The famed Great Wall of China stretches some 3

000 kilometers （1

850 miles）. High-resolution satellite remote sensing provides cheap and quick data resources for delineating the Great Wall. In this paper

the remote sensing mechanism and spectral characteristics of the Great Wall segment in remote sensing imagery were analyzed. Due to the similar spectral response feature of Great Wall to road and sand

threshold for bands is not an effective method for the extraction of Great Wall. Thus

A gray-slope algorithm is introduced

which can extract Great Wall information effectively and easily. Due to the extensive destroy to the Great Wall

it is only 1 or 2 pixels wide in IKONOS imagery. And the gray level between Great Wall and other objects around it is very different

that is

the change of gray level along Great Wall is greater than that of road and sand. Based on these two characteristics and bands threshold

the gray-slope method makes road and sand separated from the Great Wall easily. Yulin County in Shan’xi Province is selected as a case study area

and IKONOS imagery is used as a data source. The result is satisfied when this method is applied to identify the Ming Great Wall submerged in the Maowusu desert. However

the universality of this algorithm needs to be tested further in other areas as the spatial characteristics and spectral response of Great Wall may vary.