with more sophisticated communications and faster response times to version 2.0 and delivered to JSC in July 2012. The sensors incorporate a laser diode based CO2 channel that also includes an incidental water vapor (humidity) measurement. The prototypes are controlled digitally with an field-programmable gate array microcontroller architecture. Based on the results of the iterative instrument development, further prototype development and testing of instruments were performed leveraging the lessons learned where feasible. The present development extends and upgrades the earlier hardware for the advanced PLSS 2.5 prototypes for testing at JSC. The prototypes provide significantly enhanced accuracy for water vapor measurement and eliminate wavelength drift affecting the earlier versions. Various improvements to the electronics and gas sampling are currently being advanced including the companion development of engineering development units that will ultimately be capable of radiation tolerance. The combination of low power electronics with the performance of a long wavelength laser spectrometer enables multi-gas sensors with significantly increased performance over that presently offered in the EMU.

Wood, William R.↗
NASA NTRS2015

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the MODIS sensor aboard the NASA Aqua satellite. Aqua was chosen due to an afternoon orbit over the United States when land surface temperatures are relatively warm and improve the contrast between damaged and undamaged areas. This orbit is also similar to the orbit of the Suomi-National Polar-orbiting Partnership (NPP) satellite. The Suomi NPP satellite hosts the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which is the next generation of a MODIS-like sensor in polar orbit.

MODIS VIIRS↗
NASA NTRS2015

Investigation of Spiral Bevel Gear Condition Indicator Validation via AC-29-2C Combining Test Rig Damage Progression Data with Fielded Rotorcraft Data

This is the final of three reports published on the results of this project. In the first report, results were presented on nineteen tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Test Rig on spiral bevel gear sets designed to simulate helicopter fielded failures. In the second report, fielded helicopter HUMS data from forty helicopters were processed with the same techniques that were applied to spiral bevel rig test data. Twenty of the forty helicopters experienced damage to the spiral bevel gears, while the other twenty helicopters had no known anomalies within the time frame of the datasets. In this report, results from the rig and helicopter data analysis will be compared for differences and similarities in condition indicator (CI) response. Observations and findings using sub-scale rig failure progression tests to validate helicopter gear condition indicators will be presented. In the helicopter, gear health monitoring data was measured when damage occurred and after the gear sets were replaced at two helicopter regimes. For the helicopters or tails, data was taken in the flat pitch ground 101 rotor speed (FPG101) regime. For nine tails, data was also taken at 120 knots true airspeed (120KTA) regime. In the test rig, gear sets were tested until damage initiated and progressed while gear health monitoring data and operational parameters were measured and tooth damage progression documented. For the rig tests, the gear speed was maintained at 3500RPM, a one hour run-in was performed at 4000 in-lb gear torque, than the torque was increased to 8000 in-lbs. The HUMS gear condition indicator data evaluated included Figure of Merit 4 (FM4), Root Mean Square (RMS) or Diagnostic Algorithm 1(DA1), + 3 Sideband Index (SI3) and + 1 Sideband Index (SI1). These were selected based on their sensitivity in detecting contact fatigue damage modes from analytical, experimental and historical helicopter data. For this report, the helicopter dataset was reduced to fourteen tails and the test rig data set was reduced to eight tested gear sets. The damage modes compared were separated into three cases. For case one, both the gear and pinion showed signs of contact fatigue or scuffing damage. For case two, only the pinion showed signs of contact fatigue damage or scuffing. Case three was limited to the gear tests when scuffing occurred immediately after the gear run-in. Results of this investigation highlighted the importance of understanding the complete monitored systems, for both the helicopter and test rig, before interpreting health monitoring data. Further work is required to better define these two systems that include better state awareness of the fielded systems, new sensing technologies, new experimental methods or models that quantify the effect of system design on CI response and new methods for setting thresholds that take into consideration the variance of each system.

spiral bevel gears↗
NASA NTRS2016

Optical Breath Gas Extravehicular Activity Sensor for the Advanced Portable Life Support System

The infrared gas transducer used during extravehicular activity (EVA) in the extravehicular mobility unit (EMU) measures and reports the concentration of carbon dioxide (CO2) in the ventilation loop. It is nearing its end of life and there are a limited number remaining. Meanwhile, the next generation advanced portable life support system (PLSS) now being developed requires CO2 sensing technology with performance beyond that presently in use. A laser diode (LD) spectrometer based on wavelength modulation spectroscopy (WMS) is being developed to address both applications by Vista Photonics, Inc. Accommodation within space suits demands that optical sensors meet stringent size, weight, and power requirements. Version 1.0 devices were delivered to NASA Johnson Space Center (JSC) in 2011. The sensors incorporate a laser diode based CO2 channel that also includes an incidental water vapor (humidity) measurement. The prototypes are controlled digitally with a field-programmable gate array (FPGA)/microcontroller architecture. Version 2.0 devices with improved electronics and significantly reduced wetted volumes were delivered to JSC in 2012. A version 2.5 upgrade recently implemented wavelength stabilized operation, better humidity measurement, and much faster data analysis/reporting. A wholly reconfigured version 3.0 will maintain the demonstrated performance of earlier versions while being backwards compatible with the EMU and offering a radiation tolerant architecture.

Wood, William R.↗
NASA NTRS2017

Physiologically Modulating Videogames or Simulations which Use Motion-Sensing Input Devices

New types of controllers allow a player to make inputs to a video game or simulation by moving the entire controller itself or by gesturing or by moving the player's body in whole or in part. This capability is typically accomplished using a wireless input device having accelerometers, gyroscopes, and a camera. The present invention exploits these wireless motion-sensing technologies to modulate the player's movement inputs to the videogame based upon physiological signals. Such biofeedback-modulated video games train valuable mental skills beyond eye-hand coordination. These psychophysiological training technologies enhance personal improvement, not just the diversion, of the user.

Pope, Alan T.↗
NASA NTRS2018

MCT Avalanche Photodiode Detector for Two-Micron Active Remote Sensing Applications

Mercury Cadmium Telluride electron initiated avalanche photodiodes demonstrated a breakthrough in lidar active remote sensing technology. A lidar detection system, based on an array of these devices, was integrated and characterized for 2-μm applications. Characterization experiments were focused on evaluating the dark current, gain and responsivity variations with bias voltage. Quantum efficiency and input dynamic range including noise-equivalent-power and maximum detectable power, were calculated from these results. Operating the detection system using four pixels at 77.6 K, 12 V bias resulted in a current responsivity of 615.8 A/W and a voltage responsivity of 1.45 GV/W. Minimum detectable power of 14 pW was obtained, which is equivalent to 5.7 fW/Hz(exp 1/2) noise-equivalent-power, indicating an average noise-equivalent-power of 1.4 fW/Hz(exp 1/2) per pixel. Work is in progress to integrate and validate this detection system using a newly developed triple-pulse integrated path differential absorption lidar for simultaneous and independent atmospheric measurements of water vapor and carbon dioxide.

Refaat, Tamer F.↗
NASA NTRS2019

Towards a Satellite Formaldehyde – in situ Hybrid Estimate for Organic Aerosol Abundance

Organic aerosol (OA) is one of the main components of the global particulate burden and intimately links natural and anthropogenic emissions with air quality and climate. It is challenging to accurately represent OA in global models. Direct quantification of global OA abundance is not possible with current remote sensing technology; however, it may be possible to exploit correlations of OA with remotely observable quantities to infer OA spatiotemporal distributions. In particular, formaldehyde (HCHO) and OA share common sources via both primary emissions and secondary production from oxidation of volatile organic compounds (VOCs). Here, we examine OA–HCHO correlations using data from summertime airborne campaigns investigating biogenic (NASA SEAC4RS and DC3), biomass burning (NASA SEAC4RS), and anthropogenic conditions (NOAA CalNex and NASA KORUS-AQ). In situ OA correlates well with HCHO (r=0.59–0.97), and the slope and intercept of this relationship depend on the chemical regime. For biogenic and anthropogenic regions, the OA–HCHO slopes are higher in low NOx conditions, because HCHO yields are lower and aerosol yields are likely higher. The OA–HCHO slope of wildfires is over 9 times higher than that for biogenic and anthropogenic sources. The OA–HCHO slope is higher for highly polluted anthropogenic sources (e.g., KORUS-AQ) than less polluted (e.g., CalNex) anthropogenic sources. Near-surface OAs over the continental US are estimated by combining the observed in situ relationships with HCHO column retrievals from NASA's Ozone Monitoring Instrument (OMI). HCHO vertical profiles used in OA estimates are from climatology a priori profiles in the OMI HCHO retrieval or output of specific period from a newer version of GEOS-Chem. Our OA estimates compare well with US EPA IMPROVE data obtained over summer months (e.g., slope =0.60–0.62, r=0.56 for August 2013), with correlation performance comparable to intensively validated GEOS-Chem (e.g., slope =0.57, r=0.56) with IMPROVE OA and superior to the satellite-derived total aerosol extinction (r=0.41) with IMPROVE OA. This indicates that OA estimates are not very sensitive to these HCHO vertical profiles and that a priori profiles from OMI HCHO retrieval have a similar performance to that of the newer model version in estimating OA. Improving the detection limit of satellite HCHO and expanding in situ airborne HCHO and OA coverage in future missions will improve the quality and spatiotemporal coverage of our OA estimates, potentially enabling constraints on global OA distribution.

anthropogenic emissions↗