This PDF file contains the front matter associated with SPIE Proceedings Volume 8153, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

The Atmospheric Infrared Sounder (AIRS) and companion instrument, the Advanced Microwave Sounding Unit (AMSU) on the NASA Earth Observing System Aqua spacecraft are facility instruments designed to support measurements of atmospheric temperature, water vapor and a wide range of atmospheric constituents in support of weather forecasting and scientific research in climate and atmospheric chemistry. This paper is an update to the science highlights from a paper by the authors released last year and also looks back at the lessons learned and future needs of the scientific community. These lessons not only include requirements on the measurements, but scientific shortfalls as well. Results from the NASA Science Community Workshop in IR and MW Sounders relating to AIRS and AMSU requirements and concerns are covered and reflect much of what has been learned and what is needed for future atmospheric sounding from Low Earth Orbit.

High radiometric accuracy under all conditions (such as scene temperature and scan angle) is critical for establishing a climate-quality data record. In this study we compare radiances of both AIRS and IASI using the difference each instrument sees between the brightness temperature at 1231 cm-1 and that at 961 cm^-1. We collected spectra at 17 different sites distributed around the world in tropical, temperate, desert, and arctic climates. For perfectly calibrated instruments, the brightness temperature differences should closely agree, since diurnal differences caused by the differing orbits cancel to first order. We examine observed differences (indicative of calibration artifacts) as functions of scene temperature, time of day, and scan angle. AIRS is a cooled grating array spectrometer with 2378 spectral channels in the wavelength range from 3.7 to 15.4 microns. AIRS began routine operations in September 2002. IASI is a Fourier Transform spectrometer covering the range 3.6 to 15.5 microns in three bands. The spectral resolutions of AIRS and IASI are similar. IASI data have been available since July 2007.

We explore the use cloudy data, including Deep Convective Clouds (DCC) in the tropical oceans for the evaluation of the absolute calibration accuracy and stability of infrared radiometers. For the evaluation of cloudy data we use random nadir samples. We illustrate the method with Atmospheric Infrared Sounder (AIRS) data and data from the Infrared Interferometric Spectrometer (IRIS) in the tropical oceans. AIRS is on the EOS Aqua satellite, which was launched in May 2002 and is expected to continue to produce high quality data until 2015. Two copies of IRIS flew on Nimbus satellites between April 1970 and January 1971. Based on inconsistencies between AIRS and IRIS data, the absolute accuracy of the IRIS data is about 1K, including a significant day/night bias. Part of the observed radiometric bias may have been introduced by quality control, which senses a temperature and spatial uniformity dependent degradation of instrument performance. The observed biases are larger than the 0.5K accuracy claimed in the literature. This absolute calibration uncertainty has to be taken into account in the analysis of changes in the more than 30 year time span between IRIS and AIRS, before they can be attributed to changes in the clouds or the climate. The method described in this paper can be applied retrospectively to any infrared radiometer like HIRS, AVHRR and GOES. It has the capability to exposes instrument artifacts, which are not apparent from the routine quality control of the data.

The Goddard DISC has generated products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. The AIRS Science Team Version-6 retrieval algorithm will be finalized in September 2011. This paper describes some of the significant improvements contained in the Version-6 retrieval algorithm, compared to that used in Version-5, with an emphasis on the improvement of atmospheric temperature profiles, ocean and land surface skin temperatures, and ocean and land surface spectral emissivities. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm^-1 (15.38 μm) - 2665 cm^-1 (3.752 μm). These spectral regions contain significant absorption features from two CO₂ absorption bands, the 15 μm (longwave) CO₂ band, and the 4.3 μm (shortwave) CO₂ absorption band. There are also two atmospheric window regions, the 12 μm - 8 μm (longwave) window, and the 4.17 μm - 3.75 μm (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO₂ absorption regions. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses observations in longwave channels to determine coefficients which generate cloud cleared radiances R_i for all channels, and uses R_i only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used in the AIRS Version-6 Retrieval Algorithm. Results are presented for both daytime and nighttime conditions showing improved Version-6 surface and atmospheric soundings under partial cloud cover.

The MODIS high-gain ocean color bands (B8-B16) are calibrated with its solar diffuser screen (SDS) closed to avoid saturation so that the vignetting function (VF) of SDS is necessary for the calculation of the gain coefficients of these detectors. Since there was no pre-launch system level characterization of the VF, a series of yaw maneuvers were carried out at the mission beginning for both Terra and Aqua to enable its on-orbit characterization. Current VF was derived from the low-gain bands (B1-B7 & B17-B19) data and applied to high-gain ocean color bands calibration, with the assumption that all bands and detectors should share the same VF since it is wavelength independent. As expected, error exists and it was carried over into the calibrated gain coefficients of those bands that use the SDS for their on-orbit calibration. In this paper, an improved VF calculation approach, still using the yaw data as input, is presented. The new approach takes the frame-level mismatch between different detector's footprints on the solar diffuser (SD) into account so that a proper SD image frame adjustment is made when the VF of the low-gain bands is translated into high-gain bands VF. A new set of band-and-detector dependent VFs can be derived using this approach. The implementation of the new VF into calibration of high-gain bands gain coefficient has effectively reduced the undesired seasonal oscillations in its trending from up to Terra's 0.6% and Aqua's 1.0% to nearly 0.2%.

The Moderate-Resolution Imaging Spectroradiometer (MODIS) on NASA's Earth Observing System (EOS) satellite Terra provides global coverage of top-of-atmosphere (TOA) radiances that have been successfully used for terrestrial and atmospheric research. The MODIS Terra ocean color products, however, have been compromised by an inadequate radiometric calibration at the short wavelengths. The Ocean Biology Processing Group (OBPG) at NASA has derived radiometric corrections using ocean color products from the SeaWiFS sensor as truth fields. In the R2010.0 reprocessing, these corrections have been applied to the whole mission life span of 10 years. This paper presents the corrections to the radiometric gains and to the instrument polarization sensitivity, demonstrates the improvement to the Terra ocean color products, and discusses issues that need further investigation. Although the global averages of MODIS Terra ocean color products are now in excellent agreement with those of SeaWiFS and MODIS Aqua, and image quality has been significantly improved, the large corrections applied to the radiometric calibration and polarization sensitivity require additional caution when using the data.

Ocean color climate data records require water-leaving radiances with 5% absolute and 1% relative accuracies as input. Because of the amplification of any sensor calibration errors by the atmospheric correction, the 1% relative accuracy requirement translates into a 0.1% long-term radiometric stability requirement for top-of-theatmosphere radiances. The rigorous on-orbit calibration program developed and implemented for SeaWiFS by the NASA Ocean Biology Processing Group (OBPG) Calibration and Validation Team (CVT) has allowed the CVT to maintain the stability of the radiometric calibration of SeaWiFS at 0.13% or better over the mission. The uncertainties in the resulting calibrated top-of-the-atmosphere (TOA) radiances can be addressed in terms of accuracy (biases in the measurements), precision (scatter in the measurements), and stability (repeatability of the measurements). The calibration biases of lunar observations relative to the USGS RObotic Lunar Observatory (ROLO) photometric model of the Moon are 2-3%. The biases from the vicarious calibration against the Marine Optical Buoy (MOBY) are 1-2%. The precision of the calibration derived from the solar calibration signal-tonoise ratios are 0.16%, from the lunar residuals are 0.13%, and from the vicarious gains are 0.10%. The long-term stability of the TOA radiances, derived from the lunar time series, is 0.13%. The stability of the vicariouslycalibrated TOA radiances, incorporating the uncertainties in the MOBY measurements and the atmospheric correction, is 0.30%. These results allow the OBPG to produce climate data records from the SeaWiFS ocean color data.

The Landsat Data Continuity Mission (LDCM) will provide continuity in the multi-decadal land use/land cover change measurements of the Landsat Program for scientific research. The project office at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is responsible for the development, launch and post launch activation and check out for the Landsat Data Continuity Mission. The LDCM project is currently in its development phase with launch scheduled for December 2012 on an Atlas V launch vehicle provided by the Kennedy Space Center (KSC) from the Vandenberg Air Force Base (VAFB). The project is a partnership between NASA and the Department of the Interior (DOI)/United States Geological Survey (USGS). DOI/USGS is responsible for development of the ground system and will assume responsibility for satellite and ground system operations following the check-out period. This paper will provide an overview and the latest status of the LDCM mission.

The Landsat Data Continuity Mission (LDCM) will have two pushbroom Earth-imaging sensors: the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). The OLI has the reflective 30-meter and panchromatic 15-meter ETM+ bands plus additional 30-meter bands at 443 nm and 1375 nm. The TIRS has two 100-meter bands that spectrally split the ETM+ thermal band. OLI has completed performance testing and is scheduled for a late summer 2011 delivery to the spacecraft. OLI radiometric performance has shown that polarization sensitivity is 1-2%; Signal-to-Noise Ratios at signal levels about 5-10% of full scale are between 6-12 times better than ETM+, e.g., 250 versus 30; radiometric stability over 16 days is better than 0.5% (2-sigma); coherent noise is not visible; detector operability is 100% (no dead or inoperable detectors), absolute radiance calibration uncertainty is ~4%, reflectance calibration uncertainty is ~2.5% and detector-to-detector radiometric uniformity is generally better than 0.5%. TIRS completed initial performance testing in March 2011 and in August 2011 will be entering its primary thermal vacuum performance testing with the integrated instrument. At this point indications are that the TIRS instrument will have noise levels roughly ¼ of the ETM+ bands and detector-to-detector radiometric uniformity of better than 0.5%.

The Landsat Data Continuity Mission (LDCM) is planning to launch the Landsat 8 satellite in December 2012, which continues an uninterrupted record of consistently calibrated globally acquired multispectral images of the Earth started in 1972. The satellite will carry two imaging sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will provide visible, near-infrared and short-wave infrared data in nine spectral bands while the TIRS will acquire thermal infrared data in two bands. Both sensors have a pushbroom design and consequently, each has a large number of detectors to be characterized. Image and calibration data downlinked from the satellite will be processed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using the Landsat 8 Image Assessment System (IAS), a component of the Ground System. In addition to extracting statistics from all Earth images acquired, the IAS will process and trend results from analysis of special calibration acquisitions, such as solar diffuser, lunar, shutter, night, lamp and blackbody data, and preselected calibration sites. The trended data will be systematically processed and analyzed, and calibration and characterization parameters will be updated using both automatic and customized manual tools. This paper describes the analysis tools and the system developed to monitor and characterize on-orbit performance and calibrate the Landsat 8 sensors and image data products.

The LDCM will carry two new pushbroom imagers. The nine band Operational Land Imager (OLI) and the two band Thermal Infrared Sensor (TIRS) represent significant changes in Landsat Sensor Technology, as does the plan to generate a common data product from two sensors (registered 11 band data). This effort is designed to generate synthetic images that will predict the LDCM performance pre-launch, will support trouble shooting of instrument behavior during initialization and operation, and perhaps most importantly, can support Landsat remote sensing science activities throughout the mission. This paper reports on initial results of efforts to simulate all of the phenomena that can lead to non-uniformity variations in an image. This includes detector-to-detector and array-to-array non-uniformities due to variations in relative spectral response (RSR), gain, bias, and non-linearities. The overall approach involves modifying the DIRSIG image simulation model to allow detailed modeling of the Landsat orbit and LDCM sensors parameters and generation of test scenes to allow full end-to-end image simulations incorporating illumination, atmospheric, sensor geometry, and radiometry effects as a function of time, meteorology, spectral range from the visible through the long wave infrared, and spatial effects. The results reported in this paper emphasize the modeling and initial demonstration of the non-uniformity phenomenology.

The Landsat Data Continuity Mission (LDCM) will carry the Operational Land Imager (OLI) as one of its payloads. This instrument is a derivative of the Advanced Land Imager (ALI), flown on Earth Observing-1 (EO1) though it's mission is to continue the operational land imaging of the Landsat program. The OLI follows the highly successful Landsat-5 and Landsat-7 missions in continuing to populate an archive of earth images that dates back to 1972. The OLI has significant changes from the Landsat Thematic Mapper instruments, given that is the first pushbroom instrument in the program. However, it is intended to be a continuity mission, so the spatial coverage and spectral bands are similar. The suite of OLI's multispectral bands cover the same bandpasses but the panchromatic band is narrower than that of the ETM+. The OLI also has a shorter wavelength blue band for better resolution of coastal waters and a new band to aid in the detection of Cirrus clouds in the atmosphere. The thermal bands traditionally carried on the TM instruments have been moved to a separate instrument, also onboard the LDCM spacecraft. With the pushbroom design, each OLI multi-spectral band consists of nearly 7000 detectors. The OLI underwent prelaunch to verify a host of requirements on it's spectral performance, where was characterized at three different points during development. This paper will cover the results of the tests that attempt to validate the spectral uniformity requirements, including in-band response, out-of-band response, and spectral uniformity across the focal plane.

The Operational Land Imager (OLI) is a pushbroom sensor that will be a part of the Landsat Data Continuity Mission (LDCM). This instrument is the latest in the line of Landsat imagers, and will continue to expand the archive of calibrated earth imagery. An important step in producing a calibrated image from instrument data is accurately accounting for the bias of the imaging detectors. Bias variability is one factor that contributes to error in bias estimation for OLI. Typically, the bias is simply estimated by averaging dark data on a per-detector basis. However, data acquired during OLI pre-launch testing exhibited bias variation that correlated well with the variation in concurrently collected data from a special set of detectors on the focal plane. These detectors are sensitive to certain electronic effects but not directly to incoming electromagnetic radiation. A method of using data from these special detectors to estimate the bias of the imaging detectors was developed, but found not to be beneficial at typical radiance levels as the detectors respond slightly when the focal plane is illuminated. In addition to bias variability, a systematic bias error is introduced by the truncation performed by the spacecraft of the 14-bit instrument data to 12-bit integers. This systematic error can be estimated and removed on average, but the per pixel quantization error remains. This paper describes the variability of the bias, the effectiveness of a new approach to estimate and compensate for it, as well as the errors due to truncation and how they are reduced.

Verification of the Visible Infrared Imager Radiometer Suite (VIIRS) End-to-End (E2E) sensor calibration is highly recommended before launch, to identify any anomalies and to improve our understanding of the sensor onorbit calibration performance. E2E testing of the Reflective Solar Bands (RSB) calibration cycle was performed pre-launch for the VIIRS Flight 1 (F1) sensor at the Ball Aerospace facility in Boulder CO in March 2010. VIIRS reflective band calibration cycle is very similar to heritage sensor MODIS in that solar illumination, via a diffuser, is used to correct for temporal variations in the instrument responsivity. Monochromatic light from the NIST T-SIRCUS (Traveling Spectral Irradiance and Radiance Responsivity Calibrations using Uniform Sources) was used to illuminate both the Earth View (EV), via an integrating sphere, and the Solar Diffuser (SD) view, through a collimator. The collimator illumination was cycled through a series of angles intended to simulate the range of possible angles for which solar radiation will be incident on the solar attenuation screen on-orbit. Ideally, the measured instrument responsivity (defined here as the ratio of the detector response to the at-sensor radiance) should be the same whether the EV or SD view is illuminated. The ratio of the measured responsivities was determined at each collimator angle and wavelength. In addition, the Solar Diffuser Stability Monitor (SDSM), a ratioing radiometer designed to track the temporal variation in the SD Bidirectional Reflectance Factor (BRF) by direct comparison to solar radiation, was illuminated by the collimator. The measured SDSM ratio was compared to the predicted ratio. An uncertainty analysis was also performed on both the SD and SDSM calibrations.

Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager Radiometer Suite (VIIRS) assume that the sensors' radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1 (FU1) (Butler, J., Xiong, X., Oudrari, H., Pan, C., and Gleason, J., "NASA Calibration and Characterization in the NPOESS Preparatory Project (NPP)", IGARSS, July 12-17, 2009, Cape Town, South Africa.), the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor's digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the quadratic model. We show that using the inadequate quadratic model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.

The VIIRS Flight 1 (F1) instrument completed sensor level testing, including relative spectral response (RSR) characterization in 2009 and is moving forward towards a launch on the NPP platform late in 2011. As part of its mandate to produce analyses of F1 performance essentials, the VIIRS Government Team, consisting of NASA, Aerospace Corp., and MIT/Lincoln Lab elements, has produced an independent (from that of industry) analysis of F1 RSR. The test data used to derive RSR for all VIIRS spectral bands was collected in the TVAC environment using the Spectral Measurement Assembly (SpMA), a dual monochromator system with tungsten and ceramic glow bar sources. These spectrally contiguous measurements were analyzed by the Government Team to produce a complete in-band + out-of-band RSR for 21 of the 22 VIIRS bands (exception of the Day-Night Band). The analysis shows that VIIRS RSR was well measured in the pre-launch test program for all bands, although the measurement noise floor is high on the thermal imager band I5. The RSR contain expected detector to detector variation resulting from the VIIRS non-telecentric optical design, and out-of-band features are present in some bands; non-compliances on the integrated out-of-band spectral performance metric are noted in M15 and M16A,B bands and also for several VisNIR bands, though the VisNIR non-compliances were expected due to known scattering in the VisNIR integrated filter assembly. The Government Team "best" RSR have been released into the public domain for use by the science community in preparation for the post-launch era of VIIRS F1.

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key sensor carried on the NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project (NPP) mission [1] (http://jointmission.gsfc.nasa.gov/viirs.html), and is scheduled to launch in October 2011. VIIRS sensor design draws on heritage instruments including AVHRR, OLS, MODIS, and SeaWiFS. It has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background subtraction. These on-board calibrators are located at fixed scan angles. The VIIRS response versus scan angle (RVS) was characterized prelaunch in lab ambient conditions and will be used on-orbit to characterize the response for all scan angles relative to the calibrator scan angle (SD for RSB and blackbody for TEB). Since the RVS is vitally important to the quality of calibrated radiance products, several independent studies were performed and their results were compared and validated. This document provides RVS results from three groups: the NPP Instrument Calibration Support Team (NICST), Raytheon, and the Aerospace Corporation. A comparison of the RVS results obtained using a 2nd order polynomial fit to measurement data is conducted for each band, detector, and half angle mirror (HAM) side. The associated RVS fitting residuals are examined and compared with the relative differences in RVS found between independent studies. Results show that the agreement is within 0.1% and comparable with fitting residuals for all bands except for RSB band M9, where a difference of 0.2% was observed. Band M9 is highly sensitive to the atmospheric water vapor variations during the sensor ambient testing at Raytheon, and its correction might be a contributor to the observed RVS uncertainty differences. In general, NICST results have shown slightly larger RSB RVS uncertainties but still well within the 0.3% total uncertainty allowed for the RVS characterization defined in the Performance Verification Plan.

For several years, the NASA/Goddard Space Flight Center (GSFC) NPP VIIRS Ocean Science Team (VOST) provided substantial scientific input to the NPP project regarding the use of Visible Infrared Imaging Radiometer Suite (VIIRS) to create science quality ocean color data products. This work has culminated into an assessment of the NPP project and the VIIRS instrument's capability to produce science quality Ocean Color data products. The VOST concluded that many characteristics were similar to earlier instruments, including SeaWiFS or MODIS Aqua. Though instrument performance and calibration risks do exist, it was concluded that programmatic and algorithm issues dominate concerns.

The new NASA Enhanced MODIS Airborne Simulator (eMAS) is based on the legacy MAS system, which has been used extensively in support of the NASA Earth Observing System program since 1995. eMAS consists of two separate instruments designed to fly together on the NASA ER-2 and Global Hawk high altitude aircraft. The eMAS-IR instrument is an upgraded version of the legacy MAS line-scanning spectrometer, with 38 spectral bands in the wavelength range from 0.47 to 14.1 μm. The original LN2-cooled MAS MWIR and LWIR spectrometers are replaced with a single vacuum-sealed, Stirling-cooled assembly, having a single MWIR and twelve LWIR bands. This spectrometer module contains a cold optical bench where both dispersive optics and detector arrays are maintained at cryogenic temperatures to reduce infrared background noise, and ensure spectral stability during high altitude airborne operations. The EMAS-HS instrument is a stand-alone push-broom imaging spectrometer, with 202 contiguous spectral bands in the wavelength range from 0.38 to 2.40 μm. It consists of two Offner spectrometers, mated to a 4-mirror anastigmatic telescope. The system has a single slit, and uses a dichroic beam-splitter to divide the incoming energy between VNIR and SWIR focal plane arrays. It will be synchronized and bore-sighted with the IR line-scanner, and includes an active source for monitoring calibration stability. eMAS is intended to support future satellite missions including the Hyperspectral Infrared Imager ( HyspIRI,) the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP,) and the follow-on Joint Polar Satellite System (JPSS.)

Built by students and faculty at the University of North Dakota (UND), the International Space Station (ISS) Agricultural Camera (ISSAC^TM) is a multi-spectral Earth-imaging sensor currently onboard the ISS. Capabilities include three spectral bands (green, red, near-infrared), medium (~20m) spatial resolution, and off-nadir pointing (+/-30 degrees) for episodic rapid-response imaging. We describe the low-cost electro-optical design approach, which utilizes a studentcentered design and operations team and relies on modified commercial components operating within a passive vibration isolation mounting, installed inside the Window Observational Research Facility, viewing the Earth through the US Laboratory Science Window. Interfaces, safety, and other factors unique to the human-rated operational environment of the ISS are outlined. Pre-launch sensor characterization results, including spatial distortion and radiometric measurements, indicate Earth remote sensing using such a sensor is a viable approach for demonstrative operational missions. An element of the ISS National Laboratory, ISSAC was launched on HTV-2 to the ISS in January 2011. Initial operations began in June 2011. Methods of sensor operations are described, using a student staff working within the ISS operational environment. Some initial early imaging results are shown.

In partnership with the European Commission and in the frame of the Global Monitoring for Environment and Security (GMES) program, the European Space Agency (ESA) is developing the Sentinel-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a satellites constellation deployed in polar sun-synchronous orbit. While ensuring data continuity of former SPOT and LANDSAT multi-spectral missions, Sentinel-2 will also offer a wide range of improvements such as a global coverage, a large field of view (290km), a high revisit capability (5 days with two satellites), a high resolution (10m, 20m and 60m) and multi-spectral imagery (13 spectral bands). In this context, the Centre National d'Etudes Spatiales (CNES) supports ESA to define the system image products and to prototype the relevant image processing techniques. First, this paper presents the Sentinel-2 system and the image products that will be delivered: starting from raw decompressed images up to accurate ortho-images in Top of Atmosphere reflectances. The stringent image quality requirements are also described, in particular the very accurate target geo-location. Then, the prototyped image processing techniques will be addressed. Both radiometric and geometric processing will be described with a special focus on the automatic enhancement of the geometric physical model involving a global set of reference data. Finally, the very promising results obtained by the prototype will be presented and discussed. The radiometric and geometric performances will be provided as well as the associated computing time estimation on the target platform.

The goals of the Climate Monitoring CubeSat Mission (CM²) are to accelerate climate projection by obtaining global temperature, tidal and wave measurements with a simple CubeSat-based imaging spectrograph; and to demonstrate how a high-resolution imaging spectrograph can be deployed on a CubeSat satellite. In the middle atmosphere (50 - 100 km), beyond the reach of balloons or satellites, thermal signatures of CO₂ radiation and wave activity have been largely missing from climate model inputs. This paper outlines an instrument to advance the state of the art in atmospheric climate projection by providing critical global measurements of middle-atmosphere temperatures and waves with a CubeSatscale imaging spectrograph. The CM² will remotely sense middle-atmosphere temperatures and waves at ~90 km by analyzing spectra of intrinsically bright molecular oxygen emissions at near-infrared wavelengths in the O2 atmospheric band. The core instrument will be a miniaturized imaging spectrograph based on a monolithic spatial heterodyne spectrometer (SHS). This spectrograph will have sensitivity and spectral resolution to extract temperatures with 10° K precision and waves with 4 km scale resolution along a ~200 km cross-track swath. The SHS is significantly more robust than conventional interferometers, and thus better suited to space-based observation. Acquiring high-resolution middle-atmosphere temperature, tidal, and wave data on a daily, global basis will significantly improve climate models, and will help assess long-term greenhouse gas mitigation policy impact on upper-atmosphere thermal signatures. The CM² program will also establish the efficacy of highresolution CubeSat-based broadband (near-IR to UV) spectroscopy for application to other atmospheric research missions.

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe highaccuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. The CLARREO Project will implement a spaceborne earth observation mission designed to provide rigorous SI-traceable observations (i.e., radiance, reflectance, and refractivity) that are sensitive to a wide range of key decadal change variables. The instrument suite includes emitted infrared spectrometers, global navigation receivers for radio occultation, and reflected solar spectrometers. The measurements will be acquired for a period of five years and will enable follow-on missions to extend the climate record over the decades needed to understand climate change. This work describes a preliminary error budget for the RS sensor. The RS sensor will retrieve at-sensor reflectance over the spectral range from 320 to 2300 nm with 500-m GIFOV and a 100-km swath width. The current design is based on an Offner spectrometer with two separate focal planes each with its own entrance aperture and grating covering spectral ranges of 320-640, 600-2300 nm. Reflectance is obtained from the ratio of measurements of radiance while viewing the earth's surface to measurements of irradiance while viewing the sun. The requirement for the RS instrument is that the reflectance must be traceable to SI standards at an absolute uncertainty <0.3%. The calibration approach to achieve the ambitious 0.3% absolute calibration uncertainty is predicated on a reliance on heritage hardware, reduction of sensor complexity, and adherence to detector-based calibration standards. The design above has been used to develop a preliminary error budget that meets the 0.3% absolute requirement. Key components in the error budget are geometry differences between the solar and earth views, knowledge of attenuator behavior when viewing the sun, and sensor behavior such as detector linearity and noise behavior. Methods for demonstrating this error budget are also presented.

The Ocean Radiometer for Carbon Assessment (ORCA) is a new design for the next generation remote sensing of oceans biology and biogeochemistry satellite. ORCA is configured to meet the requirements of the Decadal Survey recommended Aerosol, Cloud, and Ecology (ACE ), the Ocean Ecosystem (OES) radiometer and the Pre-ACE climate data continuity mission (PACE). Under the auspices of a 2007 grant from NASA's Research Opportunity in Space and Earth Science (ROSES) and the Instrument Incubator Program (IIP) , a team at the Goddard Space Flight Center (GSFC) has been working on a functional prototype of a hyperspectral imager with flightlike optics and scan mechanisms. This paper discusses the requirements and optomechanical design of this prototype.

The Ocean Radiometer for Carbon Assessment (ORCA) is a new design for the next generation remote sensing of ocean biology and biogeochemistry. ORCA is configured to meet all the measurement requirements of the Decadal Survey Aerosol, Cloud, and Ecology (ACE ), the Ocean Ecosystem (OES) radiometer and the Pre-ACE climate data continuity mission (PACE). Under the auspices of a 2007 grant from NASA Research Opportunity in Space and Earth Science (ROSES) and the Instrument Incubator Program (IIP) , a team at the Goddard Space Flight Center (GSFC) has been working on a functional prototype with flightlike fore and aft optics and scan mechanisms. As part of the development efforts to bring ORCA closer to a flight configuration, we have conducted component-level optical testing using standard spectrophometers and system-level characterizations using nonflight commercial off-the-shelf (COTS) focal plane array detectors. Although these arrays would not be able to handle flight data rates, they are adequate for optical alignment and performance testing. The purpose of this presentation is to describe the results of this testing performed at GSFC and the National Institute of Standards and Technology (NIST) at the component and system level. Specifically, we show results for ORCA's spectral calibration ranging from the near UV, visible, and near-infrared spectral regions.

The Ocean Radiometer for Carbon Assessment (ORCA), currently being developed at Goddard, is a hyperspectral instrument with a spectral range extending from 350nm to 880nm in the UV and visible wavelength. Its radiometric measurement accuracy will depend, in part, on the extent to which it is insensitive to linearly polarized light. A wedge type depolarizer is used to reduce ORCA's polarization sensitivity over its entire spectral range. The choice for this approach is driven by the large spectral range and to a certain extent is also influenced by the currently orbiting SeaWifs instrument's use of a wedge depolarizer and its low polarization sensitivity. The wedge depolarizer's design, its modeled and measured depolarization characteristics are presented.

Emerging instrumental requirements for remotely sensing tropospheric trace species have led to a rethinking by some of the paradigm for Système International d'Unités (SI) traceability of the spectral irradiance and radiance radiometric calibrations to spectral albedo (sr^-1) which is not a SI unit. In the solar reflective wavelength region the spectral albedo calibrations are tied often to either the spectral albedo of a solar diffuser or the Moon. This new type of Mie scattering diffuser (MSD) is capable of withstanding high temperatures, and is more Lambertian than Spectralon^TM. It has the potential of covering the entire solar reflective wavelength region. Laboratory measurements have shown that the specular reflectance component is negligible, and indicate that internal absorption by multiple scattering is small. This MSD, a true volume diffuser, exhibits a high degree of radiometric stability which suggests that measurements at the National Institute of Standards and Technology (NIST) could provide a spectral albedo standard. Measurements are currently in progress of its radiometric stability under a simulated space environment of high energy ionizing and ultraviolet (UV) solar radiation for its eventual use in space as a solar diffuser.

Integrating spheres for optical calibration of remote sensing cameras have traditionally been made with Quartz Tungsten Halogen (QTH) lamps because of their stability. However, QTH lamps have the spectrum of a blackbody at approximately 3000K, while remote sensing cameras are designed to view a sun-illuminated scene. This presents a severe significant mismatch in the blue end of the spectrum. Attempts to compensate for this spectral mismatch have primarily used Xenon lamps to augment the QTH lamps. However, Xenon lamps suffer from temporal instability that is not desirable in many applications. This paper investigates the possibility of using RF-excited plasma lamps to augment QTH lamps. These plasma lamps have a somewhat smoother spectrum than Xenon. Like Xenon, they have more fluctuation than QTH lamps, but the fluctuations are slower and may be able to be tracked in an actual OGSE light source. The paper presents measurements of spectra and stability. The spectrum is measured from 320 nm to 2500 nm and the temporal stability from DC to 10 MHz. The RF-excited plasma lamps are quite small, less than 10mm in diameter and about 15 mm in length. This makes them suitable for designing reasonably sized reflective optics for directing their light into a small port on an integrating sphere. The concludes with a roadmap for further testing.

The Scanning Microwave Limb Sounder (SMLS) is a space-borne heterodyne radiometer which will measure pressure, temperature and atmospheric constituents from thermal emission in [180,680] GHz. SMLS, planned for the NRC Decadal Survey's Global Atmospheric Composition Mission, uses a novel toric Cassegrain antenna to perform both elevation and azimuth scanning. These will provide better horizontal and temporal resolution and coverage than were possible with elevation-only scanning in the two previous MLS satellite instruments. SMLS is diffraction-limited in the vertical plane but highly astigmatic in the horizontal (beam aspect ratio ~1:20). Nadir symmetry ensures that beam shape is nearly invariant over ±65° azimuth. A low-noise receiver's FOV will be swept over the reflector system by a small azimuth-scanning mirror. We describe the fabrication and thermalstability test of a composite demonstration primary reflector, having full 4m height and 1/3 the width planned for flight. Using finite-element models of reflectors6 and structure, we evaluate thermal deformations and optical performance for 4 orbital environments and isothermal soak. We compare deformations with photogrammetric measurements made during soak tests in a chamber. The test temperature range exceeds predicted orbital ranges by large factors, implying in-orbit thermal stability of 0.21 micron rms/°C; this meets SMLS requirements.

Airborne remote sensing measurements provide the capability to quantitatively measure biochemical and biophysical properties of vegetation at regional scales, therefore complementing surface and satellite measurements. The National Ecological Observatory Network (NEON) will build three airborne systems to allow for routine coverage of NEON sites (60 sites nationally) and the capacity to respond to investigator requests for specific projects. Each airborne system will consist of an imaging spectrometer, waveform lidar and high-resolution digital camera. Remote sensing data gathered with this instrumentation needs to be quantitative and accurate in order to derive meaningful information about ecosystem properties and processes. Also, comprehensive and long-term ecological studies require these data to be comparable over time, between coexisting sensors and between generations of follow-on sensors. NEON's calibration plan for the airborne instrument suite relies on intensive laboratory, on-board, ground-based characterization as well as inter-sensor comparisons. As part of these efforts, NEON organized a pathfinder mission in September 2010 to test prototype techniques and procedures for field sampling and sensor validation. Imaging spectroscopy data from AVIRIS and waveform lidar data were acquired in addition to ecological field sampling at the Ordway-Swisher Biological Station near Gainesville, Florida. This paper presents NEON's capabilities for validation of at-sensor radiance of airborne and space-based sensors and shows results from the September 2010 pathfinder mission.

The Remote Sensing Group (RSG) at the University of Arizona is currently refining an automated system for the absolute radiometric calibration of earth-observing sensors. The Radiometric Calibration Test Site (RadCaTS) relies on semi-permanent instrumentation at the Railroad Valley (RRV) test site to collect data from which surface reflectance and an atmospheric characterization is determined. Multispectral surface reflectance is determined from calibrated ground viewing radiometers and assimilated to determine the hyperspectral reflectance used in radiative transfer calculations. The reflectance retrieval algorithm relies on an accurate determination of the diffuse sky irradiance for the time of interest. Currently, diffuse sky irradiance is modeled using the atmospheric characterization as input into MODTRAN5. This work investigates the accuracy of the diffuse sky modeling by comparing modeled results to measurements made at the test site. Diffuse sky irradiance from several alternative methods are also presented. Surface reflectance is computed and compared to in-situ measurements taken with a portable spectoradiometer.

La Crau test site is used by CNES since 1987 for vicarious calibration of SPOT cameras. The former calibration activities were conducted during field campaigns devoted to the characterization of the atmosphere and the site reflectances. Since 1997, au automatic photometric station (ROSAS) was set up on the site on a 10m height pole. This station measures at different wavelengths, the solar extinction and the sky radiances to fully characterize the optical properties of the atmosphere. It also measures the upwelling radiance over the ground to fully characterize the surface reflectance properties. The photometer samples the spectrum from 380nm to 1600nm with 9 narrow bands. Every non cloudy days the photometer automatically and sequentially performs its measurements. Data are transmitted by GSM (Global System for Mobile communications) to CNES and processed. The photometer is calibrated in situ over the sun for irradiance and cross-band calibration, and over the Rayleigh scattering for the short wavelengths radiance calibration. The data are processed by an operational software which calibrates the photometer, estimates the atmosphere properties, computes the bidirectional reflectance distribution function of the site, then simulates the top of atmosphere radiance seen by any sensor over-passing the site and calibrates it. This paper describes the instrument, its measurement protocol and its calibration principle. Calibration results are discussed and compared to laboratory calibration. It details the surface reflectance characterization and presents SPOT4 calibration results deduced from the estimated TOA radiance. The results are compared to the official calibration.

The Clouds and Earth Radiant Energy System (CERES) Flight Model FM-1 and FM-2 sensors aboard the Terra and the FM-3 and FM-4 sensors aboard the Aqua spacecraft have provided the first decade of observations of quality suitable for the Earth Radiation Climate Data Record (CDR). To assure continuity of this CDR the CERES FM-5 sensor will fly on the NPP spacecraft, scheduled for launch in October 2011. The methods for calibrating the FM-5 in orbit and validating the results so as to maintain the required level of accuracy and traceability are described. These methods include use of on-board calibration sources and a number of tests devised for FM-1 through -4. In addition, comparisons of measurement by the newly calibrated FM-5 with (nearly) coincident measurements by the older CERES instruments on Terra and Aqua provide an opportunity to investigate the effects on the instruments and the on-board calibration devices of a decade of operating in space.

Clouds and the Earth's Radiant Energy System (CERES) instrument was designed to measure broadband radiances in reflected shortwave and emitted outgoing longwave energy. The 3-sensor CERES instrument measure radiances in 0.3 to 5.0 micron region with Shortwave sensor, 0.3 to >100 microns with Total sensor and 8 to 12 micron region with Window sensor. Flight Model 5 (FM5), the sixth of the CERES instruments is scheduled to launch aboard the NPP spacecraft on October 2011. An accurate determination of the radiometric gains and spectral responsivity of CERES FM5 sensors was accomplished through rigorous calibrations at Northrop Grumman Aerospace Systems' (NGAS) Radiometric Calibration Facility (RCF). The longwave calibration of the total and window sensors are achieved using the Narrow Field-of-View Blackbody (NFBB) source which is tied to International Scale of 1990 (ITS '90). A Shortwave Reference Source (SWRS) along with the Transfer Active Cavity radiometer (TACR) which acts as the transfer standard of NFBB source, is used to determine the radiometric responsivity and spectral response estimates of the SW sensor and shortwave portion of the Total sensor. The spectral responsivity in longwave region is determined using a Fourier Transform Spectrometer (FTS) system. CERES instrument also perform calibrations using on-board sources during pre-launch testing which serve as a traceability standard to carry the ground determined sensor radiometric gains to orbit. This paper covers the calibration philosophy and the results from ground calibration testing of FM5 sensors conducted in 2008. The sensor radiometric gain responses calculated using primary sources and performance of the sensors using on-board sources will be discussed.

The Clouds and Earth's Radiant Energy System (CERES) mission currently employs four instruments onboard two spacecraft to measure the earth's reflected shortwave energy and the earth emitted thermal energy that represents two components of the earth's energy budget. These measurements are made through three sensors that measure different spectral channels- a shortwave channel that measures the 0.3 to 5 microns wavelength band, a total channel that measures all the incident energy (0.3 to ~200 microns) and a window channel that measures the 8 to 12 micron wavelength band. The radiances measured in each channel (filtered radiances) are used to estimate the incident (unfiltered) shortwave and longwave radiances using knowledge of the response functions of each of the measurement channels as well as theoretical knowledge of the energy spectrum of the earth scene being measured. For longer wavelengths particularly in the far infrared, both the earth scene spectra as well as the instrument spectral response functions are not very well characterized because of the difficulties in obtaining models for the earth scene spectra as well as the limitations in the capabilities to measure the spectral responses over a very large spectral range. This results in errors in obtaining estimates of the unfiltered radiances. This paper will focus on studying the sensitivity of the CERES instrument to these inaccuracies and its impact on the errors in estimation. In addition, those spectral regions in the longwave infrared where the CERES instruments are most sensitive will be identified.

The Clouds and Earth's Radiant Energy System (CERES) project has greatly improved the understanding of the role of clouds and energy cycles in global climate studies. CERES flux and cloud properties rely on not only CERES broadband fluxes and MODIS cloud properties but also on operational geostationary (GOES, METEOSAT, MTSAT) derived fluxes and clouds, which are acquired between CERES measurements such to properly account for the diurnal cycle. The high quality of the CERES products is dependent on a consistent radiometric calibration of the un-calibrated geostationary visible sensors and MODIS. To achieve this consistency, the calibration of a reference sensor must be transferred to the other instruments. Historically, Terra-MODIS and Aqua-MODIS, both of which employ solar diffusers, have been regarded as having a well-calibrated visible channel (650 nm). Recent analysis has revealed the Aqua-MODIS instrument to be more stable than the MODIS instrument onboard the Terra satellite. For this reason, Aqua-MODIS has been chosen as the reference sensor whereas Terra-MODIS adjustments can be used to put the instrument on the same radiometric scale as Aqua-MODIS. The ray-matching technique is used to transfer the calibration of the well-calibrated MODIS instrument to the un-calibrated GEO sensors. Additionally, empirically derived models for pseudo-invariant test sites and deep convective clouds (DCC) have been developed and applied for monitoring and validating the GEO calibration. Multiple pseudo-invariant test site and DCC absolute calibration methodologies are compared. Latest results show that GOES-13 response has drifted 5-6 percent in its first 15 months of operation. The Aqua/Terra-MODIS crosscalibration trends are in agreement with calibration trends obtained from pseudo-invariant test sites and DCC. These results are in preparation for CERES Edition4 products, which will include updated geostationary calibration coefficients and cloud retrieval improvements.

Nearly 30 years of continuous observations made by a series of AVHRR sensors have offered a great potential for studies of global environment and climate change. In order to achieve this objective, each sensor must be accurately and consistently calibrated. This is not an easy task as there is no onboard calibrator for AVHRR reflective solar channels and vicarious calibration often needs to accumulate enough observations to derive useful trends. In this study, we select CEOS (the Committee on Earth Observation Satellites) endorsed Cal/Val desert sites to track the long-term stability of reflective solar channels of NOAA-17 AVHRR (launched on June 24, 2002) and re-calibrate them using well-calibrated MODIS as reference. A site-specific Bi-directional Reflectance Distribution Function (BRDF) developed based on observations made by MODIS is used to normalize AVHRR observed reflectances. Impacts of atmospheric water vapor on AVHRR to MODIS reflectance ratios are corrected with measured total water vapor contents derived from the split-window temperature difference technique. Finally, MODIS-based AVHRR calibration coefficients on top of the AVHRR prelaunch values are provided in time-dependent look-up tables (LUT). A further validation is performed using MODIS and AVHRR observations obtained over Antarctic Dome C site where impact due to atmospheric water vapor is negligibly small.

The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) and theModerate Resolution Imaging Spectroradiometer (MODIS) onboard Terra satellite, which have different spatial resolution, can observe the earth surface simultaneously. Both of these sensors have been operated more than 10 years, and it is very useful for cross-calibration because of their simultaneous observations mostly without BRDF effect. On the other hand, the CEOS IVOS group arranges the pseudo-invariant standard test sites for cross-calibration, which are able to evaluate the long-term stability among multiple sensors. This paper shows the TOA reflectance comparison between ASTER and MODIS sensor over the CEOS pseudo-invariant standard test sites.

Meteorological sounding data provided by atmospheric imaging sounders have applications in weather forecasting, atmospheric chemistry, and climate monitoring. Realistic scenes for these instruments vary in both spatial and spectral content and such variations can impact the radiometric performance of these instruments. As sounders are developed to provide climate records with demanding long-term radiometric accuracy requirements, it becomes increasingly important to understand the effect of scene variations on the performance of these instruments. We have examined the noise performance and radiometric accuracy of two geostationary sounder architectures in cloudy scenes: a Fourier transform spectrometer (FTS) and a dispersive spectrometer. Factors such as stray light, ghosting, scattering, and line-ofsight jitter in the presence of scene inhomogeneities are considered. For each sounder architecture, quantitative estimates of the radiometric errors associated with sounding in cloudy scenes are made. We find that in a dispersive system the dominant error in a cloudy scene originates from ghosting within the instrument, while in an FTS the dominant error originates from scene modulation created by line-of-sight jitter in a partially cloudy scene coupling into signal modulation over the scale of the changing optical path length of the interferometer. In this paper we describe the assumptions made and the modeling performed. We also describe how each factor influences the radiometric performance for that architecture.

The Global Space-based Inter-Calibration System (GSICS) geostationary (GEO) vs. low earth orbit (LEO) inter-calibration correction products have been routinely generated for years at NOAA to improve and harmonize the data quality of the operational GOES satellite for a better global weather monitoring, prediction and climate change studies. In this study, the collocated GOES-13 and GOES-15 Imager infrared (IR) data are used to validate the GSICS GEO-LEO Imager inter-calibration correction products. To compensate the impact of difference in the spectral response function (SRF) on the GSICS corrected GEO radiance, two radiative transfer models (RTM) with different atmospheric profiles are used to simulate the relations between the two GEO radiance values. The results of GEO-GEO inter-calibration shows that the mean Tb difference between GOES-13 and GOES-15 is less than 0.2K(Ch2), 0.65K(Ch3), 0.08K(Ch4) and 0.35K(Ch6). The two RTM models with different atmospheric profiles have significantly different impacts on the Tb difference at the two absorptive channels, Ch3 and Ch6, indicating that the impact of different optical path is not well addressed in this study. Future study should apply the double difference using the RTM as transfer to compensate for the SRF and viewing/optical path difference at each collocated pixel.

The 30 years of observations from High-Resolution Infrared Radiation Sounder (HIRS) aboard NOAA series of satellites have been widely used in numerical weather prediction and climate studies. However, there are significant discrepancies in the HIRS measurements between different satellites. The HIRS data from NOAA satellites series need to be recalibrated to establish an accurate and consistent temporal series before it can be used for climate changing detection. To ensure the consistency and reduce the uncertainties for the climate studies of clouds using NOAA HIRS data, this study explores the spectral calibration of longwave CO2 channels for the HIRS on board of NOAA series of satellites using the hyper-spectral IASI radiance measurements from MetOp satellite as reference. The HIRS measurements from each NOAA satellite are compared with the recalibrated HIRS measurements from the successive satellite at Simultaneous-Nadir-Overpass (SNO) locations. For the satellites after NOAA 15, the comparison between the HIRS measurements and the matched IASI measurements at SNO locations is also displayed. A preliminary analysis of the intersatellite biases is performed to quantify the spectral causes of the biases for HIRS channels 4. By removing these biases, our method shows the potential to recalibrate the HIRS on board of the NOAA series of satellites and make the HIRS measurements traceable to the IASI measurements with improved spectral calibration.

The ABI on GOES-R will provide imagery in two narrow visible bands (red, blue), which is not sufficient to directly produce color (RGB) images. In this paper we present a method to estimate green band from a simulated ABI multi-spectral image. To address this problem we propose to use statistical learning to train and update functions that estimate the value for the 550 nm green channel using the values that will be present in other bands of the ABI as input parameters. One challenge is that in order to exploit as many bands as possible, we cannot use straightforward non-parametric methods such as a look-up tables because the number of entries in look-up tables grows exponentially with the number of input parameters. Other simple approaches such as simple linear regression on the multi-spectral input parameters will not produce satisfactory results due to the underlying non-linearity of the data. For instance, the relationship among different spectra for cloud footprints will be radically different from that of a desert surface. The approach we propose is to use piecewise multi-linear regression on the multi-spectral input to train the green channel predictor. Our predictor is built from the combination of a classifier followed by a multi-linear function. The classifier assigns each pixel to a class based on the array of values from the simulated (or proxy) ABI bands at that pixel. To each class is associated a set of coefficients for a multi-linear predictor for 550 nm green channel to be predicted. Thus, the parameters of the predictor consist of parameters of the classifier, as well as coefficients defining the approximating hyperplane for each class. To determine these classifiers we will use methods based on K-means clustering, as well as multi-variable piecewise linear approximation.

We describe a Web resource, developed in V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences, Tomsk; it is based on a physical approach and enables a remote calculation of the atmospheric optical parameters, required for the atmospheric correction of satellite measurements. Local and spatially distributed information resources are used as information sources for specification of the opticalmeteorological state of the atmosphere. At the first stage, the Web resource is intended to process the EOS/MODIS satellite data.

A South Atlantic Anomaly (SAA) filter has been developed to filter out large amounts of noise caused by high energy protons hitting onto the optical instrument focal plane when the satellite passes through the SAA region. The filter is based on the Principal Component Analysis (PCA)/Empirical Orthogonal Function (EOF) analysis. The EOF vectors derived from an orbit outside of the SAA region were used to represent the observations coming from the noisy SAA region. Then using the clear EOF vectors, the observations within SAA region are rebuilt with the most important principle components. The filter works well in UV region. Tests on L1B data from Global Ozone Monitoring Experiment-2 (GOME2) and Ozone Monitoring Instrument (OMI) have been conducted. It is expected that this filter can help to improve the measurements and retrievals for the Ozone Mapping and Profiler Suite (OMPS) nadir profiler in the SAA region.

The broad goal of GEOSS-V, creating a unified system of systems that encompasses all relevant atmospheric and environmental remote sensing data, accesses social and economic impact information, and integrates all relevant analysis and decision-making tools, is a monumental task. This is made more difficult in that as technology and algorithms change at an ever-increasing pace, the ability to test, prototype, and integrate new technology is often difficult in large production systems. We have been developing Graphyte, a very flexible lightweight integration framework which is aimed at augmenting GEOSS-V technology by providing agile development tools for research and development.

Aerosols are one of the most important parameters affecting the Earth's energy balance and hydrological cycle¹. They can arouse uncertainties effects on climates. To narrow the uncertainties associated with the direct and indirect aerosol effects on climates, the spatial-temporal properties of aerosol over China are investigated using the radiance measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the Terra and Aqua satellites from 2002 to 2010. The most prominent variational regions are the northern, eastern China. The high AOD values occur in 2004, 2006 and 2007 year, respectively. The tendencies of AOD are in good agreement with corresponding AOD tendencies based on data from Aerosol Robotic Network (AERONET) stations in the study regions². Seasonal AOD maxima are obtained in spring (March to May) and summer (June to August) seasons, due to large humidity and biomass burning, respectively. Dust activities in spring are frequent occurrences that also lead to high aerosol loading. AOD minima are obtained in winter (December to February) seasons. The result of our analysis reveal significant trend of seasonal AOD in the Northern and Southern China.

This paper presents two techniques respectively devoted to noise and geometric characteristics assessment from standard images instead of dedicated ones. The noise computation technique assumes that high spatial frequencies are sufficiently weakened by MTF so that only noise remains near Nyquist frequency. It uses Fourier Transform or wavelet packet decomposition. The second technique is based upon matching processing between spectral bands assuming the imaging system focal plane has staggered arrays. It yields very accurate information on focal plane layout as well as high frequency attitude disturbances. Results obtained on simulated images as well as Worldview-2 real products are detailed

The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the topof- atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other MODIS bands.

The on-orbit Modulation Transfer Function (MTF) of MODIS instrument can be accurately measured by its on-board SpectroRadiometirc Calibration Assembly (SRCA). For other Earth observing instruments without calibrators similar to SRCA, the sharp edge of moon provides a reasonable high-contrast target for their on-orbit MTF characterization. In this paper, we propose a procedure to measure MODIS on-orbit MTF from the moon image. For Terra MODIS, lunar calibration was performed nearly every month since its launch in 2000. For each lunar calibration, the images of the moon from multiple scans are taken and traced across the right edge to form an edge spread function (ESF). The ESF is used to calculate a line spread function (LSF) through differentiation. The MTF in along-scan direction is then derived through the Fourier Transform of the LSF. The same procedure can also be applied to MTF calculation in along-track direction. The results are compared with SRCA measured MTF, and the long-term trending of both MTF agrees. Lunar MTF characterization appears noisier mainly because of the non-uniformity of the moon surface and moderate spatial resolution of the moon image, which makes it difficult to accurately locate the circular lunar edge in sub-pixel level. Improvement of the current method is discussed in the end.

The MODIS instruments onboard the Terra and Aqua spacecraft, launched in December 1999 and May 2002, respectively, have successfully operated through the present time. MODIS collects the Earth view (EV) data via a twosided paddle wheel scan mirror at angles of incidence (AOI) from 10.5 to 65.5 degrees. Reflective properties between the two mirror sides are not identical with large differences seen in Terra MODIS reflective solar bands (RSB). This paper describes a methodology to calculate and monitor MODIS RSB mirror side differences using EV observations. The longterm trends of response differences between two mirror sides are evaluated using different EV targets. Results show that the on-orbit changes in the properties of the scan mirror are wavelength and AOI dependent with large mirror side differences observed at shorter wavelengths in larger AOI. Starting from 2005, the mirror side difference has gradually exhibited a seasonally dependent feature in Terra MODIS visible spectral bands, which is mainly due to the changes in the scan mirror polarization property. In addition to fully characterizing on-orbit changes of the MODIS scan mirror properties, results and discussions provided in this paper will help clarify their impacts on the Level 1B data products and support future efforts to maintain MODIS data quality.

The VIIRS Ocean Science Team (VOST) has been developing an Ocean Data Simulator to create realistic VIIRS SDR datasets based on MODIS water-leaving radiances. The simulator is helping to assess instrument performance and scientific processing algorithms. Several changes were made in the last two years to complete the simulator and broaden its usefulness. The simulator is now fully functional and includes all sensor characteristics measured during prelaunch testing, including electronic and optical crosstalk influences, polarization sensitivity, and relative spectral response. Also included is the simulation of cloud and land radiances to make more realistic data sets and to understand their important influence on nearby ocean color data. The atmospheric tables used in the processing, including aerosol and Rayleigh reflectance coefficients, have been modeled using VIIRS relative spectral responses. The capabilities of the simulator were expanded to work in an unaggregated sample mode and to produce scans with additional samples beyond the standard scan. These features improve the capability to realistically add artifacts which act upon individual instrument samples prior to aggregation and which may originate from beyond the actual scan boundaries. The simulator was expanded to simulate all 16 M-bands and the EDR processing was improved to use these bands to make an SST product. The simulator is being used to generate global VIIRS data from and in parallel with the MODIS Aqua data stream. Studies have been conducted using the simulator to investigate the impact of instrument artifacts. This paper discusses the simulator improvements and results from the artifact impact studies.

Since launch, lunar observations have been made on a regular basis for both Terra and Aqua MODIS and used in a number of applications for their on-orbit calibration and characterization, including radiometric stability monitoring, band-to-band registration (BBR) characterization, optical leak and electronic cross-talk characterization, and calibration inter-comparisons with others sensors. MODIS has 36 spectral bands, consisting of a total of 490 individual detectors, which are located on four different focal plane assemblies (FPAs). This paper focuses on the use of MODIS lunar observations for its on-orbit BBR characterization in both along-scan and along-track directions. In addition to BBR, study of detector-to-detector registration (DDR) through the use of lunar observations is also discussed. The yearly averaged BBR results developed from MODIS lunar observations are presented in this paper and compared with that derived from its on-board calibrator (OBC). In general, results from different approaches agree well. Results show that on-orbit changes in BBR have been very small for both Terra and Aqua MODIS over their entire missions. It is clearly demonstrated in this paper that the lunar approaches developed and applied to MODIS can be effectively used by other sensors for their on-orbit BBR and DDR characterization.