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NASA's Black Marble nighttime lights product suite (VNP46) is available at 500m resolution since January 2012 with data fro the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-terrain, vegetation, snow, lunar and stray light corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Current and planned validation activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at difference geographic locations and time periods representing the full range of retrieval conditions.

A characterization software suite was developed to facilitate NASA's in-flight characterization of commercial remote sensing systems. Characterization of aerial and satellite systems requires knowledge of ground characteristics, or ground truth. This information is typically obtained with instruments taking measurements prior to or during a remote sensing system overpass. Acquired ground-truth data, which can consist of hundreds of measurements with different data formats, must be processed before it can be used in the characterization. Accurate in-flight characterization of remote sensing systems relies on multiple field data acquisitions that are efficiently processed, with minimal error. To address the need for timely, reproducible ground-truth data, a characterization software suite was developed to automate the data processing methods. The characterization software suite is engineering code, requiring some prior knowledge and expertise to run. The suite consists of component scripts for each of the three main in-flight characterization types: radiometric, geometric, and spatial. The component scripts for the radiometric characterization operate primarily by reading the raw data acquired by the field instruments, combining it with other applicable information, and then reducing it to a format that is appropriate for input into MODTRAN (MODerate resolution atmospheric TRANsmission), an Air Force Research Laboratory-developed radiative transport code used to predict at-sensor measurements. The geometric scripts operate by comparing identified target locations from the remote sensing image to known target locations, producing circular error statistics defined by the Federal Geographic Data Committee Standards. The spatial scripts analyze a target edge within the image, and produce estimates of Relative Edge Response and the value of the Modulation Transfer Function at the Nyquist frequency. The software suite enables rapid, efficient, automated processing of ground truth data, which has been used to provide reproducible characterizations on a number of commercial remote sensing systems. Overall, this characterization software suite improves the reliability of ground-truth data processing techniques that are required for remote sensing system in-flight characterizations.

A measurement-based radiance estimation approach for vicarious radiometric calibration of spaceborne multispectral remote sensing systems has been developed. This simplified process eliminates the use of radiative transfer codes and reduces the number of atmospheric assumptions required to perform sensor calibrations. Like prior approaches, the simplified method involves the collection of ground truth data coincident with the overpass of the remote sensing system being calibrated, but this approach differs from the prior techniques in both the nature of the data collected and the manner in which the data are processed. In traditional vicarious radiometric calibration, ground truth data are gathered using ground-viewing spectroradiometers and one or more sun photometer( s), among other instruments, located at a ground target area. The measured data from the ground-based instruments are used in radiative transfer models to estimate the top-of-atmosphere (TOA) target radiances at the time of satellite overpass. These TOA radiances are compared with the satellite sensor readings to radiometrically calibrate the sensor. Traditional vicarious radiometric calibration methods require that an atmospheric model be defined such that the ground-based observations of solar transmission and diffuse-to-global ratios are in close agreement with the radiative transfer code estimation of these parameters. This process is labor-intensive and complex, and can be prone to errors. The errors can be compounded because of approximations in the model and inaccurate assumptions about the radiative coupling between the atmosphere and the terrain. The errors can increase the uncertainty of the TOA radiance estimates used to perform the radiometric calibration. In comparison, the simplified approach does not use atmospheric radiative transfer models and involves fewer assumptions concerning the radiative transfer properties of the atmosphere. This new technique uses two neighboring uniform ground target areas having different reflectance values. The target areas can be natural or artificial and must be large enough to minimize adjacent-pixel contamination effects. The radiative coupling between the atmosphere and the terrain needs to be approximately the same for the two targets. This condition can be met for relatively uniform backgrounds when the distance between the targets is within a few hundred meters. For each target area, the radiance leaving the ground in the direction of the satellite is measured with a radiometrically calibrated spectroradiometer. Using the radiance measurements from the two targets, atmospheric adjacency and atmospheric scattering effects can be subtracted, thereby eliminating many assumptions about the atmosphere and the radiative interaction between the atmosphere and the terrain. In addition, the radiometrically calibrated spectroradiometer can be used with a known reflectance target to estimate atmospheric transmission and diffuse- to-global ratios without the need for ancillary sun photometers. Several comparisons between the simplified method and traditional techniques were found to agree within a few percent. Hence, the simplified method reduces the overall complexity of performing vicarious calibrations and can serve as a method for validating traditional radiative transfer models

A simple technique to assess the reactivity of photocatalytic coatings sprayed onto transmissive glass surfaces was developed. This new method uses ultraviolet (UV) gallium nitride (GaN) light-emitting diodes (LEDs) to drive a photocatalytic reaction (the photocatalytic breakdown of a UV-resistant dye applied to a surface coated with the semiconductor titanium dioxide); and then a combination of a stabilized white light LED and a spectrometer to track the dye degradation as a function of time. Simple, standardized evaluation techniques that assess photocatalytic materials over a variety of environmental conditions, including illumination level, are not generally available and are greatly needed prior to in situ application of photocatalytic technologies. To date, much research pertaining to this aspect of photocatalysis has been limited and has focused primarily on laboratory experiments using mercury lamps. Mercury lamp illumination levels are difficult to control over large ranges and are temporally modulated by line power, limiting their use in helping to understand and predict how photocatalytic materials will behave in natural environmental settings and conditions. The methodology described here, using steady-state LEDs and time series spectroradiometric techniques, is a novel approach to explore the effect of UV light on the photocatalytic degradation of a UV resistant dye (crystal violet). GaN UV LED arrays, centered around 365 nm with an adjustable DC power supply, are used to create a small, spatially uniform light field where the steady state light level can be varied over three to four orders of magnitude. For this study, a set of glass microscope slides was custom coated with a thinly sprayed layer of photocatalytic titanium dioxide. Crystal violet was then applied to these titanium-dioxide coated slides and to uncoated control slides. The slides were then illuminated at various light levels from the dye side of the slide by the UV LED array. To monitor dye degradation on the slides over time, a temperature-stabilized white light LED was used to illuminate the opposite side of the slides. As the dye degraded, the amount of light from the white light LED transmitted through the slide was monitored with a spectrometer and subsequently analyzed to determine and compare the rate of dye degradation for photocatalytically coated versus uncoated slide surfaces. The long-term stability of the spectrometer/white light LED combination, which required only a single reference spectra to be taken for a time series sequence of several hours, enabled accurate measurements of transmitted light over time. Time series transmission curves were generated and results demonstrated that over time the transmission increased much more rapidly on the coated slides than on the control slides. This experimental configuration and methodology for photocatalytic activity measurement minimizes many external variable effects and allows low light level studies to be performed. This study also compares the advantages of this novel LED light source design to traditional mercury lamp systems and non-LED lamp approaches that have conventionally been used. The methodology and experimental design research summarized in this abstract is partly funded by the Department of Homeland Security, Science and Technology Directorate, and by the NASA Stennis Space Center Innovative Partnerships Program.

A simple method to estimate the photocatalytic reactivity performance of spray-on titanium dioxide coatings for transmissive glass surfaces was developed. This novel technique provides a standardized method to evaluate the efficiency of photocatalytic material systems over a variety of illumination levels. To date, photocatalysis assessments have generally been conducted using mercury black light lamps. Illumination levels for these types of lamps are difficult to vary, consequently limiting their use for assessing material performance under a diverse range of simulated environmental conditions. This new technique uses an ultraviolet (UV) gallium nitride (GaN) light emitting diode (LED) array instead of a traditional black light to initiate and sustain photocatalytic breakdown. This method was tested with a UV-resistant dye (crystal violet) applied to a titanium dioxide coated glass slide. Experimental control is accomplished by applying crystal violet to both titanium dioxide coated slides and uncoated control slides. A slide is illuminated by the UV LED array, at various light levels representative of outdoor and indoor conditions, from the dye side of the slide. To monitor degradation of the dye over time, a temperature-stabilized white light LED, whose emission spectrum overlaps with the dye absorption spectrum, is used to illuminate the opposite side of the slide. Using a spectrometer, the amount of light from the white light LED transmitted through the slide as the dye degrades is monitored as a function of wavelength and time and is subsequently analyzed. In this way, the rate of degradation for photocatalytically coated versus uncoated slide surfaces can be compared. Results demonstrate that the dye absorption decreased much more rapidly on the photocatalytically coated slides than on the control uncoated slides, and that dye degradation is dependent on illumination level. For photocatalytic activity assessment purposes, this experimental configuration and methodology minimizes many external variable effects and enables small changes in absorption to be measured. This research also compares the advantages of this innovative LED light source design over traditional mercury black light systems and non- LED lamp approaches. This novel technology begins to address the growing need for a standard method that can assess the performance of photocatalytic materials before deployment for large scale, real world use.

A hyperspectral sun photometer and associated methods have been developed and demonstrated. Accurate sun photometer calibration is critical to properly measure the solar irradiance and characterize the atmosphere. Traditional sun photometer calibration requires solar observations over several hours. In contrast, the procedures for operating this photometer entail less data acquisition time and embody a more direct approach to calibration. The scientific value of the measurement data produced by this instrument is not adversely affected by atmospheric instability. In addition, this instrument yields hyperspectral data covering a large spectral range (350-2,500 nm) not available from most traditional sun photometers. The hyperspectral sun photometer components include (1) a commercially available spectroradiometer that has been laboratory-calibrated and (2) a commercially available reflectance standard panel that exhibits nearly Lambertian 99% reflectance. The spectroradiometer is positioned above, and aimed downward at, the panel. The procedure for operating this instrument calls for a series of measurements: one in which the panel is fully illuminated by the sun, one in which a shade is positioned between the panel and the sun, and two in which the shade is positioned to cast a shadow to either side of the panel. The total sequence of measurements can be performed in less than a minute. From these measurements, the total radiance, the diffuse radiance, and the direct solar radiance are calculated. The direct solar irradiance is calculated from the direct solar radiance and the known reflectance factor of the panel as a function of the solar zenith angle. Atmospheric characteristics are estimated from the optical depth at various wavelengths calculated from (1) the direct solar irradiance obtained as described above, (2) the air mass along a column from the measurement position to the Sun, and (3) the top-of-atmosphere solar irradiance. The instrumentation used to implement the sun photometer is the same as that used to characterize targets used in radiometric vicarious calibrations. Utilizing this type of sun photometer thus reduces the amount of instrumentation and labor required to perform these studies.

The Joint Agency Commercial Imagery Evaluation (JACIE) team is a collaborative interagency working group formed to leverage different government agencies' capabilities for the characterization of commercial remote sensing products. The team is composed of staff from the National Aeronautics and Space Administration (NASA), the National Geospatial-Intelligence Agency (NGA), and the U.S. Geological Survey (USGS). Each JACIE agency has a vested interest in the purchase and use of commercial imagery to support government research and operational applications. The intent of the 2006 workshop is to exchange information regarding the characterization and application of commercial imagery used by the government. The main focus of previous workshops has been on high-resolution satellite imagery from systems; such as, IKONOS (Space Imaging, Inc.), QuickBird (DigitalGlobe, Inc.), and OrbView-3 (ORBIMAGE). This workshop is being expanded to cover all civil medium- and high-resolution commercial imagery used by the government.

Scientists within NASA#s Applied Research & Technology Project Office (formerly the Applied Sciences Directorate) have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists have used the SSC V&V site to characterize thermal infrared systems. Enhancements are being considered to characterize active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. Similar techniques are used to characterize moderate spatial resolution sensing systems at selected nearby locations. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

The NASA team of University of Arizona, South Dakota State University, and NASA SSC produce consistent results. The AWiFS calibration coefficients agree reasonably well with the NASA team estimate. The NASA team will continue to assess AWiFS radiometric accuracy.

Spectral Dark Subtraction (SDS) provides good ground reflectance estimates across a variety of atmospheric conditions with no knowledge of those conditions. The algorithm may be sensitive to errors from stray light, calibration, and excessive haze/water vapor. SDS seems to provide better estimates than traditional algorithms using on-site atmospheric measurements much of the time.

Autonomous Visible to SWIR ground-based vicarious Cal/Val will be an essential Cal/Val component with such a large number of systems. Radiometrically calibrated spectroradiometers can improve confidence in current ground truth data through validation of radiometric modeling and validation or replacement of traditional sun photometer measurement. They also should enable significant reduction in deployed equipment such as equipment used in traditional sun photometer approaches. Simple, field-portable, white-light LED calibration source shows promise for visible range (420-750 nm). Prototype demonstrated <0.5% drift over 10-40 C temperature range. Additional complexity (more LEDs) will be necessary for extending spectral range into the NIR and SWIR. LED long lifetimes should produce at least several hundreds of hours or more of stability, minimizing the need for expensive calibrations and supporting long-duration field campaigns.

This viewgraph presentation describes the spatial resolution of the AWiFS multispectral images characterized by an estimation of the Modulation Transfer Function (MTF) at Nyquist frequency. The contents include: 1) MTF Analysis; 2) Target Analysis; 3) "Pulse Target"; 4) "Pulse" Method; 5) Target Images; 6) Bridge Profiles; 7) MTF Calculation; 8) MTF Results; and 9) Results Summary.

A radiometric calibration assessment of the AWiFS (Advanced Wide Field Sensor) on the Indian Remote Sensing Resourcesat-1 satellite was performed by the NASA Applied Research & Technology Project Office (formerly the Applied Sciences Directorate) at the John C. Stennis Space Center. A reflectance-based vicarious calibration approach, requiring ground-based measurements coincident with satellite acquisitions and radiative transfer calculations, was used to estimate at-sensor radiance. The AWiFS is a 4-band, multispectral, moderate-resolution (60 m) imaging sensor that operates in the visible through short-wave infrared spectrum and is currently being considered as a Landsat-like alternative. Several study sites near the Stennis Space Center that attempted to span the dynamic range of the sensor were employed. Satellite at-sensor radiance values were compared to those estimated to determine the sensor's radiometric accuracy. The results of this evaluation provide the user community with an independent assessment of the radiometric accuracy of AWiFS image products, which are commercially available through GeoEye. These results are an extension of an independent assessment made by the University of Arizona Remote Sensing Group, the South Dakota State University Satellite Calibration Group & Image Processing Lab, and the NASA Applied Sciences Directorate at the John C. Stennis Space Center the previous year.

An assessment of the Advanced Wide Field Sensor (AWiFS) is presented. The contents include: 1) Overview of AWiFS sensor; 2) Description of University of Arizona approach; 3) Description of South Dakota State approach and results; 4) Description of Stennis Space Center approach and results; 5) Summary of results for all groups.

TOA (top-of-atmosphere) radiance from high-spatial-resolution satellite imagery systems is important for a wide variety of research and applications. Many research initiatives require data with absolute radiometric accuracy better than a few percent. The conversion of satellite digital numbers to radiance depends on accurate radiometric calibration. A common method for determining and validating radiometric calibrations is to rely upon vicarious calibration approaches. Historically, vicarious calibration methods use radiative transfer codes with ground-based atmosphere and surface reflectance or radiance inputs for estimating TOA radiance values. These TOA radiance values are compared against the satellite digital numbers to determine the radiometric calibration. However, the radiative transfer codes used depend on many assumptions about the aerosol properties and the atmospheric point spread function. A measurement-based atmospheric radiance estimation approach for high-spatial-resolution, multispectral, visible/near-infrared sensors is presented that eliminates the use of radiative transfer codes and many of the underlying assumptions. A comparison between the radiative transfer and non-radiative transfer approaches is made.

This viewgraph presentation reviews NASA and the U.S. Geological Survey (USGS)'s analysis of spatial characterization resolution for Aerial Digital Imagery.

This report discusses verification and validation (V&V) assessment of Moderate Resolution Imaging Spectroradiometer (MODIS) ocean data products contributed by the Naval Research Laboratory (NRL) and Applied Coherent Technologies (ACT) Corporation to National Oceanic Atmospheric Administration s (NOAA) Near Real Time (NRT) Harmful Algal Blooms Observing System (HABSOS). HABSOS is a maturing decision support tool (DST) used by NOAA and its partners involved with coastal and public health management.

The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration have jointly conducted characterizations of aerial digital imagery from commercial data providers. In a typical scenario, a vendor acquired imagery over the Stennis Space Center test range and provided a common data package to SSC. SSC personnel analyzed the geopositional accuracy and spatial resolution of the images, then documented the characterization results in a report and delivered the report to the USGS. Spatial resolution characterization was based on edge response measurements using one of the SSC edge targets and the tilted-edge technique. Relative Edge Response (RER) has been estimated for aerial digital imagery from several commercial data providers. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale.

Within the framework of the Joint Agency Commercial Imagery Evaluation program, the National Aeronautics and Space Administration, the National Geospatial-Intelligence Agency, and the U.S. Geological Survey cooperate in the characterization of high-to-moderate-resolution commercial imagery of mutual interest. One of the systems involved in this effort is the Advanced Wide Field Sensor (AWiFS) onboard the Indian Remote Sensing (IRS) Reourcesat-1 satellite, IRS-P6. Spatial resolution of the AWiFS multispectral images was characterized by estimating the value of the system Modulation Transfer Function (MTF) at the Nyquist spatial frequency. The Nyquist frequency is defined as half the sampling frequency, and the sampling frequency is equal to the inverse of the ground sample distance. The MTF was calculated as a ratio of the Fourier transform of a profile across an AWiFS image of the Lake Pontchartrain Causeway Bridge and the Fourier transform of a profile across an idealized model of the bridge for each spectral band evaluated. The mean MTF value for the AWiFS imagery evaluated was estimated to be 0.1.

This viewgraph presentation reviews the creation of a prototype algorithm for atmospheric correction using high spatial resolution earth observing imaging systems. The objective of the work was to evaluate accuracy of a prototype algorithm that uses satellite-derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems. This presentation focused on preliminary results of only the satellite-based atmospheric correction algorithm.

A simple and cost-effective, hyperspectral sun photometer for radiometric vicarious remote sensing system calibration, air quality monitoring, and potentially in-situ planetary climatological studies, was developed. The device was constructed solely from off the shelf components and was designed to be easily deployable for support of short-term verification and validation data collects. This sun photometer not only provides the same data products as existing multi-band sun photometers but also the potential of hyperspectral optical depth and diffuse-to-global products. As compared to traditional sun photometers, this device requires a simpler setup, less data acquisition time and allows for a more direct calibration approach. Fielding this instrument has also enabled Stennis Space Center (SSC) Applied Sciences Directorate personnel to cross-calibrate existing sun photometers. This innovative research will position SSC personnel to perform air quality assessments in support of the NASA Applied Sciences Program's National Applications program element as well as to develop techniques to evaluate aerosols in a Martian or other planetary atmosphere.

Spatial resolution of panchromatic imagery from commercial remote sensing satellites was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative Edge Response (RER) was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS). By assuming a plausible range of signal-to-noise ratio and assessing the effects of Modulation Transfer Function compensation, the NIIRS estimates were made and then compared with vendor-provided values and evaluations conducted by the National Geospatial-Intelligence Agency.

Scientists within NASA's Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site has enabled the in-flight characterization of satellite high spatial resolution remote sensing system products form Space Imaging IKONOS, Digital Globe QuickBird, and ORBIMAGE OrbView, as well as advanced multispectral airborne digital camera products. SSC utilizes engineered geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment and their Instrument Validation Laboratory to characterize high spatial resolution remote sensing data products. This presentation describes the SSC characterization capabilities and techniques in the visible through near infrared spectrum and examples of calibration results.

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

This Rapid Prototyping Capability study explores the potential to use atmospheric profiles derived from GPS (Global Positioning System) radio occultation measurements and by AIRS (Atmospheric Infrared Sounder) onboard the Aqua satellite to improve surface temperature retrieval from remotely sensed thermal imagery. This study demonstrates an example of a cross-cutting decision support technology whereby NASA data or models are shown to improve a wide number of observation systems or models. The ability to use one data source to improve others will be critical to the GEOSS (Global Earth Observation System of Systems) where a large number of potentially useful systems will require auxiliary datasets as input for decision support. Atmospheric correction of thermal imagery decouples TOA radiance and separates surface emission from atmospheric emission and absorption. Surface temperature can then be estimated from the surface emission with knowledge of its emissivity. Traditionally, radiosonde sounders or atmospheric models based on radiosonde sounders, such as the NOAA (National Oceanic & Atmospheric Administration) ARL (Air Resources Laboratory) READY (Real-time Environmental Application and Display sYstem), provide the atmospheric profiles required to perform atmospheric correction. Unfortunately, these types of data are too spatially sparse and too infrequently taken. The advent of high accuracy, global coverage, atmospheric data using GPS radio occultation and AIRS may provide a new avenue for filling data input gaps. In this study, AIRS and GPS radio occultation derived atmospheric profiles from the German Aerospace Center CHAMP (CHAllenging Minisatellite Payload), the Argentinean Commission on Space Activities SAC-C (Satellite de Aplicaciones Cientificas-C), and the pair of NASA GRACE (Gravity Recovery and Climate Experiment) satellites are used as input data in atmospheric radiative transport modeling based on the MODTRAN (MODerate resolution atmospheric TRANsmittance) radiative transport software to separate out the atmospheric component of measured top of atmosphere radiance. Simulated water bodies across a variety of MODTRAN model atmospheres including desert, mid-latitude, tropical and sub-artic conditions provide test bed conditions. Atmospherically corrected radiance and surface temperature results were compared to those obtained using traditional radiosonde balloon data and models. In general, differences between the different techniques were less than 2 percent indicating the potential value satellite derived atmospheric profiles have to atmospherically correct thermal imagery.

NASA SSC maintains four ASD FieldSpec FR spectroradiometers: 1) Laboratory transfer radiometers; 2) Ground surface reflectance for V&V field collection activities. Radiometric Calibration consists of a NIST-calibrated integrating sphere which serves as a source with known spectral radiance. Spectral Calibration consists of a laser and pen lamp illumination of integrating sphere. Environmental Testing includes temperature stability tests performed in environmental chamber.

NASA Stennis Space Center's Remote Sensing group has been characterizing privately owned high spatial resolution multispectral imaging systems, such as IKONOS, QuickBird, and OrbView-3. Natural and man made targets were used for spatial resolution, radiometric, and geopositional characterizations. Higher spatial resolution also presents significant adjacency effects for accurate reliable radiometry.

The presentation gives a general description of the verification and validation capabilities available at the John C. Stennis Space Center in southern Mississippi.

Remotely sensed ground reflectance is the basis for many inter-sensor interoperability or change detection techniques. Satellite inter-comparisons and accurate vegetation indices such as the Normalized Difference Vegetation Index, which is used to describe or to imply a wide variety of biophysical parameters and is defined in terms of near-infrared and redband reflectance, require the generation of accurate reflectance maps. This generation relies upon the removal of solar illumination, satellite geometry, and atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance, however, has been widely applied to only a few systems. In this study, we atmospherically corrected commercially available, high spatial resolution IKONOS and QuickBird imagery using several methods to determine the accuracy of the resulting reflectance maps. We used extensive ground measurement datasets for nine IKONOS and QuickBird scenes acquired over a two-year period to establish reflectance map accuracies. A correction approach using atmospheric products derived from Moderate Resolution Imaging Spectrometer data created excellent reflectance maps and demonstrated a reliable, effective method for reflectance map generation.

Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

The Coral Reef Early Warning System (CREWS) is operated by NOAA's Office of Oceanic and Atmospheric Research as part of its Coral Reef Watch program in response to the deteriorating global state of coral reef and related benthic ecosystems. In addition to sea surface temperatures (SSTs), the two most important parameters used by the CREWS network in generating coral reef bleaching alerts are 1) wind speed and direction and 2) photosynthetically available radiation (PAR). NASA remote sensing products that can enhance CREWS in these areas include SST and PAR products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and wind data from the Quick Scatterometer (QuikSCAT). CREWS researchers are also interested in chlorophyll, chromophoric dissolved organic matter (CDOM), and salinity. Chlorophyll and CDOM are directly available as NASA products, while rainfall (an available NASA product) can be used as a proxy for salinity. Other potential NASA inputs include surface reflectance products from MODIS, the Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Landsat. This report also identifies NASA-supported ocean circulation models and products from future satellite missions that might enchance the CREWS DST.

NASA at Stennis Space Center (SSC) established a Space Act Agreement with Orbital Sciences Corporation (OSC) and ORBIMAGE Inc. to collaborate on the characterization of the OrbView-3 system and its imagery products and to develop characterization techniques further. In accordance with the agreement, NASA performed an independent radiometric, spatial, and geopositional accuracy assessment of OrbView-3 imagery acquired before completion of the system's initial on-orbit checkout. OSC acquired OrbView-3 imagery over SSC from July 2003 through January 2004, and NASA collected ground reference information coincident with many of these acquisitions. After evaluating all acquisitions, NASA deemed two multispectral images and five panchromatic images useful for characterization. NASA then performed radiometric, spatial, and geopositional characterizations.

The National Oceanic and Atmospheric Administration (NOAA) Harmful Algal Bloom (HAB) Mapping System and Bulletin provide a Web-based geographic information system (GIS) and an e-mail alert system that allow the detection, monitoring, and tracking of HABs in the Gulf of Mexico. NASA Earth Science data that potentially support HABMapS/Bulletin requirements include ocean color, sea surface temperature (SST), salinity, wind fields, precipitation, water surface elevation, and ocean currents. Modeling contributions include ocean circulation, wave/currents, along-shore current regimes, and chlorophyll modeling (coupled to imagery). The most immediately useful NASA contributions appear to be the 1-km Moderate Resolution Imaging Spectrometer (MODIS) chlorophyll and SST products and the (presently used) SeaWinds wind vector data. MODIS pigment concentration and SST data are sufficiently mature to replace imagery currently used in NOAA HAB applications. The large file size of MODIS data is an impediment to NOAA use and modified processing schemes would aid in NOAA adoption of these products for operational HAB forecasting.

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can place confidence in the imagery they use and can fully understand its properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, the NASA Stennis Space Center (SSC) Earth Science Applications (ESA) directorate,through the Joint Agency for Commercial Imagery Evaluation (JACIE) framework, established a commercial imaging satellite radiometric calibration team consisting of two groups: 1) NASA SSC ESA, supported by South Dakota State University, and 2) the University of Arizona Remote Sensing Group. The two groups determined the absolute radiometric calibration coefficients of the Digital Globe 4-band, 2.4-m QuickBird multispectral product covering the visible through near-infrared spectral region. For a 2-year period beginning in 2002, both groups employed some variant of a reflectance-based vicarious calibration approach, which required ground-based measurements coincident with QuickBird image acquisitions and radiative transfer calculations. The groups chose several study sites throughout the United States that covered nearly the entire dynamic range of the QuickBird sensor. QuickBird at-sensor radiance values were compared with those estimated by the two independent groups to determine the QuickBird sensor's radiometric accuracy. Approximately 20 at-sensor radiance estimates were vicariously determined each year. The estimates were combined to provide a high-precision radiometric gain calibration coefficient. The results of this evaluation provide the user community with an independent assessment of the QuickBird sensor's absolute calibration and stability over the 2-year period. While the techniques and method described reflect those developed at the NASA SSC, the results of both JACIE team groups are included in this paper.

NASA's Earth Science Applications Directorate evaluated the potential of NASA remote sensing data and modeling products to enhance the General NOAA Oil Modeling Environment (GNOME) decision support tool. NOAA's Office of Response and Restoration (OR&R) Hazardous Materials (HAZMAT) Response Division is interested in enhancing GNOME with near-realtime (NRT) NASA remote sensing products on oceanic winds and ocean circulation. The NASA SeaWinds sea surface wind and Jason-1 sea surface height NRT products have potential, as do sea surface temperature and reflectance products from the Moderate Resolution Imaging Spectroradiometer and sea surface reflectance products from Landsat and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer. HAZMAT is also interested in the Advanced Circulation model and the Ocean General Circulation Model. Certain issues must be considered, including lack of data continuity, marginal data redundancy, and data formatting problems. Spatial resolution is an issue for near-shore GNOME applications. Additional work will be needed to incorporate NASA inputs into GNOME, including verification and validation of data products, algorithms, models, and NRT data.

NASA purchased EarthSat GeoCover orthorectified Landsat imagery of global land areas covering three historical frames: (1) mid-1970's imagery from the Landsat Multispectral Scanner (MSS); (2) late 1980's-early 1990's imagery from the Landsat Thematic Mapper (TM); and (3) year 2000 imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+). Because of the distinct time frames covered by these datasets, this imagery is valuable to land cover change research. Because geopositional accuracy plays a critical role in this area of scientific research. NASA performed an independent assessment of the geopositional accuracy of each EarthSat dataset using an independent set of government-provided ground control points (GCPs). These points were instrumental in the geopositional accuracy assessment of the TM imagery. Because of the orthorectification processes of the MSS imagery and the MSS pixel size, the aforementioned GCPs could not be used, and an alternate relative assessment procedure using the previously validated TM imagery as a "truth" dataset was used for the MSS data. Finally, the ETM data specification was defined in both an absolute sense with respect to ground coordinated and relative to the previously validated TM dataset. Therefore, two separate methods were used in validating the ETM-data. Results of the NASA independent assessments showed that the accuracies of the EarthSat GeoCover datasets met the defined specifications or were within the error and limitations of the verification methods employed.

NASA purchased Earth Satellite Corporation (EarthSat) GeoCover orthorectified Landsat imagery of global land areas. The Landsat imagery covers three distinct time frames and is valuable to land cover change research. Since geopositional accuracy plays a critical role in this area of science research, NASA performed an independent assessment of the geopositional accuracy of each EarthSat dataset using an independent set of government provided ground control points. These points consisted of features identifiable within the 28.5 meter resolution TM imagery whose locations were accurately known.

In an effort to more full explore the potential of commercial remotely sensed land data sources, the NASA Earth Science Enterprise (ESE) implemented an experimental Scientific Data Purchase (SDP) that solicited bids from the private sector to meet ESE-user data needs. The images from the Space Imaging IKONOS system provided a particularly good match to the current ESE missions such as Terra and Landsat 7 and therefore serve as a focal point in this analysis.

The Earth science community needs to generate consistent and standard definitions for spatial, spectral, radiometric, and geometric properties describing passive electro-optical Earth observing sensors and their products. The parameters used to describe sensors and to describe their products are often confused. In some cases, parameters for a sensor and for its products are identical; in other cases, these parameters vary widely. Sensor parameters are bound by the fundamental performance of a system, while product parameters describe what is available to the end user. Products are often resampled, edge sharpened, pan-sharpened, or compressed, and can differ drastically from the intrinsic data acquired by the sensor. Because detailed sensor performance information may not be readily available to an international science community, standardization of product parameters is of primary performance. Spatial product parameters described include Modulation Transfer Function (MTF), point spread function, line spread function, edge response, stray light, edge sharpening, aliasing, ringing, and compression effects. Spectral product parameters discussed include full width half maximum, ripple, slope edge, and out-of-band rejection. Radiometric product properties discussed include relative and absolute radiometry, noise equivalent spectral radiance, noise equivalent temperature diffenence, and signal-to-noise ratio. Geometric product properties discussed include geopositional accuracy expressed as CE90, LE90, and root mean square error. Correlated properties discussed include such parameters as band-to-band registration, which is both a spectral and a spatial property. In addition, the proliferation of staring and pushbroom sensor architectures requires new parameters to describe artifacts that are different from traditional cross-track system artifacts. A better understanding of how various system parameters affect product performance is also needed to better ascertain the utility of existing datasets and products as well as to specify the performance of new sensors and products. Examples of simulations performed for the Landsat Data Continuity Mission illustrate how various parameters affect system and product performance. Specific examples include the effects of ground sample distance, MTF, and band-to-band registration on various products.

The Joint Agency Commercial Imagery Evaluation (JACIE) team is a collaborative interagency group focused on the characterization of commercial remote sensing data products. The team members - the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS) - each have a vested interest in the purchase and use of commercial imagery to support government research and operational applications. For both research and applications, commercial products must be well characterized for precision, accuracy, and repeatability. Since commercial systems are built and operated with no government insight or oversight, the JACIE team provides an independent product characterization of delivered image and image-derived end products. End product characterization differs from the systems calibration approach that is typically used with government systems, where detailed system design information is available. The product characterization approach addresses three primary areas of product performance: geopositional accuracy, image quality, and radiometric accuracy. The JACIE team utilizes well-characterized test sites to support characterization activities. To characterize geopositional accuracy, the team utilizes sites containing several "photo-identifiable" targets and compares their precisely known locations with those defined by the commercial image product. In the area of image quality, spatial response is characterized using edge targets and pulse targets to measure edge response and to estimate image modulation transfer function. Additionally, imagery is also characterized using the National Imagery Interpretability Rating Scale, a means of quantifying the ability to identify certain targets (e.g., rail-cars, airplanes) within an image product. Radiometric accuracy is characterized using reflectance-based vicarious calibration methods at several uniform sites. Each JACIE agency performs an aspect of product characterization based on its area of expertise, thus minimizing duplication of effort. The JACIE team collaborated to perform comprehensive characterization of products from Space Imaging Inc.'s IKONOS satellite and from DigitalGlobe's QuickBird satellite and is currently characterizing products from OrbImage s OrbView-3. JACIE assessments have resulted in several improvements to commercial image product quality and have enhanced working relationships between government and industry. Assessment results are presented at an annual JACIE High Spatial Resolution Commercial Imagery Workshop.

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can place confidence in the imagery they use and can fully understand its properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other system. In addition, the user community has little or no insight into the design and operation of commercial sensors or into the methods involved in generating commercial products. To address this calibration need, the NASA Stennis Space Center (SSC) Earth Science Applications (ESA) Directorate established a commercial satellite imaging radiometric calibration team consisting of three independent groups: NASA, SSC,ESA, the University of Arizona Remote Sensing Group, and South Dacota State University. Each group determined the absolute radiometric calibration coefficients of the Space Imaging IKONOS 4-band, 4 m multispectral product covering the visible through near-infrared spectral region. For a three year period beginning in 2000, each team employed some variant of a reflectance-based vicarious calibration approach, requiring ground-based measurements coincident with IKONOS image acquisitions and radiative transfer calculations. Several study sites throughout the United States were employed that covered nearly the entire dynamic range of the IKONOS sensor. IKONOS at-sensor radiance values were compared to those estimated by each independent group to determine the IKONOS sensor's radiometric accuracy and stability. Over 10 individual vicariously determined at-sensor radiance estimates were used each year. When combined, these estimates provided a high-precision radiometric gain calibration coefficient. No significant calibration offset was observed. The results of this evaluation provide the scientific community with an independent assessment of the IKONOS sensor's absolute calibration and temporal stability over the 3-year period. While the techniques and method described in this paper reflect those developed at the NASA SSC, the results of the entire team are included.

A pseudo-Brewster-angle infrared radiometer has been proposed for use in noncontact measurement of the surface temperature of a large body of water (e.g., a lake or ocean). This radiometer could be situated on a waterborne, airborne, or spaceborne platform. The design of the pseudo-Brewster-angle radiometer would exploit the spectral-emissivity and polarization characteristics of water to minimize errors attributable to the emissivity of water and to the reflection of downwelling (e.g., Solar and cloud-reflected) infrared radiation. The relevant emissivity and polarization characteristics are the following: . The Brewster angle is the angle at which light polarized parallel to the plane of incidence on a purely dielectric material is not reflected. The pseudo-Brewster angle, defined for a lossy dielectric (somewhat electrically conductive) material, is the angle for which the reflectivity for parallel-polarized light is minimized. For pure water, the reflectivity for parallel-polarized light is only 2.2 x 10(exp -4) at its pseudo- Brewster angle of 51deg. The reflectivity remains near zero, several degrees off from the 51deg optimum, allowing this angle of incidence requirement to be easily achieved. . The wavelength range of interest for measuring water temperatures is 8 to 12 microns. The emissivity of water for parallel- polarized light at the pseudo-Brewster angle is greater than 0.999 in this wavelength range. The radiometer would be sensitive in the wavelength range of 8 to 12 microns, would be equipped with a polarizer to discriminate against infrared light polarized perpendicular to the plane of incidence, and would be aimed toward a body of water at the pseudo- Brewster angle (see figure). Because the infrared radiation entering the radiometer would be polarized parallel to the plane of incidence and because very little downwelling parallel-polarized radiation would be reflected into the radiometer on account of the pseudo-Brewster arrangement, the radiation received by the radiometer would consist almost entirely of thermal emission from the surface of the water. Because the emissivity of the water would be very close to 1, the water could be regarded as a close approximation of a blackbody for the purpose of computing its surface temperature from the radiometer measurements by use of the Planck radiation law.