Estimating subcanopy soil moisture with radar

被引:69
|
作者
Moghaddam, M
Saatchi, S
Cuenca, RH
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA
[2] Oregon State Univ, Dept Bioresource Engn, Corvallis, OR 97331 USA
关键词
D O I
10.1029/2000JD900058
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The subcanopy soil moisture of a boreal old jack pine forest stand is estimated using polarimetric L and P band ail borne synthetic aperture radar (AIRSAR) data. Model simulations have shown that for this stand the principal scattering mechanism responsible for radar backscatter is the double-bounce mechanism between the tree trunks and the ground. The data to be used here were acquired during five flights from June to September 1994 as part of the Boreal Ecosystem-Atmosphere Study (BOREAS) project. The dielectric constants, or equivalently moisture contents, of the trunks and soil can change significantly during this period, To estimate these dynamic unknowns, parametric models of radar backscatter for the double-bounce mechanism are developed using a series of simulations of a numerical forest scattering model. A nonlinear optimization procedure is used to estimate the dielectric constants. Ground measurements of soil and trunk moisture content are used to validate the results. The trunk moisture content measurements are used to gain confidence that the respective estimation results are accurate enough not to corrupt the soil moisture estimation, which is the main focus of this paper. After conversion of the trunk moisture measurements to dielectric constants it is found that the estimated values are within 14% of the measurements. Owing to possible calibration uncertainties in the soil moisture measurements on the ground as well as in AIRSAR data, the variations rather than the absolute levels of the estimated soil moisture are considered. The results indicate: that the estimated variations closely track the measurements, The worst case average estimated change differs by <1% volumetric soil moisture from that measured on the ground.
引用
收藏
页码:14899 / 14911
页数:13
相关论文
共 50 条
  • [1] Airborne Microwave Observatory of Subcanopy and Subsurface Radar Retrieval of Root Zone Soil Moisture: Preliminary Results
    Tabatabaeenejad, Alireza
    Burgin, Mariko
    Duan, Xueyang
    Moghaddam, Mahta
    2013 IEEE RADAR CONFERENCE (RADAR), 2013,
  • [2] ADVANCES IN RADAR FORWARD AND INVERSE SCATTERING MODELS OF SUBSURFACE AND SUBCANOPY SOIL MOISTURE AND THEIR ROLE FOR THE AIRMOSS MISSION
    Moghaddam, Mahta
    Tabatabaeenejad, Alireza
    Burgin, Mariko
    Duan, Xueyang
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 1274 - 1277
  • [3] Estimating Soil Moisture by Radar Data Based on Multiple Regression
    Rodionova, N. V.
    IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2023, 59 (10) : 1281 - 1289
  • [4] Estimating Soil Moisture by Radar Data Based on Multiple Regression
    N. V. Rodionova
    Izvestiya, Atmospheric and Oceanic Physics, 2023, 59 : 1281 - 1289
  • [5] Microwave observatory of subcanopy and subsurface (MOSS): A low-frequency radar for global deep soil moisture measurements
    Moghaddam, M
    Rodriguez, E
    Rahmat-Samii, Y
    Moller, D
    Hoffman, J
    Huang, J
    Saatchi, S
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 500 - 502
  • [6] Study of Estimating Surface Soil Moisture Based on Radar and Hyperspectral Data
    Ma J.
    Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2017, 46 (05): : 666
  • [7] Estimating surface soil moisture over Sahel using ENVISAT radar altimetry
    Fatras, C.
    Frappart, F.
    Mougin, E.
    Grippa, M.
    Hiernaux, P.
    REMOTE SENSING OF ENVIRONMENT, 2012, 123 : 496 - 507
  • [8] ESTIMATING SURFACE SOIL MOISTURE OVER SAHEL USING ENVISAT RADAR ALTIMETRY
    Fatras, C.
    Frappart, F.
    Mougin, E.
    Grippa, M.
    Hiernaux, P.
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 1239 - 1242
  • [9] ESTIMATING SOIL MOISTURE USING OPTICAL AND RADAR SATELLITE REMOTE SENSING DATA
    Natali, Stefano
    Pellegrini, Loreto
    Rossi, Gianluigi
    Giordano, Ludovica
    Iannetta, Massimo
    Schino, Gabriele
    Marini, Alberto
    Nabil, Gasmi
    DESERTIFICATION AND RISK ANALYSIS USING HIGH AND MEDIUM RESOLUTION SATELLITE DATA, 2009, : 105 - +
  • [10] Simultaneously estimating surface soil moisture and roughness of bare soils by combining optical and radar data
    Zheng, Xingming
    Feng, Zhuangzhuang
    Li, Lei
    Li, Bingzhe
    Jiang, Tao
    Li, Xiaojie
    Li, Xiaofeng
    Chen, Si
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2021, 100