Surface Soil Moisture Estimation from Time Series of RADARSAT Constellation Mission Compact Polarimetric Data for the Identification of Water-Saturated Areas

被引:2
作者
Zakharov, Igor [1 ]
Kohlsmith, Sarah [2 ]
Hornung, Jon [2 ]
Charbonneau, Francois [3 ]
Bobby, Pradeep [4 ]
Howell, Mark [4 ]
机构
[1] C CORE, Ottawa, ON K2K 2A4, Canada
[2] Suncor Energy Serv Inc, Calgary, AB T2P 3E3, Canada
[3] Canada Ctr Mapping & Earth Observat CCMEO, Canada Ctr Remote Sensing CCRS, 580 Booth St, Ottawa, ON K1A 0E4, Canada
[4] C CORE, St John, NF A1B 3X5, Canada
关键词
soil moisture; wetland; synthetic aperture radar (SAR); RCM; change detection algorithm; oil sands; reclamation; RETRIEVAL; SAR; ASSIMILATION;
D O I
10.3390/rs16142664
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil moisture is one of the main factors affecting microwave radar backscatter from the ground. While there are other factors that affect backscatter levels (for instance, surface roughness, vegetation, and incident angle), relative variations in soil moisture can be estimated using space-based, medium resolution, multi-temporal synthetic aperture radar (SAR). Understanding the distribution and identification of water-saturated areas using SAR soil moisture can be important for wetland mapping. The SAR soil moisture retrieval algorithm provides a relative assessment and requires calibration over wet and dry periods. In this work, relative soil moisture indicators are derived from a time series of the RADARSAT Constellation Mission (RCM) SAR compact polarimetric (CP) data over reclaimed areas of an oil sands mine in Alberta, Canada. An evaluation of the soil moisture product is performed using in situ measurements showing agreement from June to September. The surface scattering component of m-chi CP decomposition and the RL SAR products demonstrated a good agreement with the field data (low RMSE values and a perfect alignment with field-identified wetlands).
引用
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页数:12
相关论文
共 35 条
[1]  
Banner A., 2000, Extension Note
[2]   Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets and Overcoming Obstacles [J].
Bauer-Marschallingere, Bernhard ;
Freeman, Vahid ;
Cao, Senmao ;
Paulik, Christoph ;
Schaufler, Stefan ;
Stachl, Tobias ;
Modanesi, Sara ;
Massario, Christian ;
Ciabatta, Luca ;
Brocca, Luca ;
Wagner, Wolfgang .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (01) :520-539
[3]   Field-scale soil moisture estimation using sentinel-1 GRD SAR data [J].
Bhogapurapu, Narayanarao ;
Dey, Subhadip ;
Homayouni, Saeid ;
Bhattacharya, Avik ;
Rao, Y. S. .
ADVANCES IN SPACE RESEARCH, 2022, 70 (12) :3845-3858
[4]   Soil Permittivity Estimation Over Croplands Using Full and Compact Polarimetric SAR Data [J].
Bhogapurapu, Narayanarao ;
Dey, Subhadip ;
Bhattacharya, Avik ;
Lopez-Martinez, Carlos ;
Hajnsek, Irena ;
Rao, Y. S. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
[5]   Assimilation of Surface- and Root-Zone ASCAT Soil Moisture Products Into Rainfall-Runoff Modeling [J].
Brocca, Luca ;
Moramarco, Tommaso ;
Melone, Florisa ;
Wagner, Wolfgang ;
Hasenauer, Stefan ;
Hahn, Sebastian .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2012, 50 (07) :2542-2555
[6]  
Charbonneau F.J., 2017, Nat. Resour. Can. Ott. Geomat. Can. Open File, V34, P78, DOI DOI 10.4095/301670
[7]   Compact Decomposition Theory [J].
Cloude, S. R. ;
Goodenough, D. G. ;
Chen, H. .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2012, 9 (01) :28-32
[8]  
Cloude SR, 2002, INT GEOSCI REMOTE SE, P641, DOI 10.1109/IGARSS.2002.1025131
[9]   The Potential of ALOS-2 and Sentinel-1 Radar Data for Soil Moisture Retrieval With High Spatial Resolution Over Agroforestry Areas, China [J].
Cui, Huizhen ;
Jiang, Lingmei ;
Paloscia, Simonetta ;
Santi, Emanuele ;
Pettinato, Simone ;
Wang, Jian ;
Fang, Xiyao ;
Liao, Wanjin .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
[10]   Optimizing Soil Moisture Retrieval: Utilizing Compact Polarimetric Features with Advanced Machine Learning Techniques [J].
Dabboor, Mohammed ;
Atteia, Ghada ;
Alnashwan, Rana .
LAND, 2023, 12 (10)