Semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces
By Yisok Oh, Kamal Sarabandi, Fawwaz T. Ulaby. IEEE Transactions on Geoscience and Remote Sensing, 2002
304 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Environmental Engineering, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/20f45ec8f191a08b6b97689681e2efca34a2757d
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Citations in the corpus
- A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data (2009, methodology): “Clearly, the radar sensitivity to soil moisture using the Washita 92 data is significantly different from two theoretical approaches (SPM and IEM) and two empirical solutions [4], [ 18 ].”
- Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation (2013, methodology): “Since this dataset was not sufficient for training the ANN and completely setting the neurons and weights, the AIEM and Oh models (Fung, 1994; Oh et al., 2002; Wu & Chen, 2004) were used for simulating co-polar and cross-polar data, respectively, which were included in the training set.”
- Quantitative retrieval of soil moisture content and surface roughness from multipolarized radar observations of bare soil surfaces (2004, methodology): “The semiempirical polarimetric model in [7] was developed based on existing theoretical scattering models and an extensive database obtained by ground-based polarimetric scatterometers and the Jet Propulsion Laboratory (JPL) airborne SAR system over a wide variety of bare soil surfaces.”