Based On The Object-oriented And The Remote Sensing Image Of High

In this paper, the author chooses MaDuo county of Qinghai province for Sandy Desertification monitoring.It is the typical study area, and the data is the QuickBird that the American satellite image data of remote sensing.The Longitude range is 98°04′12.9″—98°10′42.28″.The latitudes is 34°42′5.9″—34°47′29″. The area is 100 square kilometers; the transit time is in August 2007. Full-color segment space is 0.61 m, and the Multi-spectral resolution is 2.44 m. Image data have four Multi-spectral bands,the respectively regions is: B (450 ~ 520nm), G (520 ~ 600nm), R (6.3 ~ 690nm), NIR (7.6 ~ 900nm) bands. Due to the high resolution full-color band data is black and white images, including less spectral information. This paper merge more full-color and Multi-spectral bands. Through mergging of radiation calibration, atmospheric correction, mixing bands of the image, geometric correction, after that process the object-oriented classification.In the study used the QuickBird high-resolution remote sensing image,and apply the object-oriented technology method in the study area .ECognitiong classification software on the Sandy Desertification classification, extracted the desertification information classification, and obtain a good classification accuracy. This method compared with artificially interpretation, which greatly improved the extracted by remote sensing image the speed of desertification information.