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UPDATING LIDAR DSM USING HIGH RESOLUTION STEREO-BASED DSM FROM WORLDVIEW-2

机译:使用来自WorldView-2的高分辨率立体声DSM更新LIDAR DSM

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In recent years, the acquisition and processing techniques of high resolution Digital Surface Models (DSM) have been rapidly improved. Airborne LiDAR production as a well-known and high quality DSM is still unbeatable in elevation accuracy and highly produced dense point clouds. In this paper, the objective is to update an old but high quality DSM produced by LiDAR data using a DSM generated from high resolution stereo satellite images. A classification-base algorithm is proposed to extract building changes between DSMs in two epochs. For image classification procedure, the DSM and Worldview-2 orthorectified images have been used as input data for a fuzzy-based classification method. Then, extracted buildings are classified into unchanged, destroyed, new, and changed classes. In this study a dataset related to Munich city, has been utilized to test the experimental investigation. The implemented qualitative and quantitative assessments demonstrate high quality as well as high feasibility of the proposed approach.
机译:近年来,高分辨率数字表面模型(DSM)的采集和处理技术得到了迅速改善。空气传播的激光雷达作为众所周知和高质量的DSM生产仍然无法在高度精度和高度产生的密集点云中无法匹配。在本文中,目的是使用高分辨率立体声卫星图像产生的DSM更新由LIDAR数据产生的旧的但高质量的DSM。提出了一种分类基础算法,以提取两个时代中DSM之间的建筑变化。对于图像分类过程,DSM和WorldView-2逆映射图像已被用作基于模糊的分类方法的输入数据。然后,提取的建筑物被分类为不变,销毁,新的和更改的类。在这项研究中,与慕尼黑市有关的数据集已被利用来测试实验调查。实施的定性和定量评估表现出高质量,以及所提出的方法的高可行性。

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