SURFACE PARAMETERS ESTIMATION USING RADARSAT-2 POLARIMETRIC DATA OVER WHEAT COVERED AREA

被引：0
作者：
Chen, Quan [1 ,2 ,3 ]
Li, Zhen [1 ]
Cai, Aimin [2 ,3 ]
Tian, Bangsen [1 ,2 ]
机构：
[1] Chinese Acad Sci, Ctr Earth Observat & Digital Earth, Beijing 100864, Peoples R China
[2] Grad Univ Chinese Acad Sci, Beijing 100864, Peoples R China
[3] Beijing Normal Univ, Inst Remote Sensing Applicat Chinese Acad Sci, State Key Lab Remote Sensing Sci, Beijing 100864, Peoples R China
来源：
2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2010年
关键词：
Radarsat-2; Soil Moisture; Roughness; Polarimetric; Vegetation Covered area;
D O I：
10.1109/IGARSS.2010.5650824
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
In the field of agriculture, robust harvests and crop yields are challenged by the dynamic nature of soil and crop conditions that fluctuate throughout the growing season. Satellite SAR imagery is an efficient method for mapping crop and underground soil characteristics over large spatial areas and tracking temporal changes in soil and crop conditions. Compared with conventional one (ERS-1/2, Radarsat-1) or two-polarization (Envisat/ASAR) space-borne SAR sensors, RADARSAT-2 powerful new features in terms of polarization can benefit the agricultural sector. In this paper, soil moisture and LAI from ground measurements is compared with power information of two Radarsat-2 polarimetric images, result shows soil moisture does has some influence when vegetation is short, but LAI doesn't influence backscattering at any stage of this paper.
引用
收藏
页码：4843 / 4846
页数：4
相关论文
共 50 条
  • [41] Implementation of a multiangle soil moisture retrieval model using RADARSAT-2 imagery over arid Juyanze, northwest China
    Yang, Liping
    Li, Yanfei
    Li, Qi
    Sun, Xiaohui
    Kong, Jinling
    Wang, Le
    JOURNAL OF APPLIED REMOTE SENSING, 2017, 11
  • [42] 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
  • [43] An Adaptive Two-Component Model-Based Decomposition on Soil Moisture Estimation for C-Band RADARSAT-2 Imagery Over Wheat Fields at Early Growing Stages
    Huang, Xiaodong
    Wang, Jinfei
    Shang, Jiali
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2016, 13 (03) : 414 - 418
  • [44] SURFACE PARAMETER INVERSION SCHEME OVER AGRICULTURAL FIELDS WITH CROP RESIDUES AND UNDER LOW VEGETATION COVER FROM RADARSAT-2 IMAGERY
    Huang, Xiaodong
    Wang, Jinfei
    Shang, Jiali
    2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 3203 - 3206
  • [45] Soil moisture retrieval over agricultural fields from multi-polarized and multi-angular RADARSAT-2 SAR data
    Gherboudj, Imen
    Magagi, Ramata
    Berg, Aaron A.
    Toth, Brenda
    REMOTE SENSING OF ENVIRONMENT, 2011, 115 (01) : 33 - 43
  • [46] Soil permittivity estimation over vegetative fields using dual polarimetric SAR data
    Dey, Subhadip
    Bhogapurapu, Narayanarao
    Hajnsek, Irena
    Bhattacharya, Avik
    Siqueira, Paul
    REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2024, 33
  • [47] Sensitivity of Main Polarimetric Parameters of Multifrequency Polarimetric SAR Data to Soil Moisture and Surface Roughness Over Bare Agricultural Soils
    Baghdadi, Nicolas
    Dubois-Fernandez, Pascale
    Dupuis, Xavier
    Zribi, Mehrez
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2013, 10 (04) : 731 - 735
  • [48] Surface Soil Moisture Estimation from Time Series of RADARSAT Constellation Mission Compact Polarimetric Data for the Identification of Water-Saturated Areas
    Zakharov, Igor
    Kohlsmith, Sarah
    Hornung, Jon
    Charbonneau, Francois
    Bobby, Pradeep
    Howell, Mark
    REMOTE SENSING, 2024, 16 (14)
  • [49] Estimation of crop parameters using multi-temporal optical and radar polarimetric satellite data
    Betbeder, Julie
    Fieuzal, Remy
    Philippets, Yannick
    Ferro-Famil, Laurent
    Baup, Frederic
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XVII, 2015, 9637
  • [50] Using Generalized Regression Neural Network to Retrieve Bare Surface Soil Moisture From Radarsat-2 Backscatter Observations, Regardless of Roughness Effect
    Zeng, Ling
    Liu, Quanming
    Jing, Linhai
    Lan, Ling
    Feng, Jun
    FRONTIERS IN EARTH SCIENCE, 2021, 9
12345