【作者】 李晶莹；

【导师】 殷青军；

【作者基本信息】 青海师范大学 ， 地图学与地理信息系统， 2011， 硕士

【摘要】 本文选择青海省玛多县为土地沙化监测的典型研究区,影像数据来自美国的QuickBird遥感卫星,经度范围98°04′12.9″～98°10′42.28″,纬度范围34°42′5.9″～34°47′29″,面积为100平方公里,影像的过境时间是2007年8月,全色段空间分辨率为0.61m,多光谱空间分辨率为2.44m,影像数据共有四个多光谱波段,分别为:B(450～520nm)、G (520～600nm)、R (630～690nm)、NIR (760～900nm)波段。由于分辨率较高的全色波段数据为黑白影像,包含的光谱信息量较少,本文选择全色和多光谱波段融合进行研究。经辐射定标、大气校正图像融合、几何纠正处理后再进行面向对象分类。在研究中采用了QuickBird高分辨率遥感影像,应用面向对象技术方法对研究区进行了土地沙化分类分级,提取沙化信息,达到了较好的分类精度。此方法与人工解译相比,大大提高了工作效率,具有重要的推广应用价值。更多还原

【Abstract】 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.更多还原