Operational In-Flight Calibration of S-NPP VIIRS in the Visible Using Rayleigh Scattering

被引:4
|
作者
Frouin, Robert [1 ]
Sei, Alain [2 ]
Hauss, Bruce [3 ]
Pratt, Patty [2 ]
机构
[1] UCSD, SIO, Climate Atmospher Sci & Phys Oceanog Div, 9500 Gilman Dr, La Jolla, CA 92093 USA
[2] Northrop Grumman Aerosp Syst, Redondo Beach, CA USA
[3] DKK Inc, Ruston, LA USA
来源
EARTH OBSERVING SYSTEMS XIX | 2014年 / 9218卷
基金
美国国家航空航天局;
关键词
Radiometric calibration; Ocean-color remote sensing; S-NPP VIIRS; ATMOSPHERIC CORRECTION; OCEAN; EQUATION;
D O I
10.1117/12.2069433
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The Rayleigh scattering approach to absolute radiometric calibration of satellite optical sensors is investigated for SNPP VIIRS. The vicarious calibration coefficients are obtained by comparing measured and predicted top-of-atmosphere (TOA) reflectance sampled under "favorable" scene conditions, i.e., oceanic areas with stable water optical properties, where situations of clear sky, low wind speed, and low aerosol content are frequent. In such situations, and under suitable geometry, the dominant contribution to the satellite signal in the visible is due to molecular (Rayleigh) scattering, which can be computed accurately. A sensitivity study performed for suitable calibration sites indicates that, using thresholds of 7 m/s for wind speed, 0.1 for aerosol optical thickness, 0.0005 for Sun glint reflectance, and 60 degrees for Sun and view zenith angles, the error on the TOA reflectance is 2.3% at 410.5 nm (M1), increasing to 4.5% at 671.4 nm (M5). The error budget is dominated by the effect of uncertainty on aerosol optical thickness at the longer wavelengths and on marine reflectance at the shorter wavelengths. Two methods are developed to compute the VIIRS reflectance. The first method (Method 1) consists in using for the region of interest environmental conditions obtained from ancillary data or climatology. The second method (Method 2) addresses the uncertainty in aerosol model and optical thickness by accounting for the aerosol content of the scene. Application of Method 1 to VIIRS data yields calibration coefficients that are site and air mass dependent, which is not satisfactory. This results from using climatology data to specify aerosol parameters. Method 2, which utilizes the measured VIIRS reflectance in the near infrared to estimate the aerosol reflectance, reduces substantially the site and angular geometry dependence of the calibration coefficients. Accuracy can be improved by better specifying the marine reflectance, estimating the aerosol model, and further stratifying the calibration data. The large number of realizations allows for absolute calibration of individual detectors, studies of angular dependence, linearity, and polarization sensitivity, which is not possible using vicarious techniques based on (too few) in situ measurements.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] Prediction of S-NPP VIIRS DNB gains and dark offsets
    Sun, Chengbo
    Schwarting, Thomas
    Chen, Hongda
    Chiang, Kwofu
    Xiong, Xiaoxiong
    EARTH OBSERVING SYSTEMS XXII, 2017, 10402
  • [22] Assessment of the NOAA S-NPP VIIRS Geolocation Reprocessing Improvements
    Wang, Wenhui
    Cao, Changyong
    Bai, Yan
    Blonski, Slawomir
    Schull, Mitchell A.
    REMOTE SENSING, 2017, 9 (10)
  • [23] Preliminary evaluation of S-NPP VIIRS aerosol optical thickness
    Liu, Hongqing
    Remer, Lorraine A.
    Huang, Jingfeng
    Huang, Ho-Chun
    Kondragunta, Shobha
    Laszlo, Istvan
    Oo, Min
    Jackson, John M.
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2014, 119 (07) : 3942 - 3962
  • [24] Evaluation of Aqua MODIS and S-NPP VIIRS Thermal Emissive Bands Calibration Stability Using Dome-C
    Shrestha, Ashish
    Xiong, Xiaoxiong
    EARTH OBSERVING SYSTEMS XXV, 2020, 11501
  • [25] IMPROVING THE LOW LIGHT RADIANCE CALIBRATION OF S-NPP VIIRS DAY/NIGHT BAND IN THE NOAA OPERATIONS
    Uprety, Sirish
    Cao, Changyong
    Gu, Yalong
    Shao, Xi
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 4726 - 4729
  • [26] EVALUATION AND SELECTION OF SST REGRESSION ALGORITHMS FOR S-NPP VIIRS
    Petrenko, B.
    Ignatov, A.
    Kihai, Y.
    OCEAN SENSING AND MONITORING V, 2013, 8724
  • [27] Prediction of S-NPP VIIRS DNB Stray Light Correction
    Sun, Chengbo
    Schwarting, Thomas
    Chen, Hongda
    Chiang, Kwofu
    Xiong, Xiaoxiong
    EARTH OBSERVING SYSTEMS XXII, 2017, 10402
  • [28] On-Orbit Characterization of S-NPP VIIRS Transmission Functions
    McIntire, Jeff
    Moyer, David
    Efremova, Boryana
    Oudrari, Hassan
    Xiong, Xiaoxiong
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2015, 53 (05): : 2354 - 2365
  • [29] S-NPP VIIRS Thermal Emissive Bands 10-Year On-Orbit Calibration and Performance
    Diaz, Carlos L. Perez
    Xiong, Xiaoxiong
    Li, Yonghong
    Chiang, Kwofu
    REMOTE SENSING, 2021, 13 (19)
  • [30] SUBPIXEL URBAN MAPPING OVER THE CONTERMINOUS US (CONUS) USING S-NPP VIIRS
    Jin, Huiran
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 1903 - 1906