The Effect of Point Density on Point Cloud Filtering Performance

Year 2021, Volume: 2 Issue: 1, 41 - 46, 13.03.2021

Çiğdem Şerifoğlu Yılmaz , Oguz Güngör

https://doi.org/10.48123/rsgis.864234

Abstract

Point cloud filtering is an important step in Digital Terrain Model (DTM) production. Despite the fact that a great body of research has been conducted in this area so far, there are still some problems that have not yet been solved, especially in complex terrains. The fact that the use of user-defined parameters within the presented point cloud filtering methods, and the difficulty of parameter estimation in parallel to the increase in the topography slope and above-ground object diversity, decreases the filtering success. Another problem is the proper specification of the point cloud density to be studied. Point cloud density, which is generally specified considering the ground sampling distance of the DTM, influences the success of the point cloud filtering process, therefore, the accuracy of the DTM produced. In this study, five Unmanned Aerial System (UAS)-based point clouds of different densities were filtered using two different point cloud filtering algorithms Cloth Simulation Filtering (CSF) and gLiDAR to examine the impacts of the point cloud density on filtering success. It was found that the point cloud filtering performance decreased as the point density increased.

Keywords

Point cloud filtering, Digital terrain model, CSF, gLiDAR

Nokta Bulutu Yoğunluğunun Filtreleme Performansı Üzerine Etkisi

Abstract

Nokta bulutu filtreleme sayısal arazi modeli üretiminde çok önemli bir aşamadır. Şimdiye kadar bu alanda pek çok çalışma yapılmıştır ancak, özellikle kompleks zeminlerde hala aşılamayan bazı sorunlar vardır. Sunulan yöntemlerde çoğunlukla kullanıcı girişli parametreler kullanılması ve parametre kestiriminin, topografya eğimi ve zemin üstü obje çeşitliliği arttıkça zorlaşması filtreleme başarısını düşürmektedir. Bir diğer sorun ise çalışılacak nokta bulutu yoğunluğunun uygun şekilde belirlenmesidir. Üretilecek sayısal arazi modelinin yer örnekleme aralığına göre belirlenen yoğunluk aynı zamanda nokta bulutunun filtreleme başarısını ve dolayısıyla elde edilecek sayısal arazi modelinin hassasiyetini de etkilemektedir. Bu çalışmada, 5 farklı yoğunlukta üretilen insansız hava aracı tabanlı nokta bulutları, nokta bulutu yoğunluğunun filtreleme başarısına etkilerini incelemek için Cloth Simulation Filtering (CSF) ve gLiDAR filtreleme algoritmaları kullanılarak filtrelenmiştir. Elde edilen sonuçlara göre nokta bulutu yoğunluğu arttıkça filtreleme başarısının düştüğü görülmüştür.

Keywords

Nokta bulutu filtreleme, Sayısal arazi modeli, CSF, gLiDAR

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