A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring

被引:457
作者
Li, Jian [1 ]
Roy, David P. [1 ]
机构
[1] South Dakota State Univ, Geospatial Sci Ctr Excellence, Brookings, SD 57007 USA
关键词
Sentinel-2A; Sentinel-2B; Landsat-8; temporal revisit interval; near coincident sensor observation; RADIOMETRIC CROSS-CALIBRATION; CONTERMINOUS UNITED-STATES; BRDF ADJUSTED REFLECTANCE; LAND IMAGER OLI; TIME-SERIES; GENERAL-METHOD; ETM PLUS; MODIS; VEGETATION; SATELLITE;
D O I
10.3390/rs9090902
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Combination of different satellite data will provide increased opportunities for more frequent cloud-free surface observations due to variable cloud cover at the different satellite overpass times and dates. Satellite data from the polar-orbiting Landsat-8 (launched 2013), Sentinel-2A (launched 2015) and Sentinel-2B (launched 2017) sensors offer 10 m to 30 m multi-spectral global coverage. Together, they advance the virtual constellation paradigm for mid-resolution land imaging. In this study, a global analysis of Landsat-8, Sentinel-2A and Sentinel-2B metadata obtained from the committee on Earth Observation Satellite (CEOS) Visualization Environment (COVE) tool for 2016 is presented. A global equal area projection grid defined every 0.05 degrees is used considering each sensor and combined together. Histograms, maps and global summary statistics of the temporal revisit intervals (minimum, mean, and maximum) and the number of observations are reported. The temporal observation frequency improvements afforded by sensor combination are shown to be significant. In particular, considering Landsat-8, Sentinel-2A, and Sentinel-2B together will provide a global median average revisit interval of 2.9 days, and, over a year, a global median minimum revisit interval of 14 min (+/- 1 min) and maximum revisit interval of 7.0 days.
引用
收藏
页数:17
相关论文
共 39 条
[11]   The availability of cloud-free Landsat ETM plus data over the conterminous United States and globally [J].
Ju, Junchang ;
Roy, David P. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (03) :1196-1211
[12]   CEOS Visualization Environment (COVE) Tool for Intercalibration of Satellite Instruments [J].
Kessler, Paul D. ;
Killough, Brian D. ;
Gowda, Sanjay ;
Williams, Brian R. ;
Chander, Gyanesh ;
Qu, Min .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2013, 51 (03) :1081-1087
[13]  
Knuth D. E., 1998, Sorting and Searching, V2
[14]   The global availability of Landsat 5 TM and Landsat 7 ETM + land surface observations and implications for global 30 m Landsat data product generation [J].
Kovalskyy, V. ;
Roy, D. P. .
REMOTE SENSING OF ENVIRONMENT, 2013, 130 :280-293
[15]   A One Year Landsat 8 Conterminous United States Study of Cirrus and Non-Cirrus Clouds [J].
Kovalskyy, Valeriy ;
Roy, David P. .
REMOTE SENSING, 2015, 7 (01) :564-578
[16]   Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) of the 30-m ReflectiveWavelength Bands to Sentinel-2 20-m Resolution [J].
Li, Zhongbin ;
Zhang, Hankui K. ;
Roy, David P. ;
Yan, Lin ;
Huang, Haiyan ;
Li, Jian .
REMOTE SENSING, 2017, 9 (07)
[17]   Landsat 8: The plans, the reality, and the legacy [J].
Loveland, Thomas R. ;
Irons, James R. .
REMOTE SENSING OF ENVIRONMENT, 2016, 185 :1-6
[18]   Preliminary Comparison of Sentinel-2 and Landsat 8 Imagery for a Combined Use [J].
Mandanici, Emanuele ;
Bitelli, Gabriele .
REMOTE SENSING, 2016, 8 (12)
[19]   Radiometric Cross Calibration of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM plus ) [J].
Mishra, Nischal ;
Haque, Md Obaidul ;
Leigh, Larry ;
Aaron, David ;
Helder, Dennis ;
Markham, Brian .
REMOTE SENSING, 2014, 6 (12) :12619-12638
[20]   The global impact of clouds on the production of MODIS bidirectional reflectance model-based composites for terrestrial monitoring [J].
Roy, D. P. ;
Lewis, P. ;
Schaaf, C. B. ;
Devadiga, S. ;
Boschetti, L. .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2006, 3 (04) :452-456