Evaluation of Radar Backscattering Models IEM, OH, and Dubois using L and C-Bands SAR Data over different vegetation canopy covers and soil depths

被引:0
|
作者
Khabazan, S. [1 ]
Motagh, M. [1 ]
Hosseini, M. [2 ]
机构
[1] Univ Tehran, Coll Engn, Remote Sensing Div, Surveying & Geomat Engn Dept, Tehran 1439957131, Iran
[2] Univ Sherbrooke, Ctr Applicat & Rech Teledetect CARTEL, Sherbrooke, PQ J1K 2R1, Canada
来源
SMPR CONFERENCE 2013 | 2013年 / 40-1-W3卷
关键词
Soil moisture; Dubois model; Integral equation model (IEM); Oh model; Soil depth; NDVI; AIRSAR; MOISTURE; SURFACE; ROUGHNESS; INVERSION; RETRIEVAL;
D O I
暂无
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Several algorithms have been proposed in the literature to invert radar measurements to estimate surface soil moisture. The objective of this paper is to compare the performance of the most common surface back scattering models including the theoretical integral equation model (IEM) of Fung et al(1992)., and the semi-empirical models of Oh et al (1992, 1994, 2002 and 2004). and Dubois et al (1995).. This analysis uses four AIRSAR data in L and C band together with in situ measurements (soil moisture and surface roughness) over bare soil and vegetation covers area and three different soil depths. The results show that Dubois model tend to over-estimate the radar response in both bands while IEM model and Oh model frequently over-estimate the radar response in L band but under-estimate them in C band. By evaluating of all models in different soil depths, the best results were obtained in 0-3 cm depths. For vegetation area poor correlation between models backscatter simulation and radar response was observed.
引用
收藏
页码:225 / 230
页数:6
相关论文
共 9 条
  • [1] Evaluation of Radar Backscattering Models IEM, Oh, and Dubois for SAR Data in X-Band Over Bare Soils
    Baghdadi, Nicolas
    Saba, Elie
    Aubert, Maelle
    Zribi, Mehrez
    Baup, Frederic
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2011, 8 (06) : 1160 - 1164
  • [2] Evaluation of IEM, Dubois, and Oh Radar Backscatter Models Using Airborne L-Band SAR
    Panciera, Rocco
    Tanase, Mihai A.
    Lowell, Kim
    Walker, Jeffrey P.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (08): : 4966 - 4979
  • [3] Evaluation of the Oh, Dubois and IEM Backscatter Models Using a Large Dataset of SAR Data and Experimental Soil Measurements
    Choker, Mohammad
    Baghdadi, Nicolas
    Zribi, Mehrez
    El Hajj, Mohammad
    Paloscia, Simonetta
    Verhoest, Niko E. C.
    Lievens, Hans
    Mattia, Francesco
    Water, 2017, 9 (01):
  • [4] Evaluation of the Dubois, Oh, and IEM radar backscatter models over agricultural fields using C-band RADARSAT-2 SAR image data
    Merzouki, A.
    McNairn, H.
    Pacheco, A.
    CANADIAN JOURNAL OF REMOTE SENSING, 2010, 36 : S274 - S286
  • [5] Evaluation of the Dubois, Oh, and IEM radar backscatter models over agricultural fields using C-band RADARSAT-2 SAR image data
    Merzouki, A.
    McNairn, H.
    Pacheco, A.
    Canadian Journal of Remote Sensing, 2010, 36 (SUPPL. 2)
  • [6] Evaluation of radar backscattering models using L- and C-band synthetic aperture radar data
    Tao, Liangliang
    Li, Jing
    Jiang, Jinbao
    He, Shi
    Cai, Qingkong
    Chen, Xi
    JOURNAL OF APPLIED REMOTE SENSING, 2015, 9
  • [7] Evaluation of radar backscattering models using L-and C-band synthetic aperture radar data
    20155101687990
    Li, Jing (lijing@bnu.edu.cn), 1600, SPIE (09):
  • [8] Assessment of Different Backscattering Models for Bare Soil Surface Parameters Estimation from SAR Data in band C, L and P
    MirMazloumi, S. Mohammad
    Sahebi, Mahmod Reza
    EUROPEAN JOURNAL OF REMOTE SENSING, 2016, 49 : 261 - 278
  • [9] Comprehensive evaluation of soil moisture retrieval models under different crop cover types using C-band synthetic aperture radar data
    Kumar, P.
    Prasad, R.
    Choudhary, A.
    Gupta, D. K.
    Mishra, V. N.
    Vishwakarma, A. K.
    Singh, A. K.
    Srivastava, P. K.
    GEOCARTO INTERNATIONAL, 2019, 34 (09) : 1022 - 1041