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NASA NTRS2012

Colors and Photometry of Bright Materials on Vesta as Seen by the Dawn Framing Camera

The Dawn spacecraft has been in orbit around the asteroid Vesta since July, 2011. The on-board Framing Camera has acquired thousands of high-resolution images of the regolith-covered surface through one clear and seven narrow-band filters in the visible and near-IR wavelength range. It has observed bright and dark materials that have a range of reflectance that is unusually wide for an asteroid. Material brighter than average is predominantly found on crater walls, and in ejecta surrounding caters in the southern hemisphere. Most likely, the brightest material identified on the Vesta surface so far is located on the inside of a crater at 64.27deg S, 1.54deg . The apparent brightness of a regolith is influenced by factors such as particle size, mineralogical composition, and viewing geometry. As such, the presence of bright material can indicate differences in lithology and/or degree of space weathering. We retrieve the spectral and photometric properties of various bright terrains from false-color images acquired in the High Altitude Mapping Orbit (HAMO). We find that most bright material has a deeper 1-m pyroxene band than average. However, the aforementioned brightest material appears to have a 1-m band that is actually less deep, a result that awaits confirmation by the on-board VIR spectrometer. This site may harbor a class of material unique for Vesta. We discuss the implications of our spectral findings for the origin of bright materials.

Schroeder, S. E.↗
NASA NTRS2012

Finding Near-Earth Asteroid (NEA) Destinations for Human Exploration: Implications for Astrobiology

The current number of known potential NEA targets for HSF is limited to those objects whose orbital characteristics are similar to that of the Earth. This is due to the projected capabilities of the exploration systems currently under consideration and development at NASA. However, NEAs with such orbital characteristics often have viewing geometries that place them at low solar elongations and thus are difficult to detect from the vicinity of Earth. While ongoing ground-based surveys and data archives maintained by the NEO Program Observation Program Office and the Minor Planet Center (MPC) have provided a solid basis upon which to build, a more complete catalog of the NEO population is required to inform a robust and sustainable HSF exploration program. Since all the present NEO observing assets are currently confined to the vicinity of the Earth, additional effort must be made to provide capabilities for detection of additional HSF targets via assets beyond Earth orbit. A space-based NEO survey telescope located beyond the vicinity of the Earth, has considerable implications for planetary science and astrobiology. Such a telescope will provide foundational knowledge of our Solar System small body population and detect targets of interest for both the HSF and scientific communities. Data from this asset will yield basic characterization data on the NEOs observed (i.e., albedo, size determination, potential for volatiles and organics, etc.) and help down select targets for future HSF missions. Ideally, the most attractive targets from both HSF and astrobiology perspectives are those NEAs that may contain organic and volatile materials, and which could be effectively sampled at a variety of locations and depths. Presented here is an overview of four space-based survey concepts; any one of which after just a few years of operation will discover many highly accessible NEO targets suitable for robotic and human exploration. Such a space-based survey mission will reveal incredible returns for several disciplines including: exploration, in situ resource utilization, planetary defense, and science. Of particular, interest to the scientific

Landis, Rob↗
NASA NTRS2011

MODIS Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms

To monitor the earth atmosphere and its surface changes, satellite based instruments collect continuous data. While some of the data is directly used, some others such as aerosol properties are indirectly retrieved from the observation data. While retrieved variables (RV) form very powerful products, they don't come without obstacles. Different satellite viewing geometries, calibration issues, dynamically changing atmospheric and earth surface conditions, together with complex interactions between observed entities and their environment affect them greatly. This results in random and systematic errors in the final products.

Albayrak, Arif↗
NASA NTRS2012

Top-of-the-Atmosphere Shortwave Flux Estimation from UV Observations: An Empirical Approach

Measurements of top of the atmosphere (TOA) radiation are essential to the understanding of Earth's climate. Clouds, aerosols, and ozone (0,) are among the most important agents impacting the Earth's short-wave (SW) radiation budget. There are several sensors in orbit that provide independent information related to the Earth's SW radiation budget. Having coincident information from these sensors is important for understanding their potential contributions. The A-train constellation of satellites provides a unique opportunity to analyze near-simultaneous data from several of these sensors. They include the Ozone Monitoring Instrument (OMI), on the NASA Aura satellite, that makes TOA hyper-spectral measurements from ultraviolet (UV) to visible wavelengths, and Clouds and the Earth's Radiant Energy System (CERES) instrument, on the NASA Aqua satellite, that makes broadband measurements in both the long- and short-wave. OMI measurements have been successfully utilized to derive the information on trace gases (e.g., 0 1, NO" and SO,), clouds, and absorbing aerosols. TOA SW fluxes are estimated using a combination of data from CERES and the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS). In this paper, OMI retrievals of cloud/aerosol parameters and 0 1 have been collocated with CERES TOA SW flux retrievals. We use this collocated data to develop a neural network that estimates TOA shortwave flux globally over ocean using data from OMI and meteorological analyses. This input data include the effective cloud fraction, cloud optical centroid pressure (OCP), total-column 0" and sun-satellite viewing geometry from OMI as well as wind speed and water vapor from the Goddard Earth Observing System 5 Modern Era Retrospective-analysis for Research and Applications (GEOS-5 MERRA) along with a climatology of chlorophyll content. We train the neural network using a subset of CERES retrievals of TOA SW flux as the target output (truth) and withhold a different subset of the CERES data to be used for validation.

Gupta, P.↗
NASA NTRS2012

Modeling and Maximum Likelihood Fitting of Gamma-Ray and Radio Light Curves of Millisecond Pulsars Detected with Fermi

Pulsed gamma rays have been detected with the Fermi Large Area Telescope (LAT) from more than 20 millisecond pulsars (MSPs), some of which were discovered in radio observations of bright, unassociated LAT sources. We have fit the radio and gamma-ray light curves of 19 LAT-detected MSPs in the context of geometric, outermagnetospheric emission models assuming the retarded vacuum dipole magnetic field using a Markov chain Monte Carlo maximum likelihood technique. We find that, in many cases, the models are able to reproduce the observed light curves well and provide constraints on the viewing geometries that are in agreement with those from radio polarization measurements. Additionally, for some MSPs we constrain the altitudes of both the gamma-ray and radio emission regions. The best-fit magnetic inclination angles are found to cover a broader range than those of non-recycled gamma-ray pulsars.

Johnson, T. J.↗
NASA NTRS2011

Nocturnal Aerosol Optical Depth Measurements with a Small-Aperture Automated Photometer Using the Moon as a Light Source

A method is described that enables the use of lunar irradiance to obtain nighttime aerosol optical depth (AOD) measurements using a small-aperture photometer. In this approach, the U.S. Geological Survey lunar calibration system was utilized to provide high-precision lunar exoatmospheric spectral irradiance predictions for a ground-based sensor location, and when combined with ground measurement viewing geometry, provided the column optical transmittance for retrievals of AOD. Automated multiwavelength lunar measurements were obtained using an unmodified Cimel-318 sunphotometer sensor to assess existing capabilities and enhancements needed for day/night operation in NASA s Aerosol Robotic Network (AERONET). Results show that even existing photometers can provide the ability for retrievals of aerosol optical depths at night near full moon. With an additional photodetector signal-to-noise improvement of 10-100, routine use over the bright half of the lunar phase and a much wider range of wavelengths and conditions can be achieved. Although the lunar cycle is expected to limit the frequency of observations to 30%-40% compared to solar measurements, nevertheless this is an attractive extension of AERONET capabilities.

Berkoff, Timothy A.↗
NASA NTRS2011

EPIC Radiance Simulator for Deep Space Climate ObserVatoRy (DSCOVR)

The Deep Space Climate ObserVatoRy (DSCOVR) is a planned space weather mission for the Sun and Earth observations from the Lagrangian L1 point. Onboard of DSCOVR is a multispectral imager EPIC designed for unique observations of the full illuminated disk of the Earth with high temporal and 10 km spatial resolution. Depending on latitude, EPIC will observe the same Earth surface area during the course of the day in a wide range of solar and view zenith angles in the backscattering view geometry with the scattering angle of 164-172 . To understand the information content of EPIC data for analysis of the Earth clouds, aerosols and surface properties, an EPIC radiance Simulator was developed covering the UV -VIS-NIR range including the oxygen A and B-bands (A=340, 388, 443, 555, 680, 779.5, 687.7, 763.3 nm). The Simulator uses ancillary data (surface pressure/height, NCEP wind speed) as well as MODIS-based geophysical fields such as spectral surface bidirectional reflectance, column water vapor, and properties of aerosols and clouds including optical depth, effective radius, phase and cloud top height. The original simulations are conducted at 1 km resolution using the look-up table approach and then are averaged to 10 km EPIC radiances. This talk will give an overview of the EPIC Simulator with analysis of results over the continental USA and northern Atlantic.

Lyapustin, Alexei↗
NASA NTRS2012

Cloud Height Retrieval with Oxygen A and B Bands for the Deep Space Climate Observatory (DSCOVR) Mission

Planned to fly in 2014, the Deep Space Climate Observatory (DSCOVR) would see the whole sunlit half of the Earth from the L 1 Lagrangian point and would provide simultaneous data on cloud and aerosol properties with its Earth Polychromatic Imaging Camera (EPIC). EPIC images the Earth on a 2Kx2K CCD array, which gives a horizontal resolution of about 10 km at nadir. A filter-wheel provides consecutive images in 10 spectral channels ranging from the UV to the near-IR, including the oxygen A and B bands. This paper presents a study of retrieving cloud height with EPIC's oxygen A and B bands. As the first step, we analyzed the effect of cloud optical and geometrical properties, sun-view geometry, and surface type on the cloud height determination. Second, we developed two cloud height retrieval algorithms that are based on the Mixed Lambertian-Equivalent Reflectivity (MLER) concept: one utilizes the absolute radiances at the Oxygen A and B bands and the other uses the radiance ratios between the absorption and reference channels of the two bands. Third, we applied the algorithms to the simulated EPIC data and to the data from SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) observations. Results show that oxygen A and B bands complement each other: A band is better suited for retrievals over ocean, while B band is better over vegetated land due to a much darker surface. Improvements to the MLER model, including corrections to surface contribution and photon path inside clouds, will also be discussed.

Yang, Yuekui↗
NASA NTRS2011

Aerosol Retrieval and Atmospheric Correction Algorithms for EPIC

EPIC is a multi-spectral imager onboard planned Deep Space Climate ObserVatoRy (DSCOVR) designed for observations of the full illuminated disk of the Earth with high temporal and coarse spatial resolution (10 km) from Lagrangian L1 point. During the course of the day, EPIC will view the same Earth surface area in the full range of solar and view zenith angles at equator with fixed scattering angle near the backscattering direction. This talk will describe a new aerosol retrieval/atmospheric correction algorithm developed for EPIC and tested with EPIC Simulator data. This algorithm uses the time series approach and consists of two stages: the first stage is designed to periodically re-initialize the surface spectral bidirectional reflectance (BRF) on stable low AOD days. Such days can be selected based on the same measured reflectance between the morning and afternoon reciprocal view geometries of EPIC. On the second stage, the algorithm will monitor the diurnal cycle of aerosol optical depth and fine mode fraction based on the known spectral surface BRF. Testing of the developed algorithm with simulated EPIC data over continental USA showed a good accuracy of AOD retrievals (10-20%) except over very bright surfaces.

Wang, Yujie↗
NASA NTRS2012

Tidal Control of Jet Eruptions Observed by Cassini ISS

Observations by Cassini's Imaging Science Subsystem (ISS) of Enceladus' south polar region at high phase angles has revealed jets of material venting into space. Observations by Cassini's Composite Infrared Spectrometer (CIRS) have also shown that the south polar region is anomalously warm with hotspots associated with geological features called the Tiger Stripes. The Tiger Stripes are large rifts near the south pole of Enceladus, which are typically about 130 km in length, 2 km wide, with a trough 500 m deep, and are l1anked on each side by 100m tall ridges. Preliminary triangulation of jets as viewed at different times and with different viewing geometries in Cassini ISS images taken between 2005 and 2007 have constrained the locations of eight major eruptions of material and found all of them associated with the south polar fractures unofficially the 'Tiger Stripes', and found four of them coincident with the hotspots reported in 2006 by CIRS. While published ISS observations of jet activity suggest that individual eruption sites stay active on the timescale of years, any shorter temporal variability (on timescales of an orbital period, or 1.3 Earth days, for example) is more difficult to establish because of the spotty temporal coverage and the difficulty of visually isolating one jet from the forest of many seen in a typical image. Consequently, it is not known whether individual jets are continuously active, randomly active, or if they erupt on a predictable, periodic schedule. One mechanism that may control the timing of eruptions is diurnal tidal stress, which oscillates between compression/tension as well as right and left lateral shear at any given location throughout Enceladus' orbit and may allow the cracks to open and close regularly. We examine the stresses on the Tiger Stripe regions to see how well diurnal tidal stress caused by Enceladus' orbital eccentricity may possibly correlate with and thus control the observed eruptions. We then identify possible mechanisms by which tidal stress can provide access to the surface for volatile material and implications for observed jet activity.

Hurford, T. A.↗
NASA NTRS2011

A Wavelength-Dependent Visible and Infrared Spectrophotometric Function for the Moon based on ROLO Data

The USGS's Robotic Lunar Observatory (ROLO) dedicated ground-based lunar calibration project obtained photometric observations of the Moon over the spectral range attainable from Earth (0.347-2.39 microns) and over solar phase angles of 1.55 deg -97 deg . From these observations, we derived empirical lunar surface solar phase functions for both the highlands and maria that can be used for a wide range of applications. The functions can be used to correct for the effects of viewing geometry to produce lunar mosaics, spectra, and quick-look products for future lunar missions and ground-based observations. Our methodology can be used for a wide range of objects for which multiply scattered radiation is not significant, including all but the very brightest asteroids and moons.

Planetary Sciences↗
NASA NTRS2012

Highlights of TOMS Version 9 Total Ozone Algorithm

The fundamental basis of TOMS total ozone algorithm was developed some 45 years ago by Dave and Mateer. It was designed to estimate total ozone from satellite measurements of the backscattered UV radiances at few discrete wavelengths in the Huggins ozone absorption band (310-340 nm). Over the years, as the need for higher accuracy in measuring total ozone from space has increased, several improvements to the basic algorithms have been made. They include: better correction for the effects of aerosols and clouds, an improved method to account for the variation in shape of ozone profiles with season, latitude, and total ozone, and a multi-wavelength correction for remaining profile shape errors. These improvements have made it possible to retrieve total ozone with just 3 spectral channels of moderate spectral resolution (approx. 1 nm) with accuracy comparable to state-of-the-art spectral fitting algorithms like DOAS that require high spectral resolution measurements at large number of wavelengths. One of the deficiencies of the TOMS algorithm has been that it doesn't provide an error estimate. This is a particular problem in high latitudes when the profile shape errors become significant and vary with latitude, season, total ozone, and instrument viewing geometry. The primary objective of the TOMS V9 algorithm is to account for these effects in estimating the error bars. This is done by a straightforward implementation of the Rodgers optimum estimation method using a priori ozone profiles and their error covariances matrices constructed using Aura MLS and ozonesonde data. The algorithm produces a vertical ozone profile that contains 1-2.5 pieces of information (degrees of freedom of signal) depending upon solar zenith angle (SZA). The profile is integrated to obtain the total column. We provide information that shows the altitude range in which the profile is best determined by the measurements. One can use this information in data assimilation and analysis. A side benefit of this algorithm is that it is considerably simpler than the present algorithm that uses a database of 1512 profiles to retrieve total ozone. These profiles are tedious to construct and modify. Though conceptually similar to the SBUV V8 algorithm that was developed about a decade ago, the SBUV and TOMS V9 algorithms differ in detail. The TOMS algorithm uses 3 wavelengths to retrieve the profile while the SBUV algorithm uses 6-9 wavelengths, so TOMS provides less profile information. However both algorithms have comparable total ozone information and TOMS V9 can be easily adapted to use additional wavelengths from instruments like GOME, OMI and OMPS to provide better profile information at smaller SZAs. The other significant difference between the two algorithms is that while the SBUV algorithm has been optimized for deriving monthly zonal means by making an appropriate choice of the a priori error covariance matrix, the TOMS algorithm has been optimized for tracking short-term variability using month and latitude dependent covariance matrices.

Bhartia, Pawan↗
NASA NTRS2012

Canopy Level Chlorophyll Fluorescence and the PRI in a Cornfield

Two bio-indicators, the Photochemical Reflectance Index (PRI) and solar-induced red and far-red Chlorophyll Fluorescence (SIF), were derived from directional hyperspectral observations and studied in a cornfield on two contrasting days in the growing season. Both red and far-red SIF exhibited higher values on the day when the canopy in the early senescent stage, but only the far-red SIF showed sensitivity to viewing geometry. Consequently, the red/far-red SIF ratio varied greatly among azimuth positions while the largest values were obtained for the "hotspot" at both growth stages. This ratio was lower (approx.0.88 +/- 0.4) in early July than in August when the ratio approached equivalence (near approx.1). In concert, the PRI exhibited stronger responses to both zenith and azimuth angles and different values on the two growth stages. The potential of using these indices to monitor photosynthetic activities needs further investigation

Middleton, Elizabeth M.↗
NASA NTRS2012

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords:

Tan, Bin↗
NASA NTRS2012

Changes in Extratropical Storm Track Cloudiness 1983-2008: Observational Support for a Poleward Shift

Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.

Bender, Frida A-M.↗
NASA NTRS2013

The 2012 Lyrids from Non-traditional Observing Platforms

The NASA Meteoroid Environment Office (MEO) observed meteors during the Lyrid meteor shower peak on 22 April 2012 from three different observing platforms: the ground, a helium-filled balloon, and from the International Space Station (ISS). Even though the Lyrids are not noted for spectacular rates, the combination of New Moon and a favorable viewing geometry from ISS presented a unique opportunity to simultaneously image shower meteors from above the atmosphere and below it. In the end, however, no meteors were observed simultaneously, and it was impossible to identify Lyrids with 100% confidence among the 155 meteors observed from ISS and the 31 observed from the balloon. Still, this exercise proved successful in that meteors could be observed from a simple and inexpensive balloon-based payload and from less-than-optimal cameras on ISS.

Moser, Danielle E.↗
NASA NTRS2014

Stratospheric Ozone Trends and Variability as Seen by SCIAMACHY from 2002 to 2012

Vertical profiles of the rate of linear change (trend) in the altitude range 15-50 km are determined from decadal O3 time series obtained from SCIAMACHY/ENVISAT measurements in limb-viewing geometry. The trends are calculated by using a multivariate linear regression. Seasonal variations, the quasi-biennial oscillation, signatures of the solar cycle and the El Nino-Southern Oscillation are accounted for in the regression. The time range of trend calculation is August 2002-April 2012. A focus for analysis are the zonal bands of 20 deg N - 20 deg S (tropics), 60 - 50 deg N, and 50 - 60 deg S (midlatitudes). In the tropics, positive trends of up to 5% per decade between 20 and 30 km and negative trends of up to 10% per decade between 30 and 38 km are identified. Positive O3 trends of around 5% per decade are found in the upper stratosphere in the tropics and at midlatitudes. Comparisons between SCIAMACHY and EOS MLS show reasonable agreement both in the tropics and at midlatitudes for most altitudes. In the tropics, measurements from OSIRIS/Odin and SHADOZ are also analysed. These yield rates of linear change of O3 similar to those from SCIAMACHY. However, the trends from SCIAMACHY near 34 km in the tropics are larger than MLS and OSIRIS by a factor of around two.

stratosphere↗
NASA NTRS2013

Multitemporal Cross-Calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands

In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

MODIS↗