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A sequential iterative dual-filter for Lidar terrain modeling opticomplex forested environmentsmized for complex forested environments

Abstract : This paper introduces a sequential iterative dual-filter method for filtering Lidar point clouds acquired over rough and forested terrain and computing a digital terrain model (DTM). The method belongs to the family of virtual deforestation algorithms that iteratively detect and filter objects above-the ground surface. The method uses both points and raster models to do so. The algorithm performance was first tested over a complex badlands environment and compared to a reference model obtained using a traditional TIN-Iterative approach. It was further tested on a benchmark site of the ISPRS (site 5) representing mainly forests and slopes. Over badlands, the resulting DTM elevation RMSE was 0.14 m over flat areas, and increased to 0.28 m under forested and rough terrain. The later value was 12.5% lower than the one obtained with a TIN-Iterative approach. Over the ISPRS site, the TIN-Iterative model provided better results for 3 out of the 4 sample sites. But the proposed algorithm, still worked fairly well provided a total classification error of 5.52%, and is well ranked compared with other algorithms. While the TIN-iterative approach might work better with low density, the proposed one is a good alternative to process high density point cloud and compute DTMs suitable for modeling either hydrodynamic or morphological processes under forest cover at a local scale. (C) 2012 Elsevier Ltd. All rights reserved.
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https://hal.inrae.fr/hal-02605312
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Submitted on : Saturday, May 16, 2020 - 10:48:45 AM
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C. Vega, S. Durrieu, J. Morel, T. Allouis. A sequential iterative dual-filter for Lidar terrain modeling opticomplex forested environmentsmized for complex forested environments. Computers & Geosciences, Elsevier, 2012, 44 (23), pp.31-41. ⟨10.1016/j.cageo.2012.03.021⟩. ⟨hal-02605312⟩

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