The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2σ). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment

Choate, Michael

Dwyer, John

Gascon, Ferran

Masek, Jeffrey

Roy, David P.

Storey, James

English

Public Research Access Institutional Repository and Information Exchange

South Dakota State UniversityOpen PRAIRIE: Open Public Research Access InstitutionalRepository and Information ExchangeGSCE Faculty Publications Geospatial Sciences Center of Excellence (GSCE)12-2016A Note on the Temporary Misregistration ofLandsat-8 Operational Land Imager (OLI) andSentinel-2 Multi Spectral Instrument (MSI)ImageryJames StoreyU.S. Geological Survey, james.storey.ctr@usgs.govDavid P. RoySouth Dakota State University, david.roy@sdstate.eduJeffrey MasekNASA Goddard Space Flight, jeffrey.g.masek@nasa.govFerran GasconEuropean Space Agency, ferran.gascon@esa.intMichael ChoateU.S. Geological Survey, michael.choate.ctr@usgs.govFollow this and additional works at: http://openprairie.sdstate.edu/gsce_pubsPart of the Geographic Information Sciences Commons, Remote Sensing Commons, and theSpatial Science CommonsThis Article is brought to you for free and open access by the Geospatial Sciences Center of Excellence (GSCE) at Open PRAIRIE: Open PublicResearch Access Institutional Repository and Information Exchange. It has been accepted for inclusion in GSCE Faculty Publications by an authorizedadministrator of Open PRAIRIE: Open Public Research Access Institutional Repository and Information Exchange. For more information, pleasecontact michael.biondo@sdstate.edu.Recommended CitationStorey, James; Roy, David P.; Masek, Jeffrey; Gascon, Ferran; and Choate, Michael, "A Note on the Temporary Misregistration ofLandsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery" (2016). GSCE FacultyPublications. 35.http://openprairie.sdstate.edu/gsce_pubs/35A note on the temporary misregistration of Landsat-8 Operational LandImager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imageryJames Storey a,⁎, David P. Roy b, Jeffrey Masek c, Ferran Gascon d, John Dwyer e, Michael Choate aa Stinger Ghaffarian Technologies, Contractor to the U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD, USAb Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD, USAc Biospheric Sciences Laboratory, National Aeronautics and Space Administration (NASA) Goddard Space Flight Center, Greenbelt, MD, USAd European Space Agency (ESA), European Space Research Institute (ESRIN), Frascati, Italye U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center, SD, USAa b s t r a c ta r t i c l e i n f oArticle history:Received 31 May 2016Received in revised form 26 July 2016Accepted 12 August 2016Available online 20 August 2016The Landsat-8 and Sentinel-2 sensors providemulti-spectral image data with similar spectral and spatial charac-teristics that together provide improved temporal coverage globally. Both systems are designed to register Level1 products to a reference image framework, however, the Landsat-8 framework, based upon theGlobal Land Sur-vey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38m(2σ). Thesemisalignments vary geographically but should be stable for a given area. The Landsat frameworkwillbe readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. Inthe interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of inter-est and if appropriate to reproject the data to better alignment.© 2016 Elsevier Inc. All rights reserved.Keywords:LandsatSentinel-2Image registration1. IntroductionModerate spatial resolution (10 to 30 m) satellite data from thepolar-orbiting sun-synchronous Landsat-8 and Sentinel-2 sensors to-gether provide the opportunity for improved mapping and monitoringof the Earth's surface [Drusch et al., 2012; Roy et al., 2014]. These dataadvance the Committee on Earth Observation Satellites (CEOS) virtualconstellation paradigm as they have similar spatial and spectral charac-teristics that can be managed together to provide improved temporalcoverage globally [Wulder et al., 2015]. The absolute geolocation perfor-mance speciﬁcation for Sentinel-2 is 12.5 m (2σ) [Trémas et al., 2015]and for Landsat-8 is 12 m (90% circular error) [Storey et al., 2014]. Ourrecent global analysis indicates that the Sentinel-2 and Landsat-8 dataare misaligned relative to each other by 38 m (2σ), i.e., by more thanthree Sentinel-2 10-meter pixels and more than a Landsat-8 30-meterpixel. As discussed below, the degree of misalignment varies geograph-ically. The purpose of this short communication is to (i) inform the usercommunity of this issue, (ii) clarify its cause, and (iii) clarify the sched-ule for its resolution.2. Cause of the sensor misregistrationThe standard geometrically corrected Sentinel-2 data are available asLevel-1C (L1C) top-of-atmosphere (TOA) reﬂectance tiles [ESA, 2015]and theequivalent Landsat-8 data are available as Level-1T (L1T) TOA re-ﬂectance images deﬁned in the Worldwide Reference System (WRS-2)path/row coordinate system [Irons et al., 2012]. Both sensor geolocationsystems use measurements of the sensor exterior orientation (attitudeand position), combined with sensor and digital elevation models, toprecisely geolocate every sensed instantaneous ﬁeld of view. TheLandsat-8 L1T products have improved geometric ﬁdelity compared toprevious Landsat missions because of the Landsat-8 pushbroom sensordesign and because the satellite has a fully operational onboard globalpositioning system (GPS) and an attitude determination system thatuses a star-tracker and inertial measurement unit tomeasure the exteri-or orientation directly [Storey et al., 2014; Roy et al., 2014]. Similarly, theSentinel-2 uses a pushbroom sensor and has onboard GPS, three star-trackers and an inertial measurement unit [Languille et al., 2015].Both sensor geolocation systems are designed to use ground controlto improve the geolocation accuracy and repeatability. The Sentinel-2geolocation will use a Global Reference Image (GRI) derived fromorthorectiﬁed Sentinel-2 cloud-free images [Déchoz et al., 2015]. Dueto the phased Sentinel-2 global acquisition schedule and because ofthe need to obtain cloud-free imagery, the GRI is still being assembledand is scheduled for completion by the last quarter of 2017. TheLandsat-8 geolocation uses a global sample of ground control points[Storey et al., 2014] derived for each WRS-2 path/row of circa 2000Remote Sensing of Environment 186 (2016) 121–122⁎ Corresponding author.E-mail addresses: james.storey.ctr@usgs.gov (J. Storey), david.roy@sdstate.edu(D.P. Roy), jeffrey.g.masek@nasa.gov (J. Masek), ferran.gascon@esa.int (F. Gascon),dwyer@usgs.gov (J. Dwyer), michael.choate.ctr@usgs.gov (M. Choate).http://dx.doi.org/10.1016/j.rse.2016.08.0250034-4257/© 2016 Elsevier Inc. All rights reserved.Contents lists available at ScienceDirectRemote Sensing of Environmentj ourna l homepage: www.e lsev ie r .com/ locate / rseGlobal Land Survey (GLS) Landsat-7 imagery [Gutman et al., 2013]. Theimproved Landsat-8 geolocation accuracy compared to previousLandsat missions has resulted in the identiﬁcation of poorly-geolocatedGLS images [Storey et al., 2014]. This also revealed errors in the GLSframework and is the dominant source of absolute geolocation errorin Landsat-8 data products. The error varies among Landsat WRS-2path/row locations and is the main cause of the relative misalignmentof the Landsat-8 L1T and Sentinel-2 L1C data.3. Expected misregistration magnitudeTo derive an estimate of the expected Sentinel-2 to Landsat-8 mis-registration, the GLS accuracy speciﬁcation of 25 meter radial root-mean-squared error [Rengarajan et al., 2015] was converted to theequivalent 2σ value of 35 m (by multiplying by the square root of 2).The root-sum-square of this result with the observed Sentinel-2 accura-cy (without GRI ground control) of 14.6 m (2σ) [ESA, 2016] yields a38 meter (2σ) expected registration accuracy between the sensors.This estimate may be pessimistic since Landsat-8 analysis of the accura-cy of the GLS framework suggests that the GLS is somewhat more accu-rate than speciﬁed [Storey et al., 2014]. However, a pessimistic valueallows for some additional misregistration contribution due to the sen-sor speciﬁc impact of digital elevationmodel height errors on the Senti-nel-2 and Landsat-8 viewing geometries.4. Schedule for correction of the sensor misregistrationA program to improve the accuracy of the GLS framework for prob-lematic Landsat WRS-2 path/row locations began in 2014 [Storey et al.,2014]. This effort targetedpath/row locationswhere theGLS frameworkwas determined to contain biases of 50 m or more, with a goal to im-prove the accuracy to 25 m or better, while maintaining consistencywith adjacent regions. The accuracy improvement was achieved by tri-angulating blocks of Landsat-8 images to establish updated positions forthe existing GLS control points and to extract new control points whereneeded. This effort included the readjustment of the GLS data in Austra-lia to tie it to the Australian Geographic Reference Image (AGRI) [Lewiset al., 2011] using sparse AGRI tie points to control the Landsat-8 blocktriangulation. An expansion of this activity will apply the samemethodsglobally, to tie the GLS to the Sentinel-2 GRI. The completion of this ac-tivity is dependent upon the availability of the ﬁnal Sentinel-2 GRI andtherefore is not scheduled for global availability until the secondquarterof 2018. An improved global digital elevationmodel, based upon the re-sults of the NASADEM development activity [Crippen et al., 2016], isplanned for implementation in the Landsat product generation systemin the same timeframe. Thereafter, the Landsat-8 L1T data will bereprocessed as part of a new Landsat-8 collection and will align tosub-pixel precision with contemporaneous Sentinel-2 L1C data thatare processed using the GRI.Based upon the results of theAustralian readjustment and themulti-temporal registration of Landsat-8 L1T products, we anticipate Landsat-8 to Sentinel-2 registration accuracy on the order of 10m (2σ) or better.Unfortunately, this high degree of co-registration will only be achievedonce archived Landsat-8 and Sentinel-2 data have been reprocessedusing the updated GLS and ﬁnal GRI, respectively. This could take untilthe end of 2018 for Landsat-8, and the schedule for reprocessingexisting Sentinel-2 data once the ﬁnal GRI is released, has not yet beenestablished.The GLS framework is used as the control reference for L1T productsfrom all Landsat missions to ensure multi-temporal registration acrossthe Landsat archive. As has been the case throughout the GLS accuracyimprovement effort, when the GLS control reference is updated, all af-fected products across the Landsat archive are reprocessed to maintainthe geometric integrity of the archive. The improved absolute accuracyand registration to Sentinel-2 will thus be carried backward in time toprovide multi-temporal as well as multi-sensor registration.5. Implications for data usersUsers who wish to combine contemporaneous Landsat-8 and Senti-nel-2 data should be aware of the misregistration issue reported in thisnote. The sensor misregistration should be stable for a given site since itis dueprimarily to differences/errors in the sensor geometric control ref-erences. Themisregistration is characterized primarily as a translationaloffset with some secondary scaling differences also possible. For somelocations and applications the sensor misregistration may not be anissue. Users who wish to improve alignment between Landsat and Sen-tinel-2 Level 1 products may use manual methods of picking tie pointsand resampling one image to the other (common to most image pro-cessing packages), or use other, automated image-to-image registrationapproaches [Gao et al., 2009; Long et al., 2016, Yan et al., 2016].Acknowledgments and dataData supporting the analysis can be found in the references.Funding: This research was funded by the NASA Land Cover/LandUse Change (LCLUC14-2), Multi-Source Land Imaging Science Program[Grant NNX15AK94G], and by the U.S. Department of the Interior, U.S.Geological Survey (USGS), [Grant G12PC00069 andUSGS contract num-ber G15PC00012].The authors declare no conﬂicts of interest.ReferencesCrippen, R., et al., 2016. NASADEM global elevation model: methods and progress. Int.Arch. Photogramm. Remote. Sens. Spat. Inf. Sci. XLI-B4, 125–128. http://dx.doi.org/10.5194/isprs-archives-XLI-B4-125-2016.Déchoz, C., et al., 2015. Sentinel-2 global reference image. Proc. SPIE 9643, Image and Sig-nal Processing for Remote Sensing XXI, p. 96430A. http://dx.doi.org/10.1117/12.2195046.Drusch, M., et al., 2012. Sentinel-2: ESA's optical high-resolution mission for GMES oper-ational services. Remote Sens. Environ. 120, 25–36. http://dx.doi.org/10.1016/j.rse.2011.11.026.European Space Agency (ESA), 2015. Sentinel-2 Products Speciﬁcation Document (Issue13.1, ESA REF: S2-PDGS-TAS-DI-PSD, Date 18/11/2015, 496 pages).European Space Agency (ESA), 2016. Sentinel-2 Data Quality Report (Issue 05, ESA REF:S2-PDGS-MPC-DQR, Date 11 July 2016, 20 pages).Gao, F., Masek, J.G., Wolfe, R.E., 2009. An automated registration and orthorectiﬁcationpackage for Landsat and Landsat-like data processing. J. Appl. Remote. Sens. 3,033515. http://dx.doi.org/10.1117/1.3104620 (Software implementation availableat: http://www.ars.usda.gov/services/software/download.htm?softwareID=364).Gutman, G., Huang, C., Chander, G., Noojipady, P., Masek, J.G., 2013. Assessment of theNASA–USGS global land survey (GLS) datasets. Remote Sens. Environ. 134,249–265. http://dx.doi.org/10.1016/j.rse.2013.02.026.Irons, J.R., Dwyer, J.L., Barsi, J.A., 2012. The next Landsat satellite: the Landsat Data Conti-nuity Mission. Remote Sens. Environ. 122, 11–21. http://dx.doi.org/10.1016/j.rse.2011.08.026.Languille, F., Déchoz, C., Gaudel, A., Greslou, D., de Lussy, F., Trémas, T., Poulain, V., 2015.Sentinel-2 geometric image quality commissioning: ﬁrst results. Proc. SPIE 9643,Image and Signal Processing for Remote Sensing XXI, p. 964306. http://dx.doi.org/10.1117/12.2194339.Lewis, A., Wang, L.-W., Coghlan, R., 2011. AGRI: The Australian Geographic ReferenceImage: A Technical Report. Geoscience Australia, Canberra, Australia.Long, T., Jiao,W., He, G., Zhang, Z., 2016. A fast and reliablematchingmethod for automat-ed georeferencing of remotely-sensed imagery. Remote Sens. 8 (1), 56. http://dx.doi.org/10.3390/rs8010056.Rengarajan, R., Sampath, A., Storey, J., Choate, M., 2015. Validation of geometric accuracyof Global Land Survey (GLS) 2000 data. Photogramm. Eng. Remote. Sens. 81 (2),131–141. http://dx.doi.org/10.14358/PERS.81.2.131.Roy, D.P., et al., 2014. Landsat-8: science and product vision for terrestrial global changeresearch. Remote Sens. Environ. 145, 154–172. http://dx.doi.org/10.1016/j.rse.2014.02.001.Storey, J., Choate, M., Lee, K., 2014. Landsat-8 Operational Land Imager on-orbit geometriccalibration and performance. Remote Sens. 6 (11), 11127–11152. http://dx.doi.org/10.3390/rs61111127.Trémas, T., Déchoz, C., Lacherade, S., Nosavan, J., Petrucci, B., 2015. Sentinel-2: presenta-tion of the CAL/VAL commissioning phase. Proc. SPIE 9643, Image and Signal Process-ing for Remote Sensing XXI 964309. http://dx.doi.org/10.1117/12.2194847.Wulder, M.A., Hilker, T., White, J.C., Coops, N.C., Masek, J.G., Pﬂugmacher, D., Crevier, Y.,2015. Virtual constellations for global terrestrial monitoring. Remote Sens. Environ.170, 62–76. http://dx.doi.org/10.1016/j.rse.2015.09.001.Yan, L., Roy, D.P., Zhang, H., Li, J., Huang, H., 2016. An automated approach for sub-pixelregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2Multi SpectralInstrument (MSI) imagery. Remote Sens. 8 (6), 520. http://dx.doi.org/10.3390/rs8060520.122 J. Storey et al. / Remote Sensing of Environment 186 (2016) 121–122

A Note on the Temporary Misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery

The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2sigma). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment

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A Note on the Temporary Misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery

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