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
  • [11] Passive Microwave Soil Moisture Downscaling Using Vegetation Index and Skin Surface Temperature
    Fang, Bin
    Lakshmi, Venkat
    Bindlish, Rajat
    Jackson, Thomas J.
    Cosh, Michael
    Basara, Jeffrey
    VADOSE ZONE JOURNAL, 2013, 12 (03)
  • [12] A novel vegetation-water resistant soil moisture index for remotely assessing soil surface moisture content under the low-moderate wheat cover
    Yue, Jibo
    Li, Ting
    Liu, Yang
    Tian, Jia
    Tian, Qingjiu
    Li, Suju
    Feng, Haikuan
    Guo, Wei
    Yang, Hao
    Yang, Guijun
    Qiao, Hongbo
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 224
  • [13] A Semiphysical Microwave Surface Emission Model for Soil Moisture Retrieval
    Shen, Xinyi
    Hong, Yang
    Qin, Qiming
    Basara, Jeffrey B.
    Mao, Kebiao
    Wang, D.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2015, 53 (07): : 4079 - 4090
  • [14] y Monitoring Surface Soil Moisture Content over the Vegetated Area by Integrating Optical and SAR Satellite Observations in the Permafrost Region of Tibetan Plateau
    Xu, Chenyang
    Qu, John J.
    Hao, Xianjun
    Wu, Di
    REMOTE SENSING, 2020, 12 (01)
  • [15] Effects of vegetation and soil texture on surface soil moisture retrieval using multi-temporal optical and thermal infrared observations
    Leng, Pei
    Song, Xiaoning
    Li, Zhao-Liang
    Wang, Yawei
    Wang, Di
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2015, 36 (19-20) : 4972 - 4985
  • [16] Impact of surface roughness, vegetation opacity and soil permittivity on L-band microwave emission and soil moisture retrieval in the third pole environment
    Zheng, Donghai
    Wang, Xin
    van der Velde, Rogier
    Ferrazzoli, Paolo
    Wen, Jun
    Wang, Zuoliang
    Schwank, Mike
    Colliander, Andreas
    Bindlish, Rajat
    Su, Zhongbo
    REMOTE SENSING OF ENVIRONMENT, 2018, 209 : 633 - 647
  • [17] Toward High-Resolution Soil Moisture Monitoring by Combining Active-Passive Microwave and Optical Vegetation Remote Sensing Products with Land Surface Model
    Toride, Kinya
    Sawada, Yohei
    Aida, Kentaro
    Koike, Toshio
    SENSORS, 2019, 19 (18)
  • [18] A Combined Optical-Microwave Method to Retrieve Soil Moisture Over Vegetated Areas
    Mattar, Cristian
    Wigneron, Jean-Pierre
    Sobrino, Jose A.
    Novello, Nathalie
    Calvet, Jean Christophe
    Albergel, Clement
    Richaume, Philippe
    Mialon, Arnaud
    Guyon, Dominique
    Carlos Jimenez-Munoz, Juan
    Kerr, Yann
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2012, 50 (05): : 1404 - 1413
  • [19] Ensemble surface soil moisture estimates at farm-scale combining satellite-based optical-thermal-microwave remote sensing observations
    Das, Bappa
    Rathore, Pooja
    Roy, Debasish
    Chakraborty, Debashis
    Bhattacharya, Bimal Kumar
    Mandal, Dipankar
    Jatav, Raghuveer
    Sethi, Deepak
    Mukherjee, Joydeep
    Sehgal, Vinay Kumar
    Singh, Amit Kumar
    Kumar, Parveen
    AGRICULTURAL AND FOREST METEOROLOGY, 2023, 339
  • [20] AN APPROACH FOR SURFACE SOIL MOISTURE RETRIEVAL USING MICROWAVE VEGETATION INDICES BASED ON SMOS DATA
    Cui, Qian
    Shi, Jiancheng
    Zhao, Tianjie
    Liu, Qang
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 2692 - 2695