Estimating Horizontal Displacement between DEMs by Means of Particle Image Velocimetry Techniques
Estimating Horizontal Displacement between DEMs by Means of Particle Image Velocimetry Techniques
复制标题
利用粒子图像测速技术估算 DEM 之间的水平位移
作者：
J. F. Reinoso;C. León;J. Mataix
到目前为止，数字地形模型(DTM)的精度几乎完全是通过计算其高度变量来研究的。然而，被忽视的水平分量对某些线性特征的定位精度有很大的影响，例如在水文特征中。为了填补这一空白，我们提出了一种不同于地质法的测量方法，涉及流体力学(水和空气流动)或空气动力学。提出了用粒子图像测速(PIV)算法来估计格网格式的数字高程模型(DEM)之间的水平差异。在对PIV算法估计的位移应用比例因子后，预测的平均误差约为空间分辨率最高的DEM单元大小的七分之一，以及空间分辨率最小的DEM单元大小的十九分之一左右。我们的方法允许将所有类型的DEM转换为DEM格式后进行比较，同时还允许比较来自不同捕获方法的数据，即LiDAR和摄影测量数据源。
To date, digital terrain model (DTM) accuracy has been studied almost exclusively by computing its height variable. However, the largely ignored horizontal component bears a great influence on the positional accuracy of certain linear features, e.g., in hydrological features. In an effort to fill this gap, we propose a means of measurement different from the geomatic approach, involving fluid mechanics (water and air flows) or aerodynamics. The particle image velocimetry (PIV) algorithm is proposed as an estimator of horizontal differences between digital elevation models (DEM) in grid format. After applying a scale factor to the displacement estimated by the PIV algorithm, the mean error predicted is around one-seventh of the cell size of the DEM with the greatest spatial resolution, and around one-nineteenth of the cell size of the DEM with the least spatial resolution. Our methodology allows all kinds of DTMs to be compared once they are transformed into DEM format, while also allowing comparison of data from diverse capture methods, i.e., LiDAR versus photogrammetric data sources.