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   oouutt--
       ppuutt==_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.rational.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)
