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
  • [41] A physically constrained inversion for high-resolution passive microwave retrieval of soil moisture and vegetation water content in L-band
    Ebtehaj, Ardeshir
    Bras, Rafael L.
    REMOTE SENSING OF ENVIRONMENT, 2019, 233
  • [42] Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth
    Forkel, Matthias
    Schmidt, Luisa
    Zotta, Ruxandra-Maria
    Dorigo, Wouter
    Yebra, Marta
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2023, 27 (01) : 39 - 68
  • [43] A physically based statistical methodology for surface soil moisture retrieval in the Tibet Plateau using microwave vegetation indices
    Zhao, T. J.
    Zhang, L. X.
    Shi, J. C.
    Jiang, L. M.
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2011, 116
  • [44] Influences of soil moisture and vegetation cover on dust emission using satellite observations
    Alnasser, Faisal
    Chehbouni, Abdelghani
    Entekhabi, Dara
    AEOLIAN RESEARCH, 2025, 72
  • [45] Surface rock effects on soil moisture retrieval from L-band passive microwave observations
    Ye, N.
    Walker, J. P.
    Rudiger, C.
    Ryu, D.
    Gurney, R. J.
    REMOTE SENSING OF ENVIRONMENT, 2018, 215 : 33 - 43
  • [46] Spatio-temporal evaluation of resolution enhancement for passive microwave soil moisture and vegetation optical depth
    Gevaert, A. I.
    Parinussa, R. M.
    Renzullo, L. J.
    van Dijk, A. I. J. M.
    de Jeu, R. A. M.
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2016, 45 : 235 - 244
  • [47] A Model of Surface Roughness for Use in Passive Remote Sensing of Bare Soil Moisture
    Goodberlet, Mark A.
    Mead, James B.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (09): : 5498 - 5505
  • [48] An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land surface model
    Hain, Christopher R.
    Crow, Wade T.
    Anderson, Martha C.
    Mecikalski, John R.
    WATER RESOURCES RESEARCH, 2012, 48
  • [49] Enhanced Surface Soil Moisture Retrieval at High Spatial Resolution From the Integration of Satellite Observations and Soil Pedotransfer Functions
    Leng, Pei
    Li, Zhao-Liang
    Liao, Qian-Yu
    Geng, Yun-Jing
    Yan, Qiu-Yu
    Zhang, Xia
    Shang, Guo-Fei
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [50] Estimating surface soil moisture from SMAP observations using a Neural Network technique
    Kolassa, J.
    Reichle, R. H.
    Liu, Q.
    Alemohammad, S. H.
    Gentine, P.
    Aida, K.
    Asanuma, J.
    Bircher, S.
    Caldwell, T.
    Colliander, A.
    Cosh, M.
    Collins, C. Holifield
    Jackson, T. J.
    Martinez-Fernandez, J.
    McNairn, H.
    Pacheco, A.
    Thibeault, M.
    Walker, J. P.
    REMOTE SENSING OF ENVIRONMENT, 2018, 204 : 43 - 59