Soil moisture inversion at L-band using a dual-polarization technique: A model-based sensitivity analysis

2002 ◽  
Vol 23 (16) ◽  
pp. 3209-3227 ◽  
Author(s):  
N. S. Chauhan
Keyword(s):  
Sensitivity Analysis ◽  
Soil Moisture ◽  
Dual Polarization ◽  
Model Based ◽  
Polarization Technique ◽  
L Band ◽  
Soil Moisture Inversion

scholarly journals Field-Scale Soil Moisture Retrieval Using PALSAR-2 Polarimetric Decomposition and Machine Learning

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 35
Author(s):  
Xiaodong Huang ◽  
Beth Ziniti ◽  
Michael H. Cosh ◽  
Michele Reba ◽  
Jinfei Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Canopy Cover ◽  
The United States ◽  
Optical Data ◽  
Study Region ◽  
Model Based ◽  
Key Indicator ◽  
Ground Measurement ◽  
L Band

Soil moisture is a key indicator to assess cropland drought and irrigation status as well as forecast production. Compared with the optical data which are obscured by the crop canopy cover, the Synthetic Aperture Radar (SAR) is an efficient tool to detect the surface soil moisture under the vegetation cover due to its strong penetration capability. This paper studies the soil moisture retrieval using the L-band polarimetric Phased Array-type L-band SAR 2 (PALSAR-2) data acquired over the study region in Arkansas in the United States. Both two-component model-based decomposition (SAR data alone) and machine learning (SAR + optical indices) methods are tested and compared in this paper. Validation using independent ground measurement shows that the both methods achieved a Root Mean Square Error (RMSE) of less than 10 (vol.%), while the machine learning methods outperform the model-based decomposition, achieving an RMSE of 7.70 (vol.%) and R2 of 0.60.

L-Band Radar Estimation of Forest Attenuation for Active/Passive Soil Moisture Inversion

2009 ◽  
Vol 47 (9) ◽  
pp. 3026-3040 ◽  
Author(s):  
M. Kurum ◽  
R.H. Lang ◽  
P.E. O'Neill ◽  
A.T. Joseph ◽  
T.J. Jackson ◽  
...  
Keyword(s):  
Soil Moisture ◽  
L Band ◽  
Soil Moisture Inversion

Detection of Inland Open Water Surfaces Using Dual Polarization L-Band Radar for the Soil Moisture Active Passive Mission

2016 ◽  
Vol 54 (6) ◽  
pp. 3388-3399 ◽  
Author(s):  
Seung-bum Kim ◽  
Jeffrey D. Ouellette ◽  
Jakob J. van Zyl ◽  
Joel T. Johnson
Keyword(s):  
Soil Moisture ◽  
Open Water ◽  
Dual Polarization ◽  
Water Surfaces ◽  
L Band
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