def inverse_oh1994(p, q, theta): """ """ ks, gamma0 = estimate_ks_gamma0(p, q, theta) ep = gamma2ep(gamma0) mv = ep2mv(ep) return mv, ks
def inverse_dubois(hh, vv, theta, wl): """ This function performs the forward modelling using the Dubois model Input: hh: backscatter coefficient in hh pol (dB) vv: backscatter coefficient in vv pol (dB) theta: incidence angel (degree) wl: wavelength (cm) Output: mv: soil moisture h: rms height (cm) """ ep_h = estimate_ep_h(hh, vv, theta, wl) ep = ep_h[0] h = ep_h[1] mv = ep2mv(ep) return mv, h
def inverse_oh1992(p, q, theta): """ Eq. 11 of Oh(1992) Input: p: hh-vv (dB) q: hv-vv (dB) theta: incidence angle (degree) Output: mv: surface soil moisture (v/v) ks: microwave roughness """ # estimate mv gamma0 = estimate_gamma(p, q, theta) ep = gamma2ep(gamma0) mv = ep2mv(ep) # estimate ks # convert from dB to linear q = 10**(q / 10.0) ks = -np.log(1 - q / (0.23 * np.sqrt(gamma0))) return mv, ks
def inverse_oh1992(p,q,theta): """ Eq. 11 of Oh(1992) Input: p: hh-vv (dB) q: hv-vv (dB) theta: incidence angle (degree) Output: mv: surface soil moisture (v/v) ks: microwave roughness """ # estimate mv gamma0 = estimate_gamma(p, q, theta) ep = gamma2ep(gamma0) mv = ep2mv(ep) # estimate ks # convert from dB to linear q = 10**(q/10.0) ks = -np.log(1 - q/(0.23*np.sqrt(gamma0))) return mv, ks