The forest ecosystem is the important component in the terrestrial ecosystem and plays an important role in global change study.Aboveground biomass（AGB） of forest ecosystem is an important factor in global carbon cycle studies.This paper uses the ETM

+

image in combination with the field measurement data to estimate the aboveground biomass.After getting the various vegetation indexes

we get the LAI（Leaf Area Index）

and then build the correlation between the LAI and field biomass data to get the initial biomass map.In addition

a shortwave infrared based vegetation index（SWVI） was calculated to get the forest age spatial distribution map

then

by incorporating the stand age and forest category information into the new regression model to get the final biomass map.We found that the AGB estimation for overall was related to the LAI and SR（Simple Ratio）（R

2

=0.895）

and for Chinese fir has a good correlation with the LAI and NDVI（R

2

=0.93）.The LAI and AGE are good predictors for the aboveground biomass of Conifer（R

2

=0.937）;for the Broadleaf and Masson pine mix forest

the age is correlated to the AGB（R

2

=0.792）;for the Broadleaf and Chinese Fir mix forest

the AGB was strongly related to the LAI and SR（R

2

=0.931）.The result shows that combining the stand age and forest categories information into the AGB estimation is a better way to improve the accuracy of aboveground biomass estimation with the optical remote sensing

the high-resolution forest stand age and aboveground biomass spatial distribution map can provide basic and effective information for the forest sustainable development and management.