The study of automatically extracting water information in city zone based on SPOT5 image

This article look the main city zones as the research area, and study the method of extracting water information in SPOT5 image. We choose the SPOTS as the research data. We can get the water and shadow information from the image by setting the divided line in band SWIR. By using the spectrum characteristic, the space characteristic and time characteristic, such as index of shape, The decision tree model of automatically extracting water information in city zone from SPOTS image to get the water information from the area can be set up. For estimating the precision of the model, the model and supervised classification method in the whole area and in some special zone that has much building shadow are compared. The result tells that in the whole area there is some improvement between the model and supervised classification method, it's about 2.5%; especially in the special zone there is large improvement, it reaches to 11.6%. Beside that the model is good in transplanting, maybe the divided line is different.