The DLR Earth Sensing Spectrometer (DESIS) on board the International Space Station (ISS) has been providing high quality hyperspectral data to the scientific community and commercial users since the start of operations in September 2018. After almost 4 years in orbit, the DESIS instrument continues to operate correctly and to deliver hyperspectral data products for a wide variety of applications. In order to support this successful activity, the calibration team regularly analyzes the instrument data and provides updates using vicarious calibration. We present here the latest results from the DES IS vicarious calibration and our plans for future improvements

Alonso, Kevin

Bachmann, Martin

Burch, Kara

Carmona, Emiliano

Cerra, Daniele

de los Reyes, Raquel

Heiden, Uta

Knodt, Uwe

Krutz, David

Marshall, David

Müller, Rupert

Reinartz, Peter

Institute of Transport Research:Publications

VICARIOUS CALIBRATION OF THE DESIS IMAGING SPECTROMETER:STATUS AND PLANSE. Carmona1, K. Alonso1, M. Bachmann2, K. Burch3, D. Cerra1, R. de los Reyes1, U. Heiden1U. Knodt4, D. Krutz5, D. Marshall1, R. Müller1, P. Reinartz11Remote Sensing Technology Institute, DLR, Oberpfaffenhofen, 82234 Wessling, Germany2German Remote Sensing Data Center, DLR, Oberpfaffenhofen, 82234 Wessling, Germany3Innovative Imaging and Research, Corp. (I2R), Stennis Space Center, MS 39529, US4Strategic services, DLR, Linder Höhe, 51147 Köln, Germany5Institute of Optical Sensor Systems, DLR, Rutherfordstrasse 2, 12489 Berlin, GermanyABSTRACTThe DLR Earth Sensing Spectrometer (DESIS) on board theInternational Space Station (ISS) has been providing highquality hyperspectral data to the scientific community andcommercial users since the start of operations in September2018. After almost 4 years in orbit, the DESIS instrumentcontinues to operate correctly and to deliver hyperspectraldata products for a wide variety of applications. In orderto support this successful activity, the calibration team reg-ularly analyzes the instrument data and provides updatesusing vicarious calibration. We present here the latest resultsfrom the DESIS vicarious calibration and our plans for futureimprovements.Index Terms— Remote Sensing, Hyperspectral, Space-borne, Vicarious Calibration1. INTRODUCTIONThe DESIS instrument was built by the German AerospaceAgency (DLR) who also provides the processing softwarethat produces the DESIS data products. It is installed on boardthe ISS in one of the 4 slots of the MUSES platform [1]. Tele-dyne Brown Engineering built and operates this platform aswell as it operates the DESIS instrument. DESIS is a push-broom imaging spectrometer observing in the VNIR range(400 − 1000 nm) that offers a spectral sampling distance of2.55 nm. A full description of the instrument and its designcan be found in [2]. Figure 1 shows an schematic view of theDESIS instrument and some of its components.The DESIS image products consist of 235 spectral bands× 1024 spatial, across-track pixels that are divided every 1024along-track pixels into so-called tiles. Users can order DESISproducts with three different processing levels (L1B, L1C,L2A) and different processing options. A complete descrip-tion of the DESIS data products and DESIS performance canbe found in [3]. DESIS products are used in various appli-Fig. 1. The DESIS Instrument and its main components.cations by a growing community of DESIS users, who heldan initial user workshop in September 2021. For more detailson the access to the DESIS data products and the applicationsusing them see [4].DESIS calibration is based on the use of vicarious cali-bration with support from the on-board LED calibration mea-surements. The instrument was calibrated on-ground [5] andvalidated during the commissioning phase [3] with an earlyversion of the vicarious calibration. Since then, the vicariouscalibration process has been optimized and newer calibrationtables are produced regularly, specially to update the radio-metric calibration of the instrument. This was the case alsofor other spaceborne imaging spectrometers like HICO [6],which shows the validity of this approach in the context ofhyperspectral missions.The on-board calibration unit is mainly used to performsmall updates on the spectral calibration. Figure 2 shows therelative variation of the pixel central wavelengths obtainedfrom the on-board spectral calibration analysis. The datashow that after a first continuous variation at a rate of 0.2 nmper year, the central wavelength values are stable. Until nowthe only update required on the spectral calibration has beena global shift of 0.1 nm.Fig. 2. Relative spectral stability of the DESIS instrumentfrom several on-board calibration measurements performedbetween January 2019 and October 2020.2. VICARIOUS CALIBRATION OF THE DESISINSTRUMENTThe variation of the instrument’s response over time requiresthe update of the calibration coefficients on a regular basis.The main updates are performed on the radiometric calibra-tion coefficients using our vicarious calibration method [7].As input we use good quality DESIS scenes acquired overdifferent areas. Two types of input scenes are used in ourvicarious calibration:• Uniform scenes, typically desert areas that offer gooduniformity within an image tile. Examples of these ar-eas are the CEOS PICS sites, although in our case tem-poral stability is not required for the scenes. These dataare averaged on the along-track direction to obtain amean focal plane response for each scene that is laterused in a sequence of processing steps (for more de-tails see [7]) to achieve the equalization of the sensorresponse.• RadCalNet [8] scenes over the sites of Gobabeb, Rail-road Valley and La Crau that are used to adjust the ab-solute radiometric calibration within a given calibrationperiod.RadCalNet (RCN) observations are regularly scheduledover the pre-selected RCN sites to be used in our vicariouscalibration. In the case of the uniform scenes, no special tar-gets are scheduled and we simply select suitable images fromthe DESIS data archive.The duration of a period is chosen by taking into accountthe sensor performance changes and the availability of datato perform a new calibration. A total of 3 periods have beendefined up to now. A fourth period starting on the second halfof 2021 is in preparation (see section 4). Given the availabil-ity of suitable scenes, Period #2 was defined shorter in orderto study the advantages of reducing the duration of the pe-riods. In this case no significant difference in performancewas observed with respect to Periods #1 or #3, except for thewavelength range under 450 nm where the sensor shows thehighest variability. On the other hand, shorter periods willface the problem of data availability and will increase the ef-fort to maintain the vicarious calibration. An overview of thenumber of scenes of each type used in the vicarious calibra-tion of the different periods is shown in figure 3.Fig. 3. Calibration periods defined in the DESIS and the dif-ferent scenes used.Up to now only period #2 includes a global spectral shift(see figure 2) in addition to the radiometric update. The effectof this spectral shift on the radiometric coefficients is rathersmall compared with their typical variation over time in theperiods with no spectral shift.3. LATEST RESULTSFor each DESIS pixel (i, j) in the focal plane, the signal valueis converted to radiance with the calibration coefficients (Ci,j)obtained from the relative pixel calibration steps in the vi-carious calibration and the original laboratory coefficients.A simple expression provides the radiance values as Li,j =Ci,j · (DNi,j − DN0i,j) where DNi,j is the measured sen-sor value, DN0i,j is the dark current value and Ci,j is the up-dated calibration factor. We use the ratio of RCN to DESISTOA reflectance in order to compute a per-band coefficient(f corri ) that corrects the bias between DESIS and RCN. Thisis convenient given that TOA reflectance is directly providedby RCN. This factor is applied on the radiance values aftersmile correction (L̃i,j) where an interpolation of the values onthe spectral direction (L̃i,j = fint(Li−2,j , Li−1,j , ..., Li+2,j)is performed (see [3]). The final radiance values are obtainedas L̃finali,j = L̃i,j · f corri .For the absolute calibration task we select only sceneswith Sun zenith angle below 45 degrees and good atmosphericconditions. From a total of 30 RCN scenes in the three cal-ibration periods currently defined, only 19 fulfill this condi-tion. An example of the calculation of the bias correction canbe seen in figure 4 where the TOA reflectance ratio computedfor each band is fitted using a polynomial. The fit is then usedto compute a per-band correction factor that will be used toupdate the individual pixel calibration coefficients. The re-gions with strong atmospheric absorption are excluded fromthe fit (in the figure the black color points).Fig. 4. Example of the absolute calibration adjustment on theDESIS data. Left: Ratio between DESIS TOA reflectanceand RCN TOA reflectance on Period #3 using the originalcalibration coefficients from Period #1. Right: Ratio betweenDESIS TOA reflectance and RCN TOA reflectance on Period#3 once the calibration coefficients have been updated. Thered lines show examples of the polynomial fit to the data.Two main observations can be made from figure 4. First,bands above 450 nm show little variation over a period ofmore than a year between Period #3 and Period #1 (differ-ence typically ≤ 2%). Second, bands below 450 nm showan important degradation over the same amount of time. It ismaximum at 400 nm, with a rate of change around 20%/year,and it reduces continuously until disappearing in the range460− 480 nm.Figure 5 shows the ratio of TOA reflectances for the 19measurements used for the radiometric update, after calibra-tion is updated for each period. In order to reduce the system-atic errors, two estimates of the TOA reflectance ratio are av-eraged in our calculations. One is computed using directly theRCN TOA values of reflectance and corresponds to a spectralsampling distance of 10 nm (figure 5 left). The other one iscomputed by ourselves from the RCN BOA spectra after per-forming an inversion of the atmospheric correction [9] usedin DESIS L2A and corresponds to the spectral sampling dis-tance of the DESIS instrument (figure 5 right).Since the absolute bias of the calibration scenes is ad-justed to match the RCN data, it is not possible to use thismetric for our second purpose, the estimation of the calibra-tion performance. What we use instead are the RMS valuesobtained from the comparison with RCN. The value obtainedfrom the 19 calibration scenes is between 3% and 4%, outsideFig. 5. Top: ratio of TOA reflectances between RCN andDESIS for the TOA reflectance provided by RCN (left) andcomputed by us (right). The black lines show the 19 individ-ual scenes used for calibration purposes while the color linecorresponds to their mean value. Bottom: RMS values com-puted from the corresponding top plots.the strong atmospheric absorption regions and above 450 nm.In addition, we look at the performance of the calibration forthe full dataset of RCN scenes (30 scenes) that include thosewith Sun zenith angle above 45 degrees as well as those withnot optimal atmospheric conditions. The results after ana-lyzing the full dataset can be seen in figure 6. In this casewe notice that while the bias is not significantly affected, theRMS is now increased to an average value around 4%. Theseresults agree well with those from independent investigationsusing DESIS and RCN data as conducted in [10] and [11].Fig. 6. Top: ratio of TOA reflectances between RCN andDESIS for the TOA reflectance provided by RCN (left) andcomputed by us (right). The black lines show the total of 30available scenes and the color line corresponds to their meanvalue. Bottom: Root Mean Square values computed from thecorresponding top plots.In both datasets (calibration and full one) we observe thatthe RMS performance degrades quickly as the wavelength re-duces below 450 nm. Our current approach using calibrationperiods can adjust the calibration coefficients to correct themean bias of each period but can’t reduce the dispersion be-low 450 nm due to the rapid change of performance. Thereason for this degradation is not known yet, but we suspectit could be caused by a degradation on the coating of the mir-rors, more specifically of the mirror in the Pointing Unit. Thenext section presents our plans to address this limitation.4. FUTURE PLANSOur calibration strategy was designed to support small instru-ment changes over time or sudden larger changes at well iden-tified intervals. However, the rapid change in performance inregion below 450 nm is not well handled by this approachand requires a different strategy. The sparse RCN acquisi-tions do not allow us to build a detailed model based only onthem. Given this, we plan to use the on-board LED calibra-tion data to build a 2D model of the sensor response changesover time for the different spectral bands and across-track pix-els. Our investigations indicate that this performance degra-dation is constant in time although the magnitude varies forthe different across-track elements in addition to the differentmagnitude at different wavelengths. The difference between amodel with linearly changing calibration coefficients and ourcurrent approach is illustrated in figure 7. From this illustra-tion one can see that the existing approach introduces largercalibration errors at the edges of the calibration periods andit creates artificial calibration jumps when changing from oneperiod to the next. We plan to introduce this change togetherwith a new calibration period once the analysis of all the datais concluded.Although there are certain difficulties in the developmentof such a calibration model and its application to the data fromall periods, we expect that this would improve the calibrationperformance below 450 nm. This would also improve the cal-ibration performance for new acquisitions, provided that thevalidity of the sensor changes model continues to apply.Fig. 7. Illustration of the difference between current calibra-tion approach and linear calibration update model.5. REFERENCES[1] R. Perkins and P. Galloway et al., “Teledyne’s MUSESmission on the ISS: Enabling flexible and reconfigurableearth observation from space,” in 2017 IEEE Inter-national Geoscience and Remote Sensing Symposium(IGARSS), 2017, pp. 1177–1180.[2] D. Krutz, R. Müller, and U. Knodt et al., “The Instru-ment Design of the DLR Earth Sensing Imaging Spec-trometer (DESIS),” Sensors, vol. 19, pp. 1622, 2019.[3] K. Alonso, M. Bachmann, and K. Burch et al., “DataProducts, Quality and Validation of the DLR Earth Sens-ing Imaging Spectrometer (DESIS),” Sensors, vol. 19,no. 20, pp. 4471, 2019.[4] D. Cerra, D. Marshall, and U. Heiden et al., “The space-borne imaging spectrometer desis: Data access, out-reach activities, and scientific applications,” in 2022IEEE International Geoscience and Remote SensingSymposium IGARSS, 2022.[5] I. Sebastian, D. Krutz, and A. Eckardt et al., “On-groundcalibration of DESIS: DLR’s Earth Sensing ImagingSpectrometer for the International Space Station (ISS),”in Optical Sensing and Detection V, Francis Berghmansand Anna G. Mignani, Eds. International Society forOptics and Photonics, 2018, vol. 10680, pp. 1 – 12,SPIE.[6] Bo-Cai Gao, Rong-Rong Li, and Robert L. Lucke et al.,“Vicarious calibrations of HICO data acquired from theinternational space station,” Appl. Opt., vol. 51, no. 14,pp. 2559–2567, May 2012.[7] E. Carmona, K. Alonso, and M. Bachmann et al., “Vi-carious calibration of the desis imaging spectrometer,”in 2021 IEEE International Geoscience and RemoteSensing Symposium IGARSS, 2021, pp. 1611–1614.[8] M. Bouvet, K. Thome, and B. Berthelot et al., “RadCal-Net: A Radiometric Calibration Network for Earth Ob-serving Imagers Operating in the Visible to ShortwaveInfrared Spectral Range,” Remote Sensing, vol. 11, no.20, 2019.[9] R. de los Reyes, M. Langheinrich, and P. Schwind et al.,“PACO: Python-Based Atmospheric Correction,” Sen-sors, vol. 20, no. 5, 2020.[10] M. Shrestha, D. Helder, and J. Christopherson, “Dlrearth sensing imaging spectrometer (desis) level 1 prod-uct evaluation using radcalnet measurements,” RemoteSensing, vol. 13, no. 12, 2021.[11] M. Shrestha, A. Sampath, and S.N. Ramaseri Chandraet al., “System characterization report on the germanaerospace center (dlr) earth sensing imaging spectrome-ter (desis),” System characterization of Earth observa-tion sensors: U.S. Geological Survey Open-File Report2021-1030, 9 p.

Vicarious Calibration of the DESIS Imaging Spectrometer: Status and Plans

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