i.rvi.prediction(1)    Grass User's Manual    i.rvi.prediction(1)



NNAAMMEE
       ii..rrvvii..pprreeddiiccttiioonn  - Calculates ground features, e.g. plant
       cover, by remote sensing data  using  a	given  regression
       model
       _(_G_R_A_S_S _I_m_a_g_e _P_r_o_c_e_s_s_i_n_g _P_r_o_g_r_a_m_)

SSYYNNOOPPSSIISS
       ii..rrvvii..pprreeddiiccttiioonn
       ii..rrvvii..pprreeddiiccttiioonn hheellpp
       ii..rrvvii..pprreeddiiccttiioonn    mmooddeell==_n_a_m_e	 bbaanndd11==_n_a_m_e    bbaanndd22==_n_a_m_e
       bbaanndd33==_n_a_m_e oouuttppuutt==_n_a_m_e

DDEESSCCRRIIPPTTIIOONN
       This programs calculate ground feature, e.g. plant  cover,
       by remote sensing data using a given regression model. The
       input imagery is assumed with three optical bands: visible
       band1 and band2 and another infrared band3

OOPPTTIIOONNSS
   PPaarraammeetteerr::
       mmooddeell==_n_a_m_e
	      rvi regression model input file

       bbaanndd11==_n_a_m_e
	      visible band1 input file

       bbaanndd22==_n_a_m_e
	      visible band2 input file

       bbaanndd33==_n_a_m_e
	      infrared band3 input file

       oouuttppuutt==_n_a_m_e
	      output ground feature calculated

       The  current  region  definition  and  mask  settings  are
       respected when reading the input map.

NNOOTTEESS
       The ground feature of each pixel by remote sensing data is
       calculated  using rvi regression model. After run r.ratio-
       nal.regression, a rvi model is a coefficient  vector  with
       the definition of:



				 a[0]x1 + a[1]x2 + a[2]x3 + a[6]
	       ground feature = ---------------------------------
				 a[3]x1 + a[4]x2 + a[5]x3 + 1.0


SSEEEE AALLSSOO
       _r_._r_a_t_i_o_n_a_l_._r_e_g_r_e_s_s_i_o_n

       _r_._l_i_n_e_a_r_._r_e_g_r_e_s_s_i_o_n

AAUUTTHHOORR
       CERL

       _L_a_s_t _c_h_a_n_g_e_d_: _$_D_a_t_e_: _2_0_0_2_/_0_1_/_2_5 _0_5_:_4_5_:_3_3 _$



GRASS 5.0				      i.rvi.prediction(1)
