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NASA NTRS2006

Meeting Report: Long Term Monitoring of Global Vegetation using Moderate Resolution Satellites

The international community has long recognized the need to coordinate observations of Earth from space. In 1984, this situation provided the impetus for creating the Committee on Earth Observation Satellites (CEOS), an international coordinating mechanism charged with coordinating international civil spaceborne missions designed to observe and study planet Earth. Within CEOS, its Working Group on Calibration and Validation (WGCV) is tasked with coordinating satellite-based global observations of vegetation. Currently, several international organizations are focusing on the requirements for Earth observation from space to address key science questions and societal benefits related to our terrestrial environment. The Global Vegetation Workshop, sponsored by the WGCV and held in Missoula, Montana, 7-10 August, 2006, was organized to establish a framework to understand the inter-relationships among multiple, global vegetation products and identify opportunities for: 1) Increasing knowledge through combined products, 2) Realizing efficiency by avoiding redundancy, and 3) Developing near- and long-term plans to avoid gaps in our understanding of critical global vegetation information. The Global Vegetation Workshop brought together 135 researchers from 25 states and 14 countries to advance these themes and formulate recommendations for CEOS members and the Global Earth Observation System of Systems (GEOSS). The eighteen oral presentations and most of the 74 posters presented at the meeting can be downloaded from the meeting website (www.ntsg.umt.edu/VEGMTG/). Meeting attendees were given a copy of the July 2006 IEEE Transactions on Geoscience and Remote Sensing Special Issue on Global Land Product Validation, coordinated by the CEOS Working Group on Calibration and Validation (WGCV). This issue contains 29 articles focusing on validation products from several of the sensors discussed during the workshop.

Morisette, Jeffrey↗
NASA NTRS2007

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Welton, Ellsworth J.↗
NASA NTRS2005

A Fast Implementation of the ISODATA Clustering Algorithm

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to ISODATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

Memarsadeghi, Nargess↗
NASA NTRS2007

Timber Volume and Biomass Estimates in Central Siberia from Satellite Data

Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can help overcome these problems. In this joint US and Russian study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10degx12deg area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods.

Ranson, K. Jon↗
NASA NTRS2008

Efficient Kriging via Fast Matrix-Vector Products

Interpolating scattered data points is a problem of wide ranging interest. Ordinary kriging is an optimal scattered data estimator, widely used in geosciences and remote sensing. A generalized version of this technique, called cokriging, can be used for image fusion of remotely sensed data. However, it is computationally very expensive for large data sets. We demonstrate the time efficiency and accuracy of approximating ordinary kriging through the use of fast matrixvector products combined with iterative methods. We used methods based on the fast Multipole methods and nearest neighbor searching techniques for implementations of the fast matrix-vector products.

Memarsadeghi, Nargess↗
NASA NTRS2006

Performance of the GLAS Laser Transmitter in Space

The Geoscience Laser Altimeter System (GLAS), launched in January 2003, is a laser altimeter and lidar for the Earth Observing System's (EOS) ICESat mission. The laser transmitter requirements, design and qualification test results and in-flight performance for this space-based remote sensing instrument is summarized and presented.

Yu, Anthony W.↗
NASA NTRS2007

Performance of the Lidar Design and Data Algorithms for the GLAS Global Cloud and Aerosol Measurements

The Geoscience Laser Altimeter System (GLAS) launched in early 2003 is the first polar orbiting satellite lidar. The instrument design includes high performance observations of the distribution and optical scattering cross sections of atmospheric clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. For the atmospheric cloud and aerosol measurements, the 532 nm channel was designed for ultra high efficiency with solid state photon counting detectors and etalon filtering. Data processing algorithms were developed to calibrate and normalize the signals and produce global scale data products of the height distribution of cloud and aerosol layers and their optical depths and particulate scattering cross sections up to the limit of optical attenuation. The paper will concentrate on the effectiveness and limitations of the lidar channel design and data product algorithms. Both atmospheric receiver channels meet and exceed their design goals. Geiger Mode Avalanche Photodiode modules are used for the 532 nm signal. The operational experience is that some signal artifacts and non-linearity require correction in data processing. As with all photon counting detectors, a pulse-pile-up calibration is an important aspect of the measurement. Additional signal corrections were found to be necessary relating to correction of a saturation signal-run-on effect and also for daytime data, a small range dependent variation in the responsivity. It was possible to correct for these signal errors in data processing and achieve the requirement to accurately profile aerosol and cloud cross section down to 10-7 llm-sr. The analysis procedure employs a precise calibration against molecular scattering in the mid-stratosphere. The 1064 nm channel detection employs a high-speed analog APD for surface and atmospheric measurements where the detection sensitivity is limited by detector noise and is over an order of magnitude less than at 532 nm. A unique feature of the GLAS is a full acquisition of the surface return pulse, which has important application to the atmospheric transmission retrieval.

Spinhirne, James D.↗
NASA NTRS2008

Abstracts of the Annual Meeting of Planetary Geologic Mappers, Flagstaff, AZ, 2008

Topics discussed include: Merging of the USGS Atlas of Mercury 1:5,000,000 Geologic Series; Geologic Mapping of the V-36 Thetis Regio Quadrangle: 2008 Progress Report; Structural Maps of the V-17 Beta Regio Quadrangle, Venus; Geologic Mapping of Isabella Quadrangle (V-50) and Helen Planitia, Venus; Renewed Mapping of the Nepthys Mons Quadrangle (V-54), Venus; Mapping the Sedna-Lavinia Region of Venus; Geologic Mapping of the Guinevere Planitia Quadrangle of Venus; Geological Mapping of Fortuna Tessera (V-2): Venus and Earth's Archean Process Comparisons; Geological Mapping of the North Polar Region of Venus (V-1 Snegurochka Planitia): Significant Problems and Comparisons to the Earth's Archean; Venus Quadrangle Geological Mapping: Use of Geoscience Data Visualization Systems in Mapping and Training; Geologic Map of the V-1 Snegurochka Planitia Quadrangle: Progress Report; The Fredegonde (V-57) Quadrangle, Venus: Characterization of the Venus Midlands; Formation and Evolution of Lakshmi Planum (V-7), Venus: Assessment of Models using Observations from Geological Mapping; Geologic Map of the Meskhent Tessera Quadrangle (V-3), Venus: Evidence for Early Formation and Preservation of Regional Topography; Geological Mapping of the Lada Terra (V-56) Quadrangle, Venus: A Progress Report; Geology of the Lachesis Tessera Quadrangle (V-18), Venus; Geologic Mapping of the Juno Chasma Quadrangle, Venus: Establishing the Relation Between Rifting and Volcanism; Geologic Mapping of V-19, V-28, and V-53; Lunar Geologic Mapping Program: 2008 Update; Geologic Mapping of the Marius Quadrangle, the Moon; Geologic Mapping along the Arabia Terra Dichotomy Boundary: Mawrth Vallis and Nili Fossae, Mars: Introductory Report; New Geologic Map of the Argyre Region of Mars; Geologic Evolution of the Martian Highlands: MTMs -20002, -20007, -25002, and -25007; Mapping Hesperia Planum, Mars; Geologic Mapping of the Meridiani Region, Mars; Geology of Holden Crater and the Holden and Ladon Multi-Ring Impact Basins, Margaritifer Terra, Mars; Geologic Mapping of Athabasca Valles; Geologic Mapping of MTM -30247, -35247 and -40247 Quadrangles, Reull Vallis Region of Mars; Geologic Mapping of the Martian Impact Crater Tooting; Geology of the Southern Utopia Planitia Highland-Lowland Boundary Plain: First Year Results and Second Year Plan; Mars Global Geologic Mapping: Amazonian Results; Recent Geologic Mapping Results for the Polar Regions of Mars; Geologic Mapping of the Medusae Fossae Formation on Mars (MC-8 SE and MC-23 NW) and the Northern Lowlands of Venus (V-16 and V-15); Geologic Mapping of the Zal, Hi'iaka, and Shamshu Regions of Io; Global Geologic Map of Europa; Material Units, Structures/Landforms, and Stratigraphy for the Global Geologic Map of Ganymede (1:15M); and Global Geologic Mapping of Io: Preliminary Results.

Bleamaster, Leslie F., III↗
NASA NTRS2007

Using MODIS and GLAS Data to Develop Timber Volume Estimates in Central Siberia

The boreal forest is the Earth's largest terrestrial biome, covering some 12 million km2 and accounting for about one third of this planet's total forest area. Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. Ground based forest inventories, have much uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse and/or lacking. In addition, many of the forest inventories that do exist for Siberia are now a decade or more old. Thus, available forest inventories fail to capture the current conditions. Changes in forest structure in a particular forest-type and region can change significantly due to changing environment conditions, and natural and anthropogenic disturbance. Remote sensing methods can potentially overcome these problems. Multispectral sensors can be used to provide vegetation cover maps that show a timely and accurate geographic distribution of vegetation types rather than decade old ground based maps. Lidar sensors can be used to directly obtain measurements that can be used to derive critical forest structure information (e.g., height, density, and volume). These in turn can used to estimate biomass components using allometric equations without having to use out dated forest inventory. Finally, remote sensing data is ideally suited to provide a sampling basis for a rigorous statistical estimate of the variance and error bound on forest structure measures. In this study, new remote sensing methods were applied to develop estimates timber volume using NASA's MODerate resolution Imaging Spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) for a 10 deg x 10 deg area in central Siberia. Using MODIS and GLAS data, maps were produced for cover type and timber volume for 2003, and a realistic variance (error bound) for timber volume was calculated for the study area. In this 'study we used only GLAS footprints that had a slope value of less than 10 deg. This was done to avoid large errors due to the effect of slope on the GLAS models. The method requires the integration of new remote sensing methods with available ground studies of forest timber volume conducted in Russian forests. The results were compared to traditional ground forest inventory methods reported in the literature and to ground truth collected in the study area.

Ranson, K. Jon↗
NASA NTRS2007

A Fast Implementation of the Isodata Clustering Algorithm

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to IsoDATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

Memarsadeghi, Nargess↗
NASA NTRS2009

The 50 Constellation Priority Sites

The Constellation program (CxP) has developed a list of 50 sites of interest on the Moon which will be targeted by the LRO narrow angle camera. The list has also been provided to the M~ team to supplement their targeting list. This list does not represent a "site selection" process; rather the goal was to find "representative" sites and terrains to understand the range of possible surface conditions for human lunar exploration to aid engineering design and operational planning. The list compilers leveraged heavily on past site selection work (e.g. Geoscience and a Lunar Base Workshop - 1988, Site Selection Strategy for a Lunar Outpost - 1990, Exploration Systems Architecture Study (ESAS) - 2005). Considerations included scientific, resource utilization, and operational merits, and a desire to span lunar terrain types. The targets have been organized into two "tiers" of 25 sites each to provide a relative priority ranking in the event of mutual interference. A LEAG SAT (special action team) was established to validate and recommend modifications to the list. This SAT was chaired by Dr. Paul Lucey. They provided their final results to CxP in May. Dr. Wendell Mendell will organize an on-going analysis of the data as they come down to ensure data quality and determine if and when a site has sufficient data to be retired from the list. The list was compiled using the best available data, however, it is understood that with the flood of new lunar data, minor modifications or adjustments may be required.

Noble, S.↗
NASA NTRS2010

PDS Lunar Data Node Restoration of Apollo In-Situ Surface Data

The Apollo missions between 1969 and 1972 deployed scientific instruments on the Moon's surface which made in-situ measurements of the lunar environment. Apollo II had the short-term Early Apollo Surface Experiments Package (EASEP) and Apollos 12, 14, 15, 16, and 17 each set up an Apollo Lunar Surface Experiments Package (ALSEP). Each ALSEP package contained a different suite of instruments which took measurements and radioed the results back to Earth over periods from 5 to 7 years until they were turned off on 30 September 1977. To this day the ALSEP data remain the only long-term in-situ information on the Moon's surface environment. The Lunar Data Node (LDN) has been formed under the auspices of the Planetary Data System (PDS) Geosciences Node to put relevant, scientifically important Apollo data into accessible digital form for use by researchers and mission planners. We will report on progress made since last year and plans for future data restorations.

Williams, David R.↗
NASA NTRS2010

Mission Performance of the GLAS Thermal Control System - 7 Years In Orbit

ICESat (Ice, Cloud and land Elevation Satellite) was launched in 2003 carrying a single science instrument - the Geoscience Laser Altimeter System (GLAS). Its primary mission was to measure polar ice thickness. The GLAS thermal control architecture utilized propylene Loop Heat Pipe (LHP) technology to provide selectable and stable temperature control for the lasers and other electronics over a widely varying mission thermal environment. To minimize expected degradation of the radiators, Optical Solar Reflectors (OSRs) were used for both LHP radiators to minimize degradation caused by UV exposure in the various spacecraft attitudes necessary throughout the mission. Developed as a Class C mission, with selective redundancy, the thermal architecture was single st ring, except for temperature sensors used for heater control during normal operations. Although originally planned for continuous laser operations over the nominal three year science mission, laser anomalies limited operations to discrete measurement campaigns repeated throughout the year. For trending of the science data, these periods were selected to occur at approximately the same time each year, which resulted in operations during similar attitudes and beta angles. Despite the laser life issues, the LHPs have operated nearly continuously over this time, being non-operational for only brief periods. Using mission telemetry, this paper looks at the performance of the thermal subsystem during these periods and provides an assessment of radiator degradation over the mission lifetime.

Grob, Eric W.↗
NASA NTRS2010

ICESat-2 Simulated Data from Airborne Altimetery

Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is scheduled to launch in 2015 and will carry onboard the Advanced Topographic Laser Altimeter System (ATLAS), which represents a new approach to spaceborne determination of surface elevations. Specifically, the current ATLAS design is for a micropulse, multibeam, photon-counting laser altimeter with lower energy, a shorter pulse width, and a higher repetition rate relative to the Geoscience Laser Altimeter (GLAS), the instrument that was onboard ICESat. Given the new and untested technology associated with ATLAS, airborne altimetry data is necessary (1) to test the proposed ATLAS instrument geometry, (2) to validate instrument models, and (3) to assess the atmospheric effects on multibeam altimeters. We present an overview of the airborne instruments and datasets intended to address the ATLAS instrument concept, including data collected over Greenland (July 2009) using an airborne SBIR prototype 100 channel, photon-counting, terrain mapping altimeter, which addresses the first of these 3 scientific concerns. Additionally, we present the plan for further simulator data collection over vegetated and ice covered regions using Multiple Altimeter Beam Experimental Lidar (MABEL), intended to address the latter two scientific concerns. As the ICESAT-2 project is in the design phase, the particular configuration of the ATLAS instrument may change. However, we expect this work to be relevant as long as ATLAS pursues a photon-counting approach.

Brunt, Kelly M.↗
NASA NTRS2011

Performance of the GLAS Space Lidar Receiver Through Its Seven-Year Space Mission

NASA s Ice, Cloud, and land Elevation Satellite (ICESat) mission [1,2] carrying the Geoscience Laser Altimeter System (GLAS) Instrument, was launched on January 12, 2003. The three lasers on ICESat have made a total of 1.98 billion laser shot measurements of the Earth s surface and atmosphere during its 17 science data collection campaigns over its seven year operating lifetime. ICESat completed its science mission after the last laser stopped operating in October 2009. The spacecraft was de-orbited on August 30, 2010. The GLAS instrument carried 3 diode-pumped Q-switched Nd:YAG lasers, which emitted 6-nsec wide pulses at 1064 and 532 nm at a 40-Hz rate. There are three lidar receiver channels, a 1064 nm surface altimetry channel, a 1064 nm cloud backscattering lidar channel, and a 532 nm cloud and aerosol backscattering lidar channel. The altimetry and cloud backscatter channels used Si avalanche photodiode (APD) operated in analog mode as in the Mars Global Surveyor s Mars Orbital Laser Altimeter [3,4]. GLAS also utilized a number of new technologies and techniques for space lidar, including passively Q-switched diode-pumped Nd:YAG lasers, a 1-m diameter telescope, a temperature tuned etalon optical bandpass filter, Si APD single photon counting detectors, 1 Gsample/sec waveform digitizers, ultra stable clock oscillators, and digital signal processing and detection algorithms [5]. A global position system (GPS) receiver was used to provide the spacecraft position and epoch times. The ICESat mission provided a unique opportunity to monitor the lidar component performance in the space environment over a multi-year time period. We performed a number of engineering tests periodically to monitor the lidar receiver performance, including receiver sensitivity, timing precision, detector dark noise, etc. A series of engineering tests were also performed after the end of the science mission to evaluate the performance of the spare detector, oscillator, waveform digitizer, and GPS receiver. An experiment was conducted which pointed GLAS to Venus to test the receiver sensitivity to star light and to verify GLAS bore sight with respect to the spacecraft coordinate system. These tests provided unique data to assess the degradation and the rate of change of these key lidar components due to space radiation and aging. They also helped to validate new techniques to operate and calibrate future space lidars.

Sun, Xiaoli↗
NASA NTRS2011

Long Term Missions at the Sun-Earth Libration Point L1: ACE, SOHO, and WIND

Three heliophysics missions -- the Advanced Composition Explorer (ACE), Solar Heliospheric Observatory (SOHO), and the Global Geoscience WIND -- have been orbiting the Sun-Earth interior libration point L1 continuously since 1997, 1996, and 2004, respectively. ACE and WIND (both NASA missions) and SOHO (an ESA-NASA joint mission) are all operated from the NASA Goddard Space Flight Center (GSFC). While ACE and SOHO have been dedicated libration point orbiters since their launches, WIND has had also a remarkable 10-year career flying a deep-space, multiple lunar-flyby trajectory prior to 2004. That era featured 36 targeted lunar flybys with excursions to both L1 and L2 before its final insertion in L1 orbit. A figure depicts the orbits of the three spacecraft, showing projections of the orbits onto the orthographic planes of a solar rotating ecliptic frame of reference. The SOHO orbit is a quasi-periodic halo orbit, where the frequencies of the in-plane and out-of-plane motions are practically equal. Such an orbit is seen to repeat itself with a period of approximately 178 days. For ACE and WIND, the frequencies of the in-plane and out-of-plane motions are unequal, giving rise to the characteristic Lissajous motion. ACE's orbit is of moderately small amplitude, whereas WIND's orbit is a large-amplitude Lissajous of dimensions close to those of the SOHO halo orbit. As motion about the collinear points is inherently unstable, stationkeeping maneuvers are necessary to prevent orbital decay and eventual escape from the L1 region. Though the three spacecraft are dissimilar (SOHO is a 3-axis stabilized Sun pointer, WIND is a spin-stabilized ecliptic pole pointer, and ACE is also spin-stabilized with its spin axis maintained between 4 and 20 degrees of the Sun), the stationkeeping technique for the three is fundamentally the same. The technique consists of correcting the energy of the orbit via a delta-V directed parallel or anti-parallel to the Spacecraft-to-Sun line. SOHO achieves this using thrusters oriented in line with the solar direction. WIND achieves the delta-V via pulsing radial thrusters when aligned with the Sun. ACE uses axial thrusters to apply delta-V with a component that is 94% or more aligned with the ACE-Sun line. Sunward thrust adds energy to the orbit preventing decay back toward Earth. Thrust directed anti-Sunward takes energy out of the L1 orbit, thereby preventing escape from the Earth-Moon system into independent heliocentric orbit. Libration point orbit stationkeeping delta-V costs grow exponentially with time elapsed from the last maneuver performed. The doubling time constant is approximately 16 days. For the sake of fuel conservation, and for limiting the absolute magnitude of propulsion performance errors, stationkeeping maneuvers should be performed before the delta-V grows too large; for our purposes 'too large' is considered to be greater than 0.5 m/sec. In practice, the typical interval between burns for this trio is about three months, and the typical delta-V is much smaller than 0.5 m/sec. Typical annual stationkeeping costs have been around 1.0 m/sec for ACE and WIND, and much less than that for SOHO. All three spacecraft have ample fuel remaining; barring contingencies all three could, in principle, be maintained at L1 for decades to come. This paper will review the L1 orbits and the mission history of ACE, WIND, and SOHO, and describe the stationkeeping techniques and orbit maneuver experience. The Lissajous phase control that was practiced for ACE during the period from 1999 to 2001 will also be briefly discussed. The final section will consider the future of these ongoing missions.

Roberts, Craig E.↗
NASA NTRS2011

An Archean Biosphere Initiative

The search for life on extrasolar planets will necessarily focus on the imprints of biolgy on the composition of planetary atmospheres. The most notable biological imprint on the modern terrestrial atmosphere is the presence of 21 % O2, However, during most of the past 4 billion years, life and the surface environments on Earth were profoundly different than they are today. It is therefore a major goal of the astrobiology community to ascertain how the O2 content of the atmosphere has varied with time. and to understand the causes of these variations. The NAI and NASA Exobiology program have played critical roles in developing our current understanding of the ancient Earth's atmosphere, supporting diverse observational, analytical, and computational research in geoscience, life science, and related fields. In the present incarnation of the NAI, ongoing work is investigating (i) variations in atmospheric O2 in the Archean to the Cambrian, (ii) characterization of the redox state of the oceans shortly before, during and after the Great Oxidation Event (GOE), and (iii) unraveling the complex connections between environmental oxygenation, global climate, and the evolution of life.

Anbar, A. D.↗
NASA NTRS2011

Target Assembly to Check Boresight Alignment of Active Sensors

A compact and portable target assembly (Fig. 1) has been developed to measure the boresite alignment of LRO's Lunar Orbiter Laser Altimeter (LOLA) instrument at the spacecraft level. The concept for this target assembly has evolved over many years with earlier versions used to test the Mars Observer Laser Altimeter (MOLA), the Geoscience Laser Altimeter System (GLAS), and the Mercury Laser Altimeter (MLA) space-based instruments.

Ramos-Izquierdo, Luis↗