CAJ | 학술논문

提出了一种山地区域基于DEM地性线的控制纠正新方法,该方法以数字地形模型.DEM为无几何变形的控制基准纠正卫星影像.阐述了提取沟谷、山脊、山峰和凹地区域的地性线的原理和算法,给出了山地区域基于地性线进行卫星图像几何精纠正实施步骤,进一步讨论了地性线提取、控制点采集存在的问题,以及解决问题的途径.实验结果表明,对于山地区域,地性线的空间数量数倍于水系、道路等常规地图层;地性线来源于DEM,其空间稳定性和可靠性更高,可以用于山地区域的卫星影像的严格控制纠正.用该方法进行几何纠正处理,几何误差能控制在一个像元的水平上.
제출료일충산지구역기우DEM지성선적공제규정신방법,해방법이수자지형모형.DEM위무궤하변형적공제기준규정위성영상.천술료제취구곡、산척、산봉화요지구역적지성선적원리화산법,급출료산지구역기우지성선진행위성도상궤하정규정실시보취,진일보토론료지성선제취、공제점채집존재적문제,이급해결문제적도경.실험결과표명,대우산지구역,지성선적공간수량수배우수계、도로등상규지도층;지성선래원우DEM,기공간은정성화가고성경고,가이용우산지구역적위성영상적엄격공제규정.용해방법진행궤하규정처리,궤하오차능공제재일개상원적수평상.
Highly accurate geometric correction is fundamental to the application of satellite images. In highly accurate geometric correction of remote sensing images for precise match to the base maps,the difficulties in capturing ground control points (GCPs),insufficient number of GCPs and low accuracy of the geo-referenced images remain to be frequent issues. In search for solutions to these issues,this paper proposes a new method for the geometric correction of satellite images for the mountain areas based on the terrain feature lines extracted from the Digital Elevation Model (DEM). This method uses DEM as the base maps without any geometric distortion for the geometric correction of satellite images. This paper presents the theories and method to extract terrain feature lines,such as gorges,mountain ridges,peaks and concaves and describes the procedures for the geometric correction for satellite images of mountain areas based on the terrain feature lines. It further discusses the problems in extracting terrain feature lines and capturing of GCPs,as well as the solutions to these issues. The outcome from the experiments shows the number of terrain feature lines of mountains areas are a great many times of those in the conventional map layers of hydrological systems and road networks,and that terrain feature lines extracted from DEM present high stability and reliability and can be applied in the highly accurate geometric correction for satellite images of mountain areas. The results of statistical test show the average geometric error is reduced to the size of one pixel when this method is used in geometric correction.