Toward an Improved Surface Roughness Parameterization Model for Soil Moisture Retrieval in Road Construction

被引:1
|
作者
Thi Mai Nguyen [1 ]
Walker, Jeffrey P. [1 ]
Ye, Nan [1 ]
Kodikara, Jayantha [1 ]
机构
[1] Monash Univ, Dept Civil Engn, Clayton, Vic 3800, Australia
基金
澳大利亚研究理事会;
关键词
L-band radiometer; sand subgrade; soil moisture (SM); surface roughness parameter; BAND MICROWAVE EMISSION; L-MEB MODEL; SMOS; FIELD;
D O I
10.1109/TGRS.2023.3238367
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
In passive microwave remote sensing, the estimation of the surface roughness parameter is a significant obstacle for soil moisture (SM) retrieval. For a given SM content, the geometric soil surface roughness has been shown to have a large impact on the surface emission at L-band frequency, which affects the SM retrieval success when using the information observed from the radiometer and is represented through the so-called the surface roughness parameter (H-R). Moreover, no previous study has examined the effect of this factor in the context of road construction, where the geometric soil surface roughness is affected by the compaction process, resulting in a substantial change in roughness before and after compaction. Accordingly, a series of experiments at various compaction levels and SM contents was performed for a sand subgrade material in order to identify their effects on HR. The soil brightness temperature (TB) was measured using an L-band radiometer at different incidence angles and a laser profiler was used to measure the surface roughness standard deviation (sigma) before and after compaction. The results of this article have demonstrated that the incidence angle (theta) and SM both affect HR and its relation to the geometric soil surface roughness. Importantly, these factors are not accounted for by existing models. Consequently, a modified surface roughness parameter (HR) model, based on the traditional Choudhury model, was developed to include the contribution of these two factors, and its impact on the accuracy of SM retrieval results tested. Specifically, it was shown that it is possible to obtain SM retrieval results with an accuracy of 0.04 cm(3)/cm(3) at almost all incidence angles using either dual-polarization [both horizontal (H) and vertical polarization (V)] or only vertical polarization observations. The modified surface roughness parameter (HR) model has improved the performance of the SM retrieval model to achieve an accuracy of 0.04 cm(3)/cm(3), whereas the traditional Choudhury model achieved an accuracy of only 0.05 cm(3)/cm(3).
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Improved Understanding of Soil Surface Roughness Parameterization for L-Band Passive Microwave Soil Moisture Retrieval
    Panciera, Rocco
    Walker, Jeffrey P.
    Merlin, Olivier
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2009, 6 (04) : 625 - 629
  • [2] MULTI-SCALE SURFACE ROUGHNESS MODEL FOR SOIL MOISTURE RETRIEVAL
    Neelam, Maheshwari
    Colliander, Andreas
    Mohanty, Binayak P.
    Jackson, Thomas J.
    Cosh, Michael H.
    Misra, Sidharth
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 4963 - 4965
  • [3] Multiscale Surface Roughness for Improved Soil Moisture Estimation
    Neelam, Maheshwari
    Colliander, Andreas
    Mohanty, Binayak P.
    Cosh, Michael H.
    Misra, Sidharth
    Jackson, Thomas J.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 58 (08): : 5264 - 5276
  • [4] On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from synthetic aperture radar
    Verhoest, Niko E. C.
    Lievens, Hans
    Wagner, Wolfgang
    Alvarez-Mozos, Jesus
    Moran, M. Susan
    Mattia, Francesco
    SENSORS, 2008, 8 (07) : 4213 - 4248
  • [5] Surface roughness characterization for SAR applications - An alternative representation of the roughness state for soil moisture and roughness retrieval algorithms
    Louis, J
    Floury, N
    Davidson, M
    Attema, E
    Borgeaud, M
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 1408 - 1410
  • [6] Measuring Surface Roughness for Retrieval of Soil Moisture Based on Mobile Laser Scanning
    Zhong, Ruofei
    Huang, Jianxi
    Gong, Huili
    Su, Wei
    Li, Qin
    Qin, Mengli
    SENSOR LETTERS, 2011, 9 (03) : 990 - 996
  • [7] Retrieval of Soil Moisture and Surface Roughness from Backscatter Measurements of Vegetation Canopy
    Oh, Yisok
    Hong, Jin-Young
    Jung, Seung-Gun
    2007 ASIA PACIFIC MICROWAVE CONFERENCE, VOLS 1-5, 2007, : 298 - 300
  • [8] THE NEW ALGORITHM FOR RETRIEVAL OF SOIL MOISTURE AND SURFACE ROUGHNESS FROM GNSS REFLECTOMETRY
    Mironov, V. L.
    Muzalevskiy, K. V.
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 7530 - 7532
  • [9] Measuring surface roughness height to parameterize radar backscatter models for retrieval of surface soil moisture
    Bryant, R.
    Moran, M. S.
    Thoma, D. P.
    Collins, C. D. Holifield
    Skirvin, S.
    Rahman, M.
    Slocum, K.
    Starks, P.
    Bosch, D.
    Gonzalez Dugo, M. P.
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2007, 4 (01) : 137 - 141
  • [10] 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