As the continued excavation for economic benefits of bamboo resources

it has been a problem which is urgent need to solve to know the distribution and dynamic information of bamboo forest timely and accurately. However

the traditional field survey cannot meet this demand. The development of Geomatics technology has provided new approaches to seize the bamboo forest distribution information

but restricted by many factors

the extraction of bamboo information is not effective for quite a long time. On the basis of former studies

the paper took the highresolution of ALOS image as the data source and focuses on bamboo forest information extraction in Shunchang County

which is hilly area in Southern China

with the algorithm of Filmbased & Classoriented which has been put forward by us

in order to test the effectiveness of the method. In addition to using the traditional classification method of pixelbased

it introduced the objectoriented method that has been fashional in recent years

in order to compare them. What's more

it processed the nonfilm area further for higher bamboo forest information extraction accuracies. Verifying with the surveying points showed that the extraction accuracies with pixelbased and objectoriented were 84.42% and 86.46% respectively with Kappa of 0.677 3 and 0.723 4. Four results could be indicated. Firstly

both these two methods showed that the algorithm of Filmbased & Classoriented was well suitable for the bamboo forest information extraction

and could supply a significant technical reference to the image interpretation of hilly area. Secondly

from the accuracy

the method of objectoriented was a little better than the pixelbased one. Nevertheless

from the visual effect of view

there were spiced salt shapes in the figure of pixelbased

while that of objectoriented had better continuity. Although the results of these two methods were little different

the objectoriented one may be more suitable for the highresolution images such as ALOS image. Thirdly

it is hard to interpret and extract the bamboo forest information with the help of spectral features from remote sensed images single

so we have to bring in the texture information to raise the extraction accuracy. In addition to these

the terrain factors including elevation

slope and aspect are needed to regard carefully. We could infer that the bamboo forest information extraction accuracy will be raised more if the terrain combination conditions were taken to account.