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An Adaptive Method for the Construction of Digital Terrain Model from Lidar Data

机译:利用LIDAR数据构建数字地形模型的自适应方法

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To generate a DTM, measurements from above-ground features such as buildings, vehicles, and vegetation have to be classified and removed, which is nontrivial. The above-ground features present great challenges in conjunction with varying slopes of the ground. In this paper, we present a method to remove above-ground LiDAR measurements and generate DTMs by using adaptive window size according to the local gradients. Iterative construction measurements are performed until difference between two iterations are minimum. In our experiments, we apply our method to the LiDAR data acquired from the downtown region of New Orleans. It was demonstrated that the adaptive window method can remove most of the above-ground points effectively.
机译:为了产生DTM,必须对诸如建筑物,车辆和植被之类的地上的地面的测量来进行分类和去除,这是非虚拟的。地上的特征存在巨大的挑战与地面的不同倾斜。在本文中,我们介绍了一种方法来除去地上的LIDAR测量并通过根据本地梯度使用自适应窗口大小来生成DTM。执行迭代施工测量,直到两个迭代之间的差异最小。在我们的实验中,我们将我们的方法应用于从新奥尔良市中心收购的LIDAR数据。据证明,自适应窗口方法可以有效地消除大部分地上的点。

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