Fusing Microwave and Optical Satellite Observations to Simultaneously Retrieve Surface Soil Moisture, Vegetation Water Content, and Surface Soil Roughness

被引:14
|
作者
Sawada, Yohei [1 ,2 ,3 ]
Koike, Toshio [1 ,4 ]
Aida, Kentaro [5 ]
Toride, Kinya [1 ,6 ]
Walker, Jeffrey P. [7 ]
机构
[1] Univ Tokyo, Sch Engn, Dept Civil Engn, Tokyo 1138654, Japan
[2] RIKEN, Adv Inst Computat Sci, Data Assimilat Res Team, Kobe, Hyogo 6500047, Japan
[3] Japan Meteorol Agcy, Meteorol Res Inst, Forecast Dept, Tsukuba, Ibaraki 3050052, Japan
[4] Int Ctr Water Hazard & Risk Management, Tsukuba, Ibaraki 3002621, Japan
[5] Univ Tsukuba, Ctr Res Isotopes & Environm Dynam, Tsukuba, Ibaraki 3058571, Japan
[6] Univ Calif Davis, Dept Civil & Environm Engn, Davis, CA 95616 USA
[7] Monash Univ, Dept Civil Engn, Clayton, Vic 3800, Australia
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2017年 / 55卷 / 11期
基金
日本学术振兴会;
关键词
Microwave radiometry; satellite applications; soil; vegetation; water resources; AMSR-E; WET SOIL; EMISSION; MODEL; VALIDATION; ALGORITHM; ASSIMILATION; VERIFICATION; METHODOLOGY; PRODUCTS;
D O I
10.1109/TGRS.2017.2722468
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Uncertainty in surface soil roughness strongly degrades the performance of surface soil moisture (SSM) and vegetation water content (VWC) retrieval from passive microwave observations. This paper proposes an algorithm to objectively determine the surface soil roughness parameter of the radiative transfer model by fusing microwave and optical satellite observations. It is then demonstrated in a semiarid in situ observation site. The roughness correction of this new algorithm positively impacted the performance of SSM (root-mean-square error reduced from 0.088 to 0.070) and VWC retrieval from the Advanced Microwave Scanning Radiometer 2 and Moderate Resolution Imaging Spectroradiometer. Since this surface soil roughness correction may be transferrable to other microwave satellite retrieval algorithms such as those for the Soil Moisture and Ocean Salinity and Soil Moisture Active Passive satellites, this new algorithm can contribute to many microwave earth surface observation satellite missions.
引用
收藏
页码:6195 / 6206
页数:12
相关论文
共 50 条
  • [31] Surface Soil Moisture Retrieval Using Optical/Thermal Infrared Remote Sensing Data
    Wang, Yawei
    Peng, Jian
    Song, Xiaoning
    Leng, Pei
    Ludwig, Ralf
    Loew, Alexander
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 56 (09): : 5433 - 5442
  • [32] Estimating root zone soil moisture using near-surface observations from SMOS
    Ford, T. W.
    Harris, E.
    Quiring, S. M.
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2014, 18 (01) : 139 - 154
  • [33] Generation of root zone soil moisture from the integration of an all-weather satellite surface soil moisture estimates and an analytical model: A preliminary result in China
    Wang, Yanyan
    Leng, Pei
    Mad, Jianwei
    Manfreda, Salvatore
    Ma, Chunfeng
    Song, Qian
    Shang, Guo-Fei
    Zhang, Xia
    Li, Zhao-Liang
    JOURNAL OF HYDROLOGY, 2024, 644
  • [34] Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China
    Zhang, Ke
    Chao, Li-jun
    Wang, Qing-qing
    Huang, Ying-chun
    Liu, Rong-hua
    Hong, Yang
    Tu, Yong
    Qu, Wei
    Ye, Jin-yin
    WATER SCIENCE AND ENGINEERING, 2019, 12 (02) : 85 - 97
  • [35] DECOMPOSITION OF THE SMAP RADAR CHANNELS AND RELATION TO SURFACE SOIL MOISTURE AND VEGETATION
    Li, Y.
    Akbar, R.
    Yang, F.
    Lu, H.
    McColl, K.
    Entekhabi, D.
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 1989 - 1991
  • [36] Satellite-based crop coefficient and evapotranspiration using surface soil moisture and vegetation indices in Northeast Asia
    Park, Jongmin
    Baik, Jongjin
    Choi, Minha
    CATENA, 2017, 156 : 305 - 314
  • [37] Using Generalized Regression Neural Network to Retrieve Bare Surface Soil Moisture From Radarsat-2 Backscatter Observations, Regardless of Roughness Effect
    Zeng, Ling
    Liu, Quanming
    Jing, Linhai
    Lan, Ling
    Feng, Jun
    FRONTIERS IN EARTH SCIENCE, 2021, 9
  • [38] Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States
    Baldwin, D.
    Manfreda, S.
    Keller, K.
    Smithwick, E. A. H.
    JOURNAL OF HYDROLOGY, 2017, 546 : 393 - 404
  • [39] Comparison of surface soil moisture from SMOS satellite and ground measurements
    Usowicz, Boguslaw
    Marczewski, Wojciech
    Usowicz, Jerzy B.
    Lukowski, Mateusz I.
    Lipiec, Jerzy
    INTERNATIONAL AGROPHYSICS, 2014, 28 (03) : 359 - 369
  • [40] How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture?
    Zappa, Luca
    Schlaffer, Stefan
    Brocca, Luca
    Vreugdenhil, Mariette
    Nendel, Claas
    Dorigo, Wouter
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 113