Implements a variety of microwave radar scattering and soil dielectric models for remote sensing applications.

• to install, type pip install git+https://github.com/djshiltz/radarscatter
• to uninstall, type pip uninstall radarscatter

The two main commands in this package are:

• radarscatter.dielectric() to implement a soil dielectric mixing model
• radarscatter.backscatter() to compute the normalized radar cross section of bare soil

The file validation.py includes several examples that re-produce plots from each model's original publication.

Computes the complex dielectric constant of a soil-water mixture

Hallikainen et al., 1985, "Microwave Dielectric Behavior of Wet Soil - Part I: Empirical Models and Experimental Observations," IEEE Transactions on Geoscience and Remote Sensing.

Inputs:

• clay mass fraction [%]
• sand mass fraction [%]
• volumetric moisture [%]
• radar frequency [GHz]

Mironov et al., 2009, "Physically and Mineralogically Based Spectroscopic Dielectric Model for Moist Soils," IEEE Transactions on Geoscience and Remote Sensing.

Inputs:

• clay mass fraction [%]
• volumetric moisture [%]
• radar frequency [GHz]

Computes the normalized backscattering coefficient of a bare soil surface

Fung et al., 1992, "Backscattering from a Randomly Rough Dielectric Surface," IEEE Transactions on Geoscience and Remote Sensing.

The optional transition function for the reflectivity coefficients is from Wu et al., 2001, "A Transition Model for the Reflection Coefficients in Surface Scattering," IEEE Transactions on Geoscience and Remote Sensing.

The simplified equations for both the IEM model and transition function are listed in Ch. 3 of the textbook: Fung and Chen, 2010, "Microwave Scattering and Emission Models for Users," Artech House.

Inputs:

• radar frequency [GHz]
• radar polarization (hh or vv)
• radar incidence angle [deg]
• soil complex dielectric constant
• surface RMS height [cm]
• surface correlation length [cm]
• surface autocorrelation function shape parameter (1=exponential, 2=gaussian)
• boolean use_transition_function flag

Extension of the IEM where the physical correlation length is replaced by an empirical calibration. These calibrations were given in

• L-band: Baghdadi et al., 2015, "Semi-empirical Calibration of the Integral Equation Model for Co-polarized L-band Backscattering," Remote Sensing.
• C-band: Baghdadi et al., 2006, "Calibration of the Integral Equation Model for SAR Data in C-band and HH and VV Polarizations," International Journal of Remote Sensing.
• X-band: Baghdadi et al., 2011, "Comparison Between Backscattered TerraSAR Signals and Simulations from the Radar Backscattering Models IEM, Oh, and Dubois," IEEE Geoscience and Remote Sensing Letters.

Inputs:

• radar frequency [GHz]
• radar polarization (hh or vv)
• radar incidence angle [deg]
• complex dielectric constant
• surface RMS height [cm]

Baghdadi et al., 2016, "A New Empirical Model for Radar Scattering from Bare Soil Surfaces," Remote Sensing.

Inputs:

• radar frequency [GHz]
• radar polarization (hh or vv)
• radar incidence angle [deg]
• volumetric moisture [%]
• surface RMS height [cm]

Dubois et al., 1995, "Measuring Soil Moisture with Imaging Radars," IEEE Transactions on Geoscience and Remote Sensing.

Inputs:

• radar frequency [GHz]
• radar polarization (hh or vv)
• radar incidence angle [deg]
• real part of soil dielectric constant
• surface RMS height [cm]