Suffering from the interference of all kinds of background factors (clouds

shadows and pollution) and complicated changes of water itself in spectrum and shape

the process of water extraction can still not be completely automatic. Based on the goal of automatic interpretation of diverse water bodies under complicated backgrounds a new water extraction process is put forward by practical requirements. Adaptive segmentation or classification

local iteration

and post processing are the key steps of the proposed method mainly designed for the automatic extraction of large-scale water body information from Landsat TM/ETM images. The experiments are conducted on two typical research areas

Balkhash Lake and the Yangtze River region

each with 8 scenes of TM images. And we found that the proposed method can effectively overcome the interference factors

such as the cloud

shadow

water changes

which can achieve better extraction effect and preliminarily satisfy the actual application needs.