The Harmonized Landsat and Sentinel-2 surface reflectance data set

Remote Sensing of Environment

Volumn 219, Issue , 2018, Pages 145-161

  Claverie, Martin ^a,b   Ju, Junchang ^a,b   Masek, Jeffrey G ^b   Dungan, Jennifer L ^c   Vermote, Eric F ^b   Roger, Jean Claude ^a,b   Skakun, Sergii V ^a,b   Justice, Christopher ^a  

^a UNIVERSITY OF MARYLAND   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

^c NASA AMES RESEARCH CENTER   (United States)

Author keywords

Analysis Ready Data; Harmonization; Landsat; Sentinel 2; Surface reflectance; Virtual Constellation

Indexed keywords

NASA; QUALITY ASSURANCE; RADIOMETERS; REFLECTION; REMOTE SENSING; TIME SERIES;

ANALYSIS READY DATA; HARMONIZATION; LANDSAT; SENTINEL-2; SURFACE REFLECTANCE; VIRTUAL CONSTELLATION;

DISTRIBUTION FUNCTIONS;

BIDIRECTIONAL REFLECTANCE; DATA PROCESSING; DATA QUALITY; DATA SET; ERROR ANALYSIS; HARMONIC ANALYSIS; LANDSAT; MODIS; NADIR; SATELLITE DATA; SENTINEL; SPATIAL RESOLUTION; SURFACE REFLECTANCE;

EID: 85053595296     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2018.09.002     Document Type: Article

References (74)

1. Becker-Reshef, I., Justice, C., Sullivan, M., Vermote, E., Tucker, C., Anyamba, A., Small, J., Pak, E., Masuoka, E., Schmaltz, J., Hansen, M., Pittman, K., Birkett, C., Williams, D., Reynolds, C., Doorn, B., Monitoring global croplands with coarse resolution earth observations: the Global Agriculture Monitoring (GLAM) project. Remote Sens. 2 (2010), 1589–1609.
2. Bégué, A., Arvor, D., Bellon, B., Betbeder, J., de Abelleyra, D., Ferraz, R., Lebourgeois, V., Lelong, C., Simões, M., Verón, S.R., Remote sensing and cropping practices: a review. Remote Sens., 2018, 10.
3. Breon, F.-M., Vermote, E., Correction of MODIS surface reflectance time series for BRDF effects. Remote Sens. Environ. 125 (2012), 1–9.
4. Breon, F., Vermote, E., Murphy, E., Franch, B., Measuring the directional variations of land surface reflectance from MODIS. IEEE Trans. Geosci. Remote Sens., 2015, 1–12.
5. CEOS, CEOS Analysis Ready Data for Land (CARD4L) Description Document. 2016.
6. Chander, G., Mishra, N., Helder, D.L., Aaron, D.B., Angal, A., Choi, T., Xiong, X., Doelling, D.R., Applications of spectral band adjustment factors (SBAF) for cross-calibration. IEEE Trans. Geosci. Remote Sens. 51 (2013), 1267–1281.
7. Claverie, M., Demarez, V., Duchemin, B., Hagolle, O., Ducrot, D., Marais-Sicre, C., Dejoux, J.-F., Huc, M., Keravec, P., Beziat, P., Fieuzal, R., Ceschia, E., Dedieu, G., Maize and sunflower biomass estimation in southwest France using high spatial and temporal resolution remote sensing data. Remote Sens. Environ., 124, 2012.
8. Claverie, M., Vermote, E., Franch, B., He, T., Hagolle, O., Kadiri, M., Masek, J., Evaluation of medium spatial resolution BRDF-adjustment techniques using multi-angular SPOT4 (Take5) acquisitions. Remote Sens., 7, 2015, 12057.
9. Claverie, M., Vermote, E., Franch, B., Masek, J., Evaluation of the Landsat-5 TM and Landsat-7 ETM + surface reflectance products. Remote Sens. Environ. 169 (2015), 390–403.
10. Dechoz, C., Poulain, V., Massera, S., Languille, F., Greslou, D., de Lussy, F., Gaudel, A., L'Helguen, C., Picard, C., Tremas, T., Sentinel 2 global reference image. Conference on Image and Signal Processing for Remote Sensing XXI. Toulouse, France, 2015.
11. Doxani, G., Vermote, E., Roger, J.-C., Gascon, F., Adriaensen, S., Frantz, D., Hagolle, O., Hollstein, A., Kirches, G., Li, F., Louis, J., Mangin, A., Pahlevan, N., Pflug, B., Vanhellemont, Q., Atmospheric correction inter-comparison exercise. Remote Sens., 10(2), 2018, 352.
12. Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., Meygret, A., Spoto, F., Sy, O., Marchese, F., Bargellini, P., Sentinel-2: ESA's optical high-resolution mission for GMES operational services. Remote Sens. Environ. 120 (2012), 25–36.
13. Egorov, V.A., Roy, P.D., Zhang, K.H., Hansen, C.M., Kommareddy, A., Demonstration of percent tree cover mapping using Landsat analysis ready data (ARD) and sensitivity with respect to Landsat ARD processing level. Remote Sens., 10, 2018.
14. ESA, Sentinel-2 User Handbook. 2015.
15. ESA, Data Quality Report S2-PDGS-MPC-DQR. 2018.
16. Foga, S., Scaramuzza, P.L., Guo, S., Zhu, Z., Dilley, R.D., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Hughes, M.J., Laue, B., Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sens. Environ. 194 (2017), 379–390.
17. Franch, B., Vermote, E.F., Claverie, M., Intercomparison of Landsat albedo retrieval techniques and evaluation against in situ measurements across the US SURFRAD network. Remote Sens. Environ. 152 (2014), 627–637.
18. Gao, F., Masek, J.G., Wolfe, R.E., Automated registration and orthorectification package for Landsat and Landsat-like data processing. J. Appl. Remote. Sens., 3, 2009.
19. Gao, F., He, T., Masek, J.G., Shuai, Y., Schaaf, C.B., Wang, Z., Angular effects and correction for medium resolution sensors to support crop monitoring. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 7 (2014), 4480–4489.
20. Gascon, F., Bouzinac, C., Thépaut, O., Jung, M., Francesconi, B., Louis, J., Lonjou, V., Lafrance, B., Massera, S., Gaudel-Vacaresse, A., Copernicus Sentinel-2A calibration and products validation status. Remote Sens., 9, 2017, 584.
21. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R., Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202 (2017), 18–27.
22. Hagolle, O., Huc, M., Pascual, D.V., Dedieu, G., A multi-temporal method for cloud detection, applied to FORMOSAT-2, VENμS, LANDSAT and SENTINEL-2 images. Remote Sens. Environ. 114 (2010), 1747–1755.
23. Hall, D.K., Riggs, G.A., Salomonson, V.V., DiGirolamo, N.E., Bayr, K.J., MODIS snow-cover products. Remote Sens. Environ. 83 (2002), 181–194.
24. Hansen, M.C., Loveland, T.R., A review of large area monitoring of land cover change using Landsat data. Remote Sens. Environ. 122 (2012), 66–74.
25. Hansen, M., DeFries, R., Townshend, J.R.G., Sohlberg, R., UMD Global Land Cover Classification, 1 Kilometer, 1981–1994, 1.0. 1998, U.o.M. Department of Geography, College Park, Maryland.
26. Ju, J., Roy, D.P., Vermote, E., Masek, J., Kovalskyy, V., Continental-scale validation of MODIS-based and LEDAPS Landsat ETM plus atmospheric correction methods. Remote Sens. Environ. 122 (2012), 175–184.
27. Justice, C., Gutman, G., Vadrevu, K.P., NASA Land Cover and Land Use Change (LCLUC): an interdisciplinary research program. J. Environ. Manag. 148 (2015), 4–9.
28. Kotchenova, S.Y., Vermote, E.F., Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II. Homogeneous Lambertian and anisotropic surfaces. Appl. Opt. 46 (2007), 4455–4464.
29. Languille, F., Dechoz, C., Gaudel, A., Greslou, D., de Lussy, F., Tremas, T., Poulain, V., Sentinel 2 geometric image quality commissioning - first results. Conference on Image and Signal Processing for Remote Sensing XXI. Toulouse, France, 2015.
30. Li, J., Roy, D., A global analysis of Sentinel-2A, Sentinel-2B and Landsat-8 data revisit intervals and implications for terrestrial monitoring. Remote Sens., 9, 2017, 902.
31. Lobell, D.B., The use of satellite data for crop yield gap analysis. Field Crop Res. 143 (2013), 56–64.
32. Louis, J., Debaecker, V., Pflug, B., Main-Knorn, M., Bieniarz, J., Mueller-Wilm, U., Cadau, E., Gascon, F., SENTINEL-2 SEN2COR: L2A processor for users. Ouwehand, L., (eds.) ESA Living Planet Symposium 2016, 2016, Spacebooks Online, 1–8.
33. Loveland, T.R., Dwyer, J.L., Landsat: building a strong future. Remote Sens. Environ. 122 (2012), 22–29.
34. Markham, B.L., Barsi, J.A., Kaita, E., Ong, L., Morfitt, R., Haque, M.O., Radiometric calibration and stability of the Landsat-8 Operational Land Imager (OLI). Conference on Earth Observing Systems XX. San Diego, CA, 2015.
35. Martimort, P., Berger, M., Curnicero, B., Del Bello, U., Fernandez, V., Gascon, F., Silvestrin, P., Spoto, F., Sy, O., Sentinel-2 - The Optical High-resolution Mission for GMES Operational Services. 2007, Esa Bulletin-European Space Agency, 18–23.
36. Masek, J.G., Vermote, E.F., Saleous, N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Kutler, J., Lim, T.K., A Landsat surface reflectance dataset for North America, 1990–2000. IEEE Geosci. Remote Sens. Lett. 3 (2006), 68–72.
37. Melaas, E.K., Friedl, M.A., Zhu, Z., Detecting interannual variation in deciduous broadleaf forest phenology using Landsat TM/ETM plus data. Remote Sens. Environ. 132 (2013), 176–185.
38. Middleton, E.M., Ungar, S.G., Mandl, D.J., Ong, L., Frye, S.W., Campbell, P.E., Landis, D.R., Young, J.P., Pollack, N.H., The earth observing one (EO-1) satellite mission: over a decade in space. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 6 (2013), 243–256.
39. Montanaro, M., Gerace, A., Lunsford, A., Reuter, D., Stray light artifacts in imagery from the Landsat 8 thermal infrared sensor. Remote Sens. 6 (2014), 10435–10456.
40. Nemani, R., NASA Earth Exchange: next generation earth science collaborative. Isprs Bhopal 2011 Workshop Earth Observation for Terrestrial Ecosystem, vol. 38-8, 2011, 17.
41. Pearson, R.K., Outliers in process modeling and identification. IEEE Trans. Control Syst. Technol. 10 (2002), 55–63.
42. Roy, D.P., Borak, J.S., Devadiga, S., Wolfe, R.E., Zheng, M., Descloitres, J., The MODIS land product quality assessment approach. Remote Sens. Environ. 83 (2002), 62–76.
43. Roy, D.P., Lewis, P., Schaaf, C.B., Devadiga, S., Boschetti, L., The global impact of clouds on the production of MODIS bidirectional reflectance model-based composites for terrestrial monitoring. IEEE Geosci. Remote Sens. Lett. 3 (2006), 452–456.
44. Roy, D.P., Ju, J., Lewis, P., Schaaf, C., Gao, F., Hansen, M., Lindquist, E., Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data. Remote Sens. Environ. 112 (2008), 3112–3130.
45. Roy, D.P., Ju, J.C., Kline, K., Scaramuzza, P.L., Kovalskyy, V., Hansen, M., Loveland, T.R., Vermote, E., Zhang, C.S., Web-enabled Landsat Data (WELD): Landsat ETM plus composited mosaics of the conterminous United States. Remote Sens. Environ. 114 (2010), 35–49.
46. Roy, D.P., Wulder, M.A., Loveland, T.R., Woodcock, C.E., Allen, R.G., Anderson, M.C., Helder, D., Irons, J.R., Johnson, D.M., Kennedy, R., Scambos, T., Schaaf, C.B., Schott, J.R., Sheng, Y., Vermote, E.F., Belward, A.S., Bindschadler, R., Cohen, W.B., Gao, F., Hipple, J.D., Hostert, P., Huntington, J., Justice, C.O., Kilic, A., Kovalskyy, V., Lee, Z.P., Lymbumer, L., Masek, J.G., McCorkel, J., Shuai, Y., Trezza, R., Vogelmann, J., Wynne, R.H., Zhu, Z., Landsat-8: science and product vision for terrestrial global change research. Remote Sens. Environ. 145 (2014), 154–172.
47. Roy, D.P., Zhang, H.K., Ju, J., Gomez-Dans, J.L., Lewis, P.E., Schaaf, C.B., Sun, Q., Li, J., Huang, H., Kovalskyy, V., A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance. Remote Sens. Environ. 176 (2016), 255–271.
48. Roy, D.P., Li, J., Zhang, H.K., Yan, L., Huang, H., Li, Z., Examination of Sentinel-2A multi-spectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance. Remote Sens. Environ. 199 (2017), 25–38.
49. Shelestov, A., Lavreniuk, M., Kussul, N., Novikov, A., Skakun, S., Exploring Google Earth engine platform for Big Data Processing: classification of multi-temporal satellite imagery for crop mapping. Front. Earth Sci., 5, 2017, 17.
50. Skakun, S., Kussul, N., Shelestov, A., Kussul, O., Flood hazard and flood risk assessment using a time series of satellite images: a case study in Namibia. Risk Anal. 34 (2014), 1521–1537.
51. Skakun, S., Roger, J.-C., Vermote, E.F., Masek, J.G., Justice, C.O., Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping. Int. J. Digital Earth, 2017, 1–17.
52. Skakun, S., Vermote, E., Roger, J.C., Franch, B., Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale. AIMS Geosci. 3 (2017), 163–186.
53. Storey, J., Choate, M., Lee, K., Landsat 8 operational land imager on-orbit geometric calibration and performance. Remote Sens. 6 (2014), 11127–11152.
54. Storey, J., Roy, D.P., Masek, J., Gascon, F., Dwyer, J., Choate, M., A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery. Remote Sens. Environ. 186 (2016), 121–122.
55. Strahler, A.H., Lucht, W., Schaaf, C.B., Tsang, T., Gao, F., Li, X., Lewis, P., Barnsley, M., Documentation, M., (eds.) MODIS BRDF/Albedo Product: Algorithm Theoretical Basis Document Version 5.0, 1999 (Boston).
56. Teillet, P.M., Fedosejevs, G., Thome, K.J., Barker, J.L., Impacts of spectral band difference effects on radiometric cross-calibration between satellite sensors in the solar-reflective spectral domain. Remote Sens. Environ. 110 (2007), 393–409.
57. Trinh, R.C., Fichot, C.G., Gierach, M.M., Holt, B., Malakar, N.K., Hulley, G., Smith, J., Application of Landsat 8 for monitoring impacts of wastewater discharge on coastal water quality. Front. Mar. Sci., 4, 2017.
58. USGS, Landsat Analysis Ready Data (ARD). 2018.
59. Vermote, E.F., Kotchenova, S., Atmospheric correction for the monitoring of land surfaces. J. Geophys. Res.-Atmos., 113, 2008.
60. Vermote, E., Saleous, N., LEDAPS Surface Reflectance Product Description. 2007.
61. Vermote, E., Justice, C.O., Breon, F.-M., Towards a generalized approach for correction of the BRDF effect in MODIS directional reflectances. IEEE Trans. Geosci. Remote Sens., 47, 2009.
62. Vermote, E., Justice, C., Claverie, M., Franch, B., Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sens. Environ. 185 (2016), 46–56.
63. Waldner, F., De Abelleyra, D., Veron, S.R., Zhang, M., Wu, B.F., Plotnikov, D., Bartalev, S., Lavreniuk, M., Skakun, S., Kussul, N., Le Maire, G., Dupuy, S., Jarvis, I., Defourny, P., Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity. Int. J. Remote Sens. 37 (2016), 3196–3231.
64. Whitcraft, A.K., Becker-Reshef, I., Justice, C.O., A framework for defining spatially explicit earth observation requirements for a global agricultural monitoring initiative (GEOGLAM). Remote Sens. 7 (2015), 1461–1481.
65. Whitcraft, A.K., Vemiote, E.F., Becker-Reshef, I., Justice, C.O., Cloud cover throughout the agricultural growing season: impacts on passive optical earth observations. Remote Sens. Environ. 156 (2015), 438–447.
66. White, E.V., Roy, D.P., A Contemporary Decennial Examination of Changing Agricultural Field Sizes Using Landsat Time Series Data. 2015.
67. Woodcock, C.E., Allen, R., Anderson, M., Belward, A., Bindschadler, R., Cohen, W., Gao, F., Goward, S.N., Helder, D., Helmer, E., Nemani, R., Oreopoulos, L., Schott, J., Thenkabail, P.S., Vermote, E.F., Vogelmann, J., Wulder, M.A., Wynne, R., Free access to Landsat imagery. Science, 320, 2008, 1011.
68. Wulder, M.A., Masek, J.G., Cohen, W.B., Loveland, T.R., Woodcock, C.E., Opening the archive: how free data has enabled the science and monitoring promise of Landsat. Remote Sens. Environ. 122 (2012), 2–10.
69. Yan, L., Roy, D.P., Li, Z., Zhang, H.K., Huang, H., Sentinel-2A multi-temporal misregistration characterization and an orbit-based sub-pixel registration methodology. Remote Sens. Environ. 215 (2018), 495–506.
70. Zhang, H.K., Roy, D.P., Kovalskyy, V., Optimal solar geometry definition for global long-term Landsat time-series bidirectional reflectance normalization. IEEE Trans. Geosci. Remote Sens. 54 (2016), 1410–1418.
71. Zhang, H.K., Roy, D.P., Yan, L., Li, Z., Huang, H., Vermote, E., Skakun, S., Roger, J.-C., Characterization of Sentinel-2A and Landsat-8 top of atmosphere, surface, and nadir BRDF adjusted reflectance and NDVI differences. Remote Sens. Environ. 215 (2018), 482–494.
72. Zhu, Z., Woodcock, C.E., Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sens. Environ. 118 (2012), 83–94.
73. Zhu, Z., Woodcock, C.E., Automated cloud, cloud shadow, and snow detection in multitemporal Landsat data: an algorithm designed specifically for monitoring land cover change. Remote Sens. Environ. 152 (2014), 217–234.
74. Zhu, Z., Wang, S., Woodcock, C.E., Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images. Remote Sens. Environ. 159 (2015), 269–277.