Early evaluation of the VIIRS calibration, cloud mask and surface reflectance Earth data records

被引:52
|
作者
Vermote, Eric [1 ]
Justice, Chris [2 ]
Csiszar, Ivan [3 ]
机构
[1] NASA, Goddard Space Flight Ctr, Terr Informat Syst Lab, Greenbelt, MD 20771 USA
[2] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[3] NOAA NESDIS, Ctr Satellite Applicat & Res, College Pk, MD USA
关键词
Remote sensing; Atmospheric correction; Surface reflectance; RADIATIVE-TRANSFER CODE; ATMOSPHERIC CORRECTION; VECTOR VERSION; SATELLITE DATA; LAND; VALIDATION; 6S; SIMULATION; RETRIEVAL; PRODUCTS;
D O I
10.1016/j.rse.2014.03.028
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Surface reflectance is one of the key products from VIIRS and as with MODIS, is used in developing several higher-order land products. The VIIRS Surface Reflectance(SR) Intermediate Product (IP) is based on the heritage MODIS Collection 5 product (Vermote, El Saleous, & Justice, 2002). The quality and character of surface reflectance depend on the accuracy of the VIIRS Cloud Mask (VCM), the aerosol algorithms and the adequate calibration of the sensor. The focus of this paper is the early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system, the Interface Data Processing System (IDPS). After a brief introduction, the paper presents the calibration performance and the role of the surface reflectance in calibration monitoring. The analysis of the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions) showstypical problems over bright surfaces and high elevation sites. Also discussed is the performance of the aerosol input used in the atmospheric correction and in particular the artifacts generated by the use of the Navy Aerosol Analysis and Prediction System. Early quantitative results of the performance of the SR product over the AERONET sites show that with the few adjustments recommended, the accuracy is within the threshold specifications. The analysis of the adequacy of the SR product (Land PEATE adjusted version) in applications of societal benefits is then presented. We conclude with a set of recommendations to ensure consistency and continuity of the JPSS mission with the MODIS Land Climate Data Record. Published by Elsevier Inc.
引用
收藏
页码:134 / 145
页数:12
相关论文
共 50 条
  • [21] Assessing the quality of the radiometric and spectral calibration of casi data and retrieval of surface reflectance factors
    Jacobsen, A
    Heidebrecht, KA
    Goetz, AFH
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2000, 66 (09): : 1083 - 1091
  • [22] AERONET-based surface reflectance validation network (ASRVN) data evaluation: Case study for railroad valley calibration site
    Wang, Y.
    Czapla-Myers, J.
    Lyapustin, A.
    Thome, K.
    Dutton, E. G.
    REMOTE SENSING OF ENVIRONMENT, 2011, 115 (10) : 2710 - 2717
  • [23] A Framework of Generating Land Surface Reflectance of China Early Landsat MSS Images by Visibility Data and Its Evaluation
    Zhao, Cong
    Wu, Zihua
    Qin, Qiming
    Ye, Xin
    REMOTE SENSING, 2022, 14 (08)
  • [24] Estimation of the Broken Cloud Effect on Retrieving Reflectance of Cloudless Earth Surface Regions from MODIS Imagery
    Tarasenkov, M., V
    Zonov, M. N.
    Engel, M., V
    Belov, V. V.
    RUSSIAN METEOROLOGY AND HYDROLOGY, 2021, 46 (11) : 747 - 754
  • [25] Estimation of the Broken Cloud Effect on Retrieving Reflectance of Cloudless Earth Surface Regions from MODIS Imagery
    M. V. Tarasenkov
    M. N. Zonov
    M. V. Engel’
    V. V. Belov
    Russian Meteorology and Hydrology, 2021, 46 : 747 - 754
  • [26] Analysis of MODIS-MISR calibration differences using surface albedo around AERONET sites and cloud reflectance
    Lyapustin, A.
    Wang, Y.
    Kahn, R.
    Xiong, J.
    Ignatov, A.
    Wolfe, R.
    Wu, A.
    Holben, B.
    Bruegge, C.
    REMOTE SENSING OF ENVIRONMENT, 2007, 107 (1-2) : 12 - 21
  • [27] Evaluation of land surface phenology from VIIRS data using time series of PhenoCam imagery
    Zhang, Xiaoyang
    Jayavelu, Senthilnath
    Liu, Lingling
    Friedl, Mark A.
    Henebry, Geoffrey M.
    Liu, Yan
    Schaaf, Crystal B.
    Richardson, Andrew D.
    Gray, Joshua
    AGRICULTURAL AND FOREST METEOROLOGY, 2018, 256 : 137 - 149
  • [28] LaSRC (Land Surface Reflectance Code): Overview, application and validation using MODIS, VIIRS, LANDSAT and Sentinel 2 data's
    Vermote, E.
    Roger, J. C.
    Franch, B.
    Skakun, Sergii
    IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 8173 - 8176
  • [29] Evaluation of methods for soil surface moisture estimation from reflectance data
    Liu, WD
    Baret, F
    Gu, XF
    Zhang, B
    Tong, QX
    Zheng, LF
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2003, 24 (10) : 2069 - 2083
  • [30] Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records
    Riggs, George A.
    Hall, Dorothy K.
    Roman, Miguel O.
    EARTH SYSTEM SCIENCE DATA, 2017, 9 (02) : 765 - 777