【摘要】 数字高程模型(DEM)是地理信息系统和遥感等领域所必需的核心数据,已经应用到很多方面。本文提出了一种利用ICESat GLA14数据优化SRTM1数据的方法。首先,根据SRTM误差分布去除GLA14数据中的粗差点,完成坐标基准和高程基准的统一。其次,分析了SRTM误差随坡度、坡向的变化规律,并建立了误差模型。最后,将GLA14数据随机划分为控制点和检查点,使用控制点采用最小二乘法拟合误差,使用检查点评价精度提升效果,并多次重复随机划分的过程,验证算法的有效性。实验结果表明:使用该算法针对不同地区不同地形的DEM进行了实验,均取得了很好的效果。更多还原

【Abstract】 DEM has become the kernel data of GIS and remote sensing,and has been applied to various areas.An approach to optimize SRTM1 data using ICESat GLA14 data is proposed in this paper.First,the outliers of GLA14 data is filtered out according to the error distribution of SRTM1 and the coordinate system and height reference of both data is unified.Then,the relationship between the error of SRTM1 and the slope and the aspect of land is analyzed and an error model of SRTM1 is established.Finally,we divide the GLA14 data into control points and check points randomly,use the control points to fit the error model by least square method,use the check points to evaluate the effect of optimization.We repeat the divide several times to prove the effectiveness of our approach.The results of experiment show that our approach has a good effect among different areas and different topography.更多还原