First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI

被引:22
|
作者
Li, Shuang [1 ,2 ]
Wang, Weile [3 ]
Hashimoto, Hirofumi [3 ]
Xiong, Jun [4 ]
Vandal, Thomas [4 ]
Yao, Jing [1 ,2 ]
Qian, Lexiang [5 ]
Ichii, Kazuhito [6 ]
Lyapustin, Alexei [7 ]
Wang, Yujie [7 ,8 ]
Nemani, Ramakrishna [9 ]
机构
[1] Guizhou Educ Univ, Sch Geog & Resources, Guiyang 550018, Peoples R China
[2] Guizhou Educ Univ, Guizhou Prov Key Lab Geog State Monitoring Waters, Guiyang 550018, Peoples R China
[3] NASA, Ames Res Ctr, CSUMB, Moffett Field, CA 94035 USA
[4] NASA, Ames Res Ctr, BAERI, Moffett Field, CA 94035 USA
[5] Guangzhou Univ, Sch Geog Sci, Guangzhou 510006, Peoples R China
[6] Chiba Univ, Ctr Environm Remote Sensing, Chiba 2638522, Japan
[7] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[8] UMBC, Joint Ctr Earth Syst Technol JCET, Baltimore, MD 21228 USA
[9] NASA, Goddard Space Flight Ctr, Ames Res Ctr, Moffett Field, CA 94035 USA
基金
美国国家航空航天局;
关键词
Himawari-8; AHI; geostationary satellite; MAIAC; surface reflectance; ATMOSPHERIC CORRECTION; INTER-CALIBRATION; VEGETATION; MODIS; SCIAMACHY; ALBEDO; BRDF;
D O I
10.3390/rs11242990
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A provisional surface reflectance (SR) product from the Advanced Himawari Imager (AHI) on-board the new generation geostationary satellite (Himawari-8) covering the period between July 2015 and December 2018 is made available to the scientific community. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is used in conjunction with time series Himawari-8 AHI observations to generate 1-km gridded and tiled land SR every 10 minutes during day time. This Himawari-8 AHI SR product includes retrieved atmospheric properties (e.g., aerosol optical depth at 0.47 mu m and 0.51 mu m), spectral surface reflectance (AHI bands 1-6), parameters of the RTLS BRDF model, and quality assurance flags. Product evaluation shows that Himawari-8 AHI data on average yielded 35% more cloud-free, valid pixels in a single day when compared to available data from the low earth orbit (LEO) satellites Terra/Aqua with MODIS sensor. Comparisons of Himawari-8 AHI SR against corresponding MODIS SR products (MCD19A1) over a variety of land cover types with the similar viewing geometry show high consistency between them, with correlation coefficients (r) being 0.94 and 0.99 for red and NIR bands, respectively. The high-frequency geostationary data are expected to facilitate studies of ecosystems on daily to diurnal time scales, complementing observations from networks such as the FLUXNET.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Aerosol data assimilation using data from Himawari-8, a next-generation geostationary meteorological satellite
    Yumimoto, K.
    Nagao, T. M.
    Kikuchi, M.
    Sekiyama, T. T.
    Murakami, H.
    Tanaka, T. Y.
    Ogi, A.
    Irie, H.
    Khatri, P.
    Okumura, H.
    Arai, K.
    Morino, I.
    Uchino, O.
    Maki, T.
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2016, 43 (11) : 5886 - 5894
  • [42] Mapping Diurnal Variability of the Wintertime Pearl River Plume Front from Himawari-8 Geostationary Satellite Observations
    Hu, Zifeng
    Xie, Guanghao
    Zhao, Jun
    Lei, Yaping
    Xie, Jinchi
    Pang, Wenhong
    [J]. WATER, 2022, 14 (01)
  • [43] Data article: Full disk real-time Himawari-8/9 satellite AHI imagery from JAXA
    Sun, Xixi
    Gnanamuthu, Sasikala
    Zagade, Nilesh
    Wang, Peng
    Bright, Jamie M.
    [J]. JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2021, 13 (06)
  • [44] SIMULTANEOUS RETRIEVAL OF LAND SURFACE TEMPERATURE AND EMISSIVITY FROM AHI/HIMAWARI8 DATA
    Zhou, Shugui
    Cheng, Jie
    Meng, Xiangchen
    [J]. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 6417 - 6420
  • [45] Improved Hourly Estimates of Aerosol Optical Thickness Using Spatiotemporal Variability Derived From Himawari-8 Geostationary Satellite
    Kikuchi, Maki
    Murakami, Hiroshi
    Suzuki, Kentaroh
    Nagao, Takashi M.
    Higurashi, Akiko
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 56 (06): : 3442 - 3455
  • [46] Comparison of Cloud Properties from Himawari-8 and FengYun-4A Geostationary Satellite Radiometers with MODIS Cloud Retrievals
    Lai, Ruize
    Teng, Shiwen
    Yi, Bingqi
    Letu, Husi
    Min, Min
    Tang, Shihao
    Liu, Chao
    [J]. REMOTE SENSING, 2019, 11 (14)
  • [47] A minimum albedo aerosol retrieval method for the new-generation geostationary meteorological satellite Himawari-8
    Yan, Xing
    Li, Zhanqing
    Luo, Nana
    Shi, Wenzhong
    Zhao, Wenji
    Yang, Xingchuan
    Jin, Jiannan
    [J]. ATMOSPHERIC RESEARCH, 2018, 207 : 14 - 27
  • [48] Spatiotemporal Dispersion of Local-Scale Dust from the Erdenet Mine in Mongolia Detected by Himawari-8 Geostationary Satellite
    Batbold, Chultem
    Yumimoto, Keiya
    Chonokhuu, Sonomdagva
    Byambaa, Batdelger
    Avirmed, Batdavaa
    Ganbat, Shuukhaaz
    Kaneyasu, Naoki
    Matsumi, Yutaka
    Yasunari, Teppei J.
    Taniguchi, Kenji
    Hasebe, Noriko
    Fukushi, Keisuke
    Matsuki, Atsushi
    [J]. SOLA, 2022, 18 : 225 - 230
  • [49] Development of Fog Detection Algorithm during Nighttime Using Himawari-8/AHI Satellite and Ground Observation Data
    Kim, So-Hyeong
    Suh, Myoung-Seok
    Han, Ji-Hye
    [J]. ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES, 2019, 55 (03) : 337 - 350
  • [50] Efficient Deep Learning Approaches for Active Fire Detection Using Himawari-8 Geostationary Satellite Images
    Lee, Sihyun
    Kang, Yoojin
    Sung, Taejun
    Im, Jungho
    [J]. KOREAN JOURNAL OF REMOTE SENSING, 2023, 39 (5-3) : 979 - 995