sstl uk-dmc slim-6 data quality assessment

2380 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 47, NO. 7, JULY 2009

SSTL UK-DMC SLIM-6 Data Quality AssessmentGyanesh Chander, Member, IEEE, Sebastien Saunier,

Michael J. Choate, Member, IEEE, and Pasquale L. Scaramuzza

Abstract—Satellite data from the Surrey Satellite TechnologyLimited (SSTL) United Kingdom (UK) Disaster Monitoring Con-stellation (DMC) were assessed for geometric and radiometricquality. The UK-DMC Surrey Linear Imager 6 (SLIM-6) sen-sor has a 32-m spatial resolution and a ground swath width of640 km. The UK-DMC SLIM-6 design consists of a three-bandimager with green, red, and near-infrared bands that are set tosimilar bandpass as Landsat bands 2, 3, and 4. The UK-DMCdata consisted of imagery registered to Landsat orthorectifiedimagery produced from the GeoCover program. Relief displace-ments within the UK-DMC SLIM-6 imagery were accounted forby using global 1-km digital elevation models available throughthe Global Land One-km Base Elevation (GLOBE) Project. Po-sitional accuracy and relative band-to-band accuracy were mea-sured. Positional accuracy of the UK-DMC SLIM-6 imagery wasassessed by measuring the imagery against digital orthophotoquadrangles (DOQs), which are designed to meet national mapaccuracy standards at 1 : 24 000 scales; this corresponds to a hor-izontal root-mean-square accuracy of about 6 m. The UK-DMCSLIM-6 images were typically registered to within 1.0–1.5 pixelsto the DOQ mosaic images. Several radiometric artifacts likestriping, coherent noise, and flat detector were discovered andstudied. Indications are that the SSTL UK-DMC SLIM-6 datahave few artifacts and calibration challenges, and these can beadjusted or corrected via calibration and processing algorithms.The cross-calibration of the UK-DMC SLIM-6 and Landsat 7Enhanced Thematic Mapper Plus was performed using imagestatistics derived from large common areas observed by the twosensors.

Index Terms—Calibration, characterization, Enhanced The-matic Mapper Plus (ETM+), geometry, Landsat, radiometry,relative spectral response (RSR), spectral bands, Surrey LinearImager 6 (SLIM-6), Surrey Satellite Technology Limited (SSTL),United Kingdom (UK) Disaster Monitoring Constellation (DMC).

I. MISSION PROFILE

THE DISASTER Monitoring Constellation (DMC) pro-vides worldwide daily revisit capability for disaster re-

sponse and delivers high temporal resolution imagery formany applications, including oil and gas supply continuity,cartography, environment, telecoms, agriculture, and forestry.The Surrey Satellite Technology Limited (SSTL) is a pri-vately owned subsidiary of the University of Surrey, Guildford,England. Some key missions developed by SSTL are the five

Manuscript received June 2, 2008; revised October 19, 2008 and January 2,2009. First published March 27, 2009; current version published June 19, 2009.This work was performed under USGS Contract 08HQCN0005.

G. Chander, M. J. Choate, and P. L. Scaramuzza are with Stinger GhaffarianTechnologies (SGT), Inc., contractor to the U.S. Geological Survey (USGS)Earth Resources Observation and Science (EROS) Center, Sioux Falls,SD 57198 USA (e-mail: [email protected]).

S. Saunier is with the GAEL Consultant, 77420 Champs-sur-Marne, France.Color versions of one or more of the figures in this paper are available online

at http://ieeexplore.ieee.org.Digital Object Identifier 10.1109/TGRS.2009.2013206

University of Surrey Satellites (UoSAT), Korea Institute ofTechnology Satellites (KITSAT-1 and -2), Portuguese satel-lite (PoSAT-1), Caractérisation de l’Environnement Radio-electrique pour un instrument Spatial Embarque (CERISE),UoSAT-12, Thai-Microsatellite (TMSat), Surrey NanosatelliteApplication Program (SNAP), and Tsinghua-1 [1], [2]. TheDMC Consortium is made up of five nations, each of whichowns and operates a satellite and ground station. The membersare Algeria, China, Nigeria, Turkey, and the U.K. Table I sum-marizes key specifications of the constellation satellites. Theobjective of the DMC microsatellites is to provide a daily globalimaging capability at medium resolution for rapid responsedisaster monitoring and mitigation. The project relies on aninternational consortium into which each nation or organizationoperates its own satellite and ground segments. Table II listsorbit characteristics of several Earth Observation missions andthose of the UK-DMC. The DMC constellation satellite has anoperation life of five years [2], [3]. DMC International ImagingLtd. (DMCii) handles the sale and supply of DMC data andinternational disaster response. Created after the launch of thesatellite constellation, DMCii is in charge of data distributionand service creation. DMCii coordinates partners through acentralized mission planning system at SSTL and fulfills cus-tomer requests.

II. UK-DMC SENSOR OVERVIEW

Sensors onboard UK-DMC satellites differ and depend onsatellite owner (Table I). The Extended Swath Imaging Systemsensor, also called Surrey Linear Imager 6 (SLIM-6), is usedonboard UK-DMC satellites. The UK-DMC SLIM-6 sensor isa multispectral sensor operating in three spectral bands in thevisible and near-infrared (NIR) regions of the electromagneticspectrum. The UK-DMC SLIM-6 design consists of a three-band imager providing a spatial resolution of 32 m and a groundswath width of 640 km. The large swath of UK-DMC SLIM-6is achieved by having two separate banks of cameras, eachcovering half the swath and overlapping at nadir, as shown inFig. 1. Each sensor has a charge-coupled device (CCD) witha linear array of over 10 000 detectors. The satellite uses twoseparate arrays for each band, which overlap in ground projec-tion to produce images with a swath width exceeding 640 km,using almost 20 000 detectors in total.

The sensor optics is characterized by a very short focallength (150 mm) and an aperture diameter of about 90 mm;this configuration equips the sensor with a small detector size(6.5 μm AC/AT) with respect to a 30-m ground samplingdistance [2]. The UK-DMC has a field of view (FOV) of±17.5◦. The Landsat 7 (L7) Enhanced Thematic Mapper Plus

0196-2892/$25.00 © 2009 IEEE

CHANDER et al.: SSTL UK-DMC SLIM-6 DATA QUALITY ASSESSMENT 2381

TABLE IDMC SATELLITE SPECIFICATIONS

TABLE IIUK-DMC AND OTHER SATELLITE MISSION CHARACTERISTICS

Fig. 1. Layout of the UK-DMC SLIM-6 multispectral imager [3].

(ETM+) has a FOV of ±7.2◦. Because of the large FOV,the UK-DMC SLIM-6 images will have geometric distortionsat the swath edge. Fig. 2 compares the UK-DMC SLIM-6swath with the geographical coverage from other sensors.

Fig. 2. UK-DMC SLIM-6 imager (640-km swath width) overlaid with scenefootprints from other imaging sensors as summarized in Table II.

Fig. 3 compares the swath width and spatial resolution of thesesensors. Fig. 4 shows a comparison of the FOV of UK-DMCSLIM-6 and L7 ETM+ sensors. Table III summarizes the keyspecifications of the UK-DMC SLIM-6 and L7 ETM+ sensors.


Fig. 3. Swath width along with spatial resolution.

Fig. 4. Across-track spatial resolution along the FOV.

TABLE IIIUK-DMC SLIM-6 AND L7 ETM+ KEY SPECIFICATIONS

UK-DMC onboard data storage capacity is 1.5 GB. Althoughthe chip has potential for a 10-b dynamic range, only 8 b arestored and sent to the ground. Hence, the dynamic range is256 gray-level values [2]. The data transfer is achieved usingS-band with a data rate of about 5 Mb/s. The data volume thatcan be downlinked from UK-DMC is 1.5 GB per day at SSTLin Guildford, U.K. This data transfer capability is inferior to theone provided with communication in X-band. Satellites such asLandsat ETM+ and Système Pour l’Observation de la Terre(SPOT) HRVIR provide X-band transfer of about 2 × 75 Mb/sand 1 × 50 Mb/s. UK-DMC satellites are not able to transmitdata to a ground segment through satellite relay. A 1.5-GB staterecorder is mounted onboard the UK-DMC satellite, which isvery small storage capability when compared to L7 ETM+(378 GB) [3].

The UK-DMC provides a constant phasing between thesatellites. Satellite orbital position is determined using a Global

TABLE IVUK-DMC SLIM-6 PRODUCT ORGANIZATION

TABLE VUK-DMC SLIM-6 PRODUCT LEVEL

Positioning System receiver, which provides the timing func-tion. Orbit control is maintained using pressurized cold gas ora liquefied gas system (resistojet thrusters) for constellationphasing maneuvers and small orbit corrections. In general,the simplest attitude control is a passive stabilization, and itrelies on either magnetic or gravity gradient methods. Simpleand passively stable systems have a low pointing performance.Complex systems using reaction wheels are highly accuratepointing systems. Satellite stabilization techniques for control-ling orientation or attitude of the spacecraft are classified intofour categories: single spin stabilization, dual spin stabilization,three-axis stabilization, and gravity gradient stabilization [4].UK-DMC platform attitude control is done through the use ofgravity gradient method. The European Space Agency Envi-ronmental Satellite, SPOT, and Landsat are stabilized with athree-axis technique and offer a better pointing accuracy (about0.015◦) compared to the microsatellites (DMC, Micro Lab)stabilized with a gravity gradient technique (about 2◦).

A. UK-DMC SLIM-6 Data Products

UK-DMC product from the SLIM-6 sensor is processed inGeoTiff Digital Image Map (DIMAP) format. The DIMAPformat is the new format for SPOT products, introduced forthe Spot 5 launch in May 2002 and developed with the CentreNational d’Etudes Spatiales. The DIMAP format is a public for-mat for describing geographic data. Although it was speciallydesigned for image data, it can also handle vector data. Anexample of the UK-DMC SLIM-6 product id DU000107T_L1Tis summarized in Table IV. UK-DMC SLIM-6 processinglevels listed in Table V are compliant with the commonly used


Fig. 5. UK-DMC SLIM-6 (400 × 400 pixels) imagery over (a) Paris urban area, (b) industrial plant, and (c) crop fields.

Fig. 6. Comparison of UK-DMC SLIM-6 spectral ranges with other sensors.

standard nomenclature. Fig. 5 shows sample full-resolutionimagery over the following: 1) Paris urban area; 2) industrialplant; and 3) crop fields. The four-lane “Normandie” bridge thathas a width of 23.5 m is shown near the industrial plant. Whenzooming in on the image data, the bridge is recorded in less thantwo pixels. The industry plant and the warehouse can be seen,but they are hard to recognize.

B. Spectral Characteristics of the Sensor

The UK-DMC SLIM-6 sensor provides three spectral bandscovering the green (520–600 nm), red (630–690 nm), and NIR(770–900 nm) electromagnetic spectrum regions. Fig. 6 showsa comparison of the UK-DMC SLIM-6 spectral ranges withother sensors. These spectral ranges are similar to the green,red, and NIR spectral bands of SPOT 5 High Resolution Geo-metric, Landsat 5 (L5) Thematic Mapper (TM), and L7 ETM+.Although the spectral range is similar, it does not mean that fora given wavelength, the spectral response of UK-DMC SLIM-6band matches with the band of the L7 ETM+. The SLIM-6spectral filters were manufactured by Barr Associates Inc., U.S.,using the same materials and processes as the spectral filters onthe ETM+ sensor. The spectral filter of each channel is pro-tected by a fused silica radiation absorption window, which ispositioned on the space facing side of the filter. The spectral fil-ters are located in front of the camera lens. Fig. 7 shows a com-

parison of the relative spectral response (RSR) profiles of L7ETM+, Indian Remote Sensing Satellite (IRS-P6) AdvancedWide Field Sensor (AWiFS) and Linear Imaging Self-Scanner(LISS-III), China-Brazil Earth Resources Satellite (CBERS-2)High Resolution CCD Camera (CCD) the Infrared Multispec-tral Scanner (IRMSS), and UK-DMC SLIM-6 sensors. Thetwo separate banks of UK-DMC SLIM-6 cameras have slightlydifferent spectral responses. In red band, the spectral filtersfrom the two banks were very similar and a single RSR profilewas used to characterize the response. The RSR profiles fromthe two banks are referred as primary (P) or secondary (S). Theyare sometimes referred to as Port and Starboard. The P is themaster imager in each image pair and is usually in the left-handside (hence, port side of the delivered image) [3].

Fig. 8 shows an evaluation that was performed to checkthe UK-DMC SLIM-6 ability to discern the typical surfacematerials. The green-band peak around 0.55 μm (fir tree curve)can be used to discriminate vegetation and identify man-madestructures. The red band is ending just before the vegetationreflectance drop (around 0.69 μm) and can be used to discernbare soil from vegetation canopy. The NIR band is used forwater body discrimination, and soil moisture and vegetationmonitoring. Red and NIR bands are used for computationof spectral vegetation indices such as the widely used nor-malized difference vegetation index. Handling red and NIRbands is suitable for discrimination of crop canopy density.


Fig. 7. Comparison of the RSR profiles of L7 ETM+, P6 AWiFS/LISS-III, CBERS-2 CCD/IRMSS, and UK-DMC SLIM-6 sensors.

Fig. 8. Typical spectral reflectance curves and UK-DMC SLIM-6 spectralranges.

The UK-DMC SLIM-6 spectral bands cannot be used fordiscrimination of clays (TM5, TM7), hydroxides, iron oxide(TM1 blue), or plant stress (TM5, TM7).

III. GEOMETRIC ANALYSIS

The geometric characterization involves understanding theprocesses by which pixel coordinates within an image canbe mapped to known locations on the ground. Generally, thisprocess involves the use of well-surveyed photo-identifiable tar-gets placed within a scene. Because this is primarily a functionof what can be seen at a given resolution, different techniquesare applied to different resolution ranges to ensure that methodsexist to evaluate a wide range of sensors. In addition, thesetechniques seek to leverage existing technologies where pos-sible. One place that this leverage is applied is with the use ofsome of the geometric assessment tools that were developedfor the L7 ETM+ Image Assessment System (IAS) [5], [6].The IAS is responsible for offline assessment of image qualityto ensure compliance with the radiometric and geometric re-quirements of the L7 satellite and the ETM+ sensor throughoutthe mission [7], [8].


TABLE VIUK-DMC SLIM-6 DATA USED FOR GEOMETRY CHARACTERIZATION

A. Data Sets Used for the Study

Eight UK-DMC SLIM-6 data sets acquired over the Rail-road Valley Playa, Nevada (RVPN) geometric supersite wereassessed in this paper. These images are listed in Table VIand were acquired with zero-degree viewing angle (nadir).The table also lists whether the digital orthophoto quadrangle(DOQ) data sets needed for the geodetic assessment of the datawere available. Images were processed by UK-DMC Interna-tional Imaging Ltd. and listed as being processed to a Level-1terrain corrected (L1T) product. These products are processedwith ground control and have the effects due to elevationremoved from the imagery. GeoCover imagery was used as areference source for registering the UK-DMC SLIM-6 data.The GeoCover program [9] created wall-to-wall orthorectifiedLandsat TM and ETM+ imagery. The imagery is listed ashaving a geodetic accuracy of better than 50-m root-mean-square error (rmse). Elevation data used within the process-ing were the global 1-km digital elevation models availablethrough the Global Land One-km Base Elevation (GLOBE)Project [10]. All UK-DMC SLIM-6 images were resampledto a Universal Transverse Mercator projection using the WorldGeodetic System 1984 (WGS84) geographic coordinate systemand had a pixel size of 32 m in both the X and Y map directions.

B. I2I Assessment

The image-to-image (I2I) characterization is usually per-formed to compare the relative accuracy between two images.One image is selected as a reference and another as thesearch image. Points/Image chips (small area of about 64 ×64 pixels) are selected from the reference image and are corre-lated with the search image. The coregistration results providean insight to the relative accuracy of the search image withrespect to the reference image. Plotting the points measuredbetween the two images helps in assessing any systematic biasor higher order distortion between the image data. The I2Iassessment provides numerical evaluation of the accuracy ofcommon bands of temporally distinct images [7]. The I2I toolavailable within the IAS can be used to analyze other imageryas needed besides the ETM+ data.

The IAS I2I tool assesses the geometric difference betweentwo image files by performing normalized grayscale correlationon windowed image pairs between two data sets. Several crite-ria are used for determining if a single correlation measurementis successful. Some of these criteria include strength of thecorrelation peak and maximum allowable displacement. Offsetsare measured as the peak location of the correlation surface.The offset is calculated to the subpixel level by fitting a 3-D

Fig. 9. UK-DMC SLIM-6 and coregistered DOQ mosaic.

Fig. 10. Full-resolution window of resampled DOQ mosaic.

surface around the peak of the correlation surface. A studentt-test is performed on the measured offsets to remove anyoutliers produced from the correlation process. Statistics cal-culated on the final points kept from the I2I process providean assessment of the geometric differences between the twoimages. The I2I comparison tool expects the image data setsbeing compared to have the same resolution.

One worldwide reference system (WRS) wall-to-wall DOQmosaic is often referred to as a geometric supersite. The Landsatprogram has a suite of geometric test sites (“supersites”) toevaluate geometric accuracy. The supersites are georeferencedimages derived from a high-resolution source. These high-resolution data sets consist of mosaics of DOQs over the extentof one standard WRS-2 Landsat image (187 km by 187 km).DOQs meet national map accuracy standards at 1 : 24 000 scale,which equates to a horizontal root-mean-square accuracy ofabout 6 m. This corresponds to an uncertainty of 1/5 of anETM+ pixel at the 30-m scale. The DOQs are mosaicked tocreate a data set equal to one WRS-2 nominal swath.

The L7 IAS I2I was used in performing a geodetic assess-ment of the UK-DMC SLIM-6 L1T data sets. The ground con-trols used for geodetic accuracy of the UK-DMC SLIM-6 datasets were the mosaicked DOQs. These mosaicked DOQs weresubsampled to match the resolution of the UK-DMC SLIM-6data. Fig. 9 shows the UK-DMC SLIM-6 images along withthe coregistered DOQ mosaic images used for the geodetic ac-curacy assessment. The very apparent checkered pattern withinthe DOQ mosaic is due to the radiometric differences betweenindividual DOQs. A full-resolution window of the DOQ mosaiccan be seen in Fig. 10. There were two images for which no


TABLE VIIGEODETIC ACCURACY OF UK-DMC SLIM-6 IMAGES

Fig. 11. Vector residuals between UK-DMC SLIM-6 and DOQ mosaic image(DU0005eaT).

DOQs were available for a geodetic accuracy assessment. Theimages still had a band-to-band (B2B) registration assessmentperformed on the data sets.

Comparison between the UK-DMC SLIM-6 images and theDOQ mosaics are listed in Table VII. The UK-DMC SLIM-6images were typically registered to within 1.0–1.5 pixels tothe DOQ mosaic images. The rmse measured between theUK-DMC SLIM-6 image and the reference DOQ data setsranged from 7.03 to 23.53 m (0.22–0.74 pixels) in theX-direction and from 26.20 to 36.67 m (0.82–1.15 pixels) in theY -direction. Fig. 11 shows a plot of vector residuals producedfrom the UK-DMC SLIM-6 to DOQ mosaic comparison. Vec-tors are scaled by a factor of 4000 so that they are more easilyviewable within the imagery. In all six comparisons, there wasa slight bias in the line direction or, more likely, along the flightpath of the satellite.

C. B2B Assessment

The B2B characterization is performed to ensure that theproper band alignment is provided for an image product.Typically, when using the IAS B2B assessment tool, a bandalignment assessment registers each band against every otherband (resample bands of higher resolution to coarse resolution).The B2B assessment provides a numerical evaluation of theaccuracy of the band registration within an image. The B2B toolavailable within the IAS can be used to analyze other imageryas needed besides the ETM+ data.

TABLE VIIIB2B REGISTRATION RESULTS

The IAS B2B tool works similarly to the I2I tool. The B2Btool works by first choosing an evenly distributed set of pointsbetween each band pair within the imagery. The process thenperforms a normalized grayscale correlation between the twobands at each location and follows the same procedures as I2Iin determining subpixel location. After each band combinationis measured, a student t-test is performed on each individual setof band pairs to remove any remaining outliers. Statistics canbe calculated on the final points kept to give an assessment ofthe band alignment within the image data. Plotting the residualskept can help determine the kind of band alignment distortionthat is present.

For the B2B correlation process, data sets that contain bandsof differing resolution must have one of the bands resampledso that image bands to be compared have matching resolu-tions. For multiresolution data sets, the differences in resolutionmust be of integer multiples. Bands of common resolution arecreated by reducing higher resolution bands to be of equalresolution to that of the lower bands. The two techniques usedin the IAS for reducing the resolution of an image are theGaussian Pyramid approach and an oversampled cubic convo-lution weighting function. Other approaches, such as using aweighting function that more closely resembles the modulartransfer function (MTF) of the sensor, would be useful butrequire further investigation.

The B2B assessment of the UK-DMC SLIM-6 data setswas also performed using the IAS B2B tool. Table VIII liststhe B2B registration for all eight of the UK-DMC SLIM-6images. Fig. 12 shows the residual vector plots for each bandpair measured for all eight UK-DMC SLIM-6 images. Vectorsare scaled by a factor of 3000 so that they are more visiblewithin the imagery. The B2B assessment showed some biaswithin the band registration. Most often, the bias appeared tobe associated with the registration of band 1 to band 3. Inseveral cases, the registration of band 2 to band 3 also showed anoticeable bias.


Fig. 12. B2B registration residuals (DU0005eaT).

IV. RADIOMETRIC ANALYSIS

The UK-DMC SLIM-6 calibration team performs regularradiometric characterization and monitors the stability of thesensor. The calibration team has carried out the followingprojects: 1) acquisition of deep space image for dark currentand relative calibration, just after satellite launch when gradientboom system is disabled; 2) acquisition of dark images overPacific, snow scenes over DOM-C, and comparison to the deepspace image; 3) monthly monitoring of relative calibration per-formed on snow scenes; and 4) a vicarious calibration exercisein collaboration with the University of Arizona on data setsacquired over RVPN test site to monitor the absolute calibrationaccuracy [3].

Radiometric analysis was performed on one SSTL UK-DMCSLIM-6 sensor image acquired over the Las Vegas, Nevadaregion, with an imaging time of 17:25:26 on 2004-07-19. Theimage used for the study was processed to create a Level-1radiometrically corrected image (L1R) in TIFF format.

A. Flat Detector

There appears to be at least one “flat” detector, which causesa stripe of bright data in the flight direction. This artifactstretches the entire height of the scene, although it is less visiblein cloudy regions and more visible over dark terrain. In Fig. 13,it appears in all three bands but in slightly different locations;the red band is the major contributor to the stripe visible in theRGB image. This “flat” detector has a reduced dynamic range,causing its response to be ∼3–4 DN higher than the adjacentdetectors. The location and approximate digital number (DN)magnitude of this vertical stripe is

NIR : pixel 15426 ∼3 DN

Red : pixel 15416 ∼4 DN

Green : pixel 15418 ∼3 DN.

Quantitative assessments were performed on a uniform im-age part over the “flat” detector. For a given line number, thepixel value of the three bands was extracted along the columnnumber. In image coordinates, the location of the stripe differsfrom one band to the other, as shown in Fig. 14.

Fig. 13. Detector anomaly in each band and composite.

B. Coherent Noise

All bands exhibit low magnitude banding, visible only inextreme stretches over homogenous terrain. Fig. 15 showsLake Mead with an extreme linear stretch applied, displayingthe banding. Considering that SLIM-6 is a pushbroom sensor,this banding appears to be a coherent noise source with awavelength of about 270 scan lines. To examine the banding,an area of interest was cropped from the center of the lake,380 detectors wide and 896 scan lines high, and then, the meanof each scan line was calculated. This created visible coherentnoise patterns in all three bands, as shown in Fig. 16.

Fig. 17 shows a plot of the Fourier transform of the waterdata, calculated in an attempt to isolate the coherent noisesources. Two major sources appear in all bands at wavelengthsof about 270 scan lines and 25 scan lines. Other sources maybe harmonics of these, or they may be separate sources ofnoise, and it is possible that some are caused by patterns inthe underlying imagery of the lake itself. Access to nighttime orshutter data would be required for a full coherent noise analysis.


Fig. 14. Corrupted detector values along column number.

Fig. 15. Lake Mead (430 × 200 pixels) with linear stretch applied, displayingbanding.

Fig. 16. 380-detector mean of RGB bands over water area.

C. MTF

The ability of an imaging sensor to resolve the spatial ob-jects can be assessed using MTF. The MTF is the normalizedmagnitude of the Fourier transform of the sensor’s point spreadfunction. Specifications can be defined by requesting certainminimum values of the MTF at critical spatial frequencies (e.g.,Nyquist frequency). MTF is extremely difficult to quantifywithout a calibrated ground target, but qualitatively, the NIR

Fig. 17. Power spectrum of 380-detector mean water data.

band in these data appears to be blurrier than the red and greenbands. Fig. 18 shows an example of a highway whose detailsare much more distinct in the red and green bands than in theNIR band.

Prelaunch or in-flight MTF is usually provided with the mis-sion specification document because it is strongly associatedwith the ground resolution. However, no prelaunch MTF valueis given for the UK-DMC SLIM-6 sensor and no scientificpublications were found.

D. Striping

Individual detectors within an array typically do not possesssimilar gain and bias characteristics. This mismatch of detectorresponse results in the appearance of striping in acquired im-ages. Over clouds, the green band saturates at about 210 DNand exhibits minor detector striping, as shown in Fig. 19. Thisdetector striping is about 4 DN in magnitude. The NIR and redbands saturate over clouds, but they saturate at 255, and theydo not exhibit this detector variation. The fact that the greenband saturates at 210 DN may point to a problem with therelative gain calibration in the green band and could indicatenonlinearity in the green band over high-radiance targets. Ifany specific band shows saturation, it is possible to changethe integration times independently for each band to preventstriping. No low saturations were found in the provided data.


Fig. 18. NIR, Red, and Green bands (175 × 175 pixels), showing MTF differences.

Fig. 19. Detector saturation striping in green band (430 × 200 pixels).

Fig. 20. Odd/Even detector striping in the red band (100 × 40 pixels).

In addition to the saturation striping shown in Fig. 19, the redband exhibits a residual odd–even detector striping as shownin Fig. 20. This striping is about 2 DN in magnitude and isonly visible in the imagery when an extreme stretch has beenapplied. It is visible over targets of any radiance, indicating asimple miscalibration of the relative detector biases, not a po-tential nonlinearity effect as in the saturation striping in Fig. 19.The dark detector bias appears to be above 10 DN for all bands.

Fast Fourier transform (FFT) was performed on image chipsextracted from the UK-DMC SLIM-6 image data set acquired,as shown in Fig. 21. An FFT 2-D representation highlightsnonnominal frequency peaks occurring along north–south axis.FFT results confirmed a persistent line-to-line miscalibrationoccurring on UK-DMC SLIM-6 green band. The histogram andstatistics of the image chips are also summarized in Fig. 21.The shapes of the green- and red-band histograms and thestandard deviation are very close. The histogram of the NIRband is wider than that of the other bands with higher standarddeviation. The red band has some residual striping, but themagnitude of the striping artifact is less in comparison to thegreen band. The UK-DMC SLIM-6 NIR band seems to be freefrom the striping artifact.

E. Cross-Calibration With the L7 ETM+

The cross-calibration approach involved comparing imagestatistics derived from large common areas observed by the L7ETM+ and UK-DMC SLIM-6 sensors [12]–[14]. The imagedata from both sensors were converted to absolute units ofat-sensor radiance, which is the fundamental step in puttingimage data from multiple sensors and platforms onto a commonradiometric scale [15]–[17]. The absolute radiance values arescaled to 8-b values representing calibrated digital numbers(Qcal) before output to the distribution media. Conversion fromQcal in L1 products back to Lλ requires knowledge of theoriginal gain (Grescale) and bias (Brescale) rescaling factors.For L7 ETM+ data, the Qcal-to-Lλ conversion is summarizedin the L7 Science Data User’s Handbook [18]. For UK-DMCSLIM-6 data, the Qcal-to-Lλ conversion process is given by therelationship

Lλ =Qcal

Grescale+ Brescale

Where :

Grescale =255

LMAXλ − LMINλ

Brescale = LMINλ.

The scaling coefficients (rescale gain and rescale bias) areunique for every image, and these unique coefficients arestored in the metadata files that accompany every L1R andL1T product. The spectral radiance is provided in the unitsof W/(m2 · sr · μm). A single sun elevation angle correctionwas applied, but no radiative transfer codes were applied forestimating gaseous transmittance, no bidirectional functionswere estimated for taking into account surface roughness, andno spectral band adjustments were performed. Two differentplaya regions were taken for result confirmation. The results ofthe comparison for the spectral bands are shown in Fig. 22. Theplots compare the at-sensor spectral radiance extracted fromthe UK-DMC SLIM-6 and L7 ETM+ data. Each data pointon these plots represents an ensemble average of all pixels ina defined region for a given day and spectral band. The one-to-one line represents the idealized perfect agreement betweenthe radiances obtained from both sensors for a particular band.The average percent differences in at-sensor radiance estimatesobtained from the UK-DMC SLIM-6 and L7 ETM+ are within−18% for the green band, 32% for the red band, and 6% forthe NIR spectral band. Additional work needs to be done to


Fig. 21. (Middle) Image chips, (bottom) histograms, and (top) respective 2-D FFT images.

Fig. 22. Comparison of at-sensor radiance (in the units of W/m2 · sr · μm)measurements from large ground regions common to both UK-DMC SLIM-6and L7 ETM+ sensors.

characterize the absolute differences between the two sensorsover the entire mission. This study needs to quantify uncer-tainties due to spectral, spatial, temporal, and atmosphere dif-ferences and should be performed over multiple dates to yieldmore robust results.

V. SUMMARY

Geometric analyses were conducted on eight SSTL UK-DMC SLIM-6 CCD sensor data sets acquired over the RVPN

area. The RVPN site is referenced to the WRS-2 as path 40and row 33. The UK-DMC SLIM-6 images were processedwith the latest geometric improvements to their processingsystem. The I2I characterization was performed to comparethe relative accuracy between the UK-DMC SLIM-6 imageand a reference DOQ. The UK-DMC SLIM-6 images weretypically registered to within 1.0–1.5 pixels to the DOQ mosaicimages. The rmse measured between the UK-DMC SLIM-6image and the reference DOQ data sets ranged from 7.03 to23.53 m (0.22–0.74 pixels) in the X-direction and from 26.20to 36.67 m (0.82–1.15 pixels) in the Y -direction. The B2Bcharacterization was performed to check the band alignment forthe UK-DMC SLIM-6 images. The rmse band alignment offsetsmeasured within the UK-DMC SLIM-6 data sets had values ofup to 12.03 m (0.37 pixels) in the line direction and 20.03 m(0.62 pixels) in the sample direction. The preliminary resultsshow that the data from the UK-DMC SLIM-6 sensor meet thespecifications and can be used to support remote sensing ap-plications. Several radiometric artifacts like striping, coherentnoise, and flat detector were discovered and studied. Indicationsare that the SSTL UK-DMC SLIM-6 data have few artifacts andcalibration challenges, and these can be adjusted or correctedvia calibration and processing algorithms. The cross-calibrationof the L7 ETM+ and UK-DMC SLIM-6 was performed usingimage statistics derived from large common areas observed bythe two sensors. The average percent differences in at-sensor


radiance estimates obtained from the ETM+ and SLM-6 arewithin −18% for the green band, 32% for the red band, and 6%for the NIR spectral band. A full radiometric analysis of SSTLsatellite data would require a dark or nighttime data acquisitionand/or data from any dedicated calibration sources aboard thesatellite.

ACKNOWLEDGMENT

Satellite data from the Surrey Satellite Technology LTD(SSTL) Disaster Monitoring Constellation (DMC) were pro-vided under Technical Assistance Agreement UK-08.0000,ACIS Reference ID # 8512 between the USGS and SSTL datedSeptember 29, 2005. Any use of trade, product, or firm names isfor descriptive purposes only and does not imply endorsementby the U.S. Government.

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Gyanesh Chander (M’02) received the M.S. degreein electrical engineering from South Dakota StateUniversity, Brookings, in 2001.

He is currently a Lead Systems Engineer withStinger Ghaffarian Technologies, Inc., Greenbelt,MD, contractor to the U.S. Geological Survey(USGS) Earth Resources Observation and Science(EROS) Center, Sioux Falls, SD. His primary respon-sibilities at EROS include satellite sensor character-ization and calibration research to support ongoingradiometric projects. His current research focuses on

cross-calibration between various sensors from different platforms for missioncontinuity, thereby providing consistent measurements of Earth’s surface fea-tures. For the past nine years, he has worked extensively with the NationalAeronautics and Space Administration, European Space Agency, Indian SpaceResearch Organization, and Instituto Nacional de Pesquisas Espaciais in thearea of radiometric characterization and calibration of satellites and airbornesensors. He has played a pivotal role in the development of the LandsatThematic Mapper Image Assessment System and the EO-1 Advanced LandImager Image Assessment System.

Mr. Chander is a member of the international Committee of Earth Obser-vation Satellites and actively participates in the Working Group CalibrationValidation and Infrared Visible and Optical Sensor’s subcommittee meetings.He is leading the Group on Earth Observations task DA-09-01a_2 to establisha catalog of prime candidate worldwide test sites for the postlaunch characteri-zation and calibration of space-based imaging sensors.

Sebastien Saunier received the M.S. degree in ap-plied mathematics from Jussieu Paris VII University,Paris, France, and the second M.S. degree in sig-nal processing from École Nationale Supérieure del’Electronique et de ses Applications School, CergyPontoise, France, in 1999 and 2001, respectively.

For the past five years, he has been an EarthObservation Application Engineer for optical sensorwith GAEL Consultant, Champs-sur-Marne, France,in the frame of European Space Agency (ESA)European Space Research Institute (ESRIN)

projects. His current activities are in the area of radiometric, geometric andspatial resolution, calibration, validation, and quality control.

Michael J. Choate (S’92–M’93) received the B.S.degree in electrical engineering and the M.S. degreein engineering from South Dakota State University,Brookings, in 1990 and 1994, respectively.

He is currently with Stinger Ghaffarian Technolo-gies, Inc., Greenbelt, MD, contractor to the U.S.Geological Survey (USGS) Earth Resources Obser-vation and Science (EROS) Center, Sioux Falls, SD.His current work includes the geometric calibra-tion and characterization of satellite and airborneinstruments.

Pasquale L. Scaramuzza received the B.S. degreein physics from Drexel University, Philadelphia, PA,in 1990, and the M.S. degree in physics from TempleUniversity, Philadelphia, in 1993.

He is currently with Stinger Ghaffarian Technolo-gies, Inc., Greenbelt, MD, contractor to the U.S.Geological Survey (USGS) Earth Resources Obser-vation and Science (EROS) Center, Sioux Falls, SD.He is a Radiometric Analyst working on the Landsat7 image assessment system, where he performs thedaily checks of the data and instrument calibrations,

performs analyses on the radiometric performance of the instrument, andupdates calibration parameters.

sstl uk-dmc slim-6 data quality assessment

Documents

stinger ghaffarian

km base elevation

earth resources

disaster monitoring

european space

enhanced thematic

average percent

deep space