Employing Pi-SAR polarimetric data acquired in 2002 and 2003

forest biomass estimation approach is stud- ied on Tomakomai forests located in Hokkaido

Japan.The purpose of this project is to develop effective approach for esti- mating forest biomass.The ground truth data of 19 test sites are in hand.In this test sites

one sample stand of 20m×20m are selected and tree height

age

basal area

diameter of breast height and tree species are measured

the biomass is then calculated.The conventional Radar cross section（RCS）method is first investigated.It is found that RCS increases with biomass and becomes saturated rapidly

under the situation of this paper.That is:the L-band RCS saturation levels are found approximately to the biomass of 40t/hm2

with the tree age of 30 years

the tree height of 8m

and the basal area of 30 m

2

/hm

2

.The RCS saturates at 20t/hm

2

for X-band data.Therefore

forest biomass beyond saturation level cannot be estimated utilizing RCS.To search the quantitative relation between high-resolution SAR data and forest parameters

sta- tistical analysis approach is utilized.The probability density function of image amplitude is then investigated

and among different distribution including Rayleigh

log-normal

Weibull and K-distributions

the K-distribution is found to fit best to the L-band data of all polarizations according to the Akaike information criterion（AIC）.The relations between K-distribu- tion index and different tree parameters including biomass

tree age

height

basal area

are investigated.It is found that the tree biomass correlates best with the index parameter.Moreover

K-distribution index increases with biomass beyond RCS saturation level

and the highest correlation coefficient is obtained at cross-polarization.The regression model is de- veloped between K-distribution index and forest biomass at cross-polarization based on 19 test sites data.In August and September of 2005

we further collected ground truth data of 23 test sites.Based on the relation of K-distribution index of cross-polarization and forest biomass

the biomass estimation is made for the 23 test sites.The comparison of estimated bi- omass and measured ground truth data rerifies that the average accuracy of the estimation reaches 85%.It is concluded that

at least for the Hokkaido forests

this empirical model is an effective and superior way of estimating forest biomass from polarimetric SAR data compared with the conventional RCS model.