An investigation of tree extraction from UAV-based photogrammetric dense point cloud

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ORIGINAL PAPER

An investigation of tree extraction from UAV-based photogrammetric dense point cloud Nizar Polat 1

&

Murat Uysal 2

Received: 30 March 2017 / Accepted: 29 July 2020 # Saudi Society for Geosciences 2020

Abstract Manually, tree detection with terrestrial field work is a nonprofit labor in terms of time, cost, and manpower. As a rapid alternative, terrestrial and airborne laser scanners are widely in use for data collecting. But this active remote sensing technology is expensive, especially in local small areas. At this point, unmanned aerial vehicles stand as a new opportunity for data collection platforms for tree detection in both large and local study areas. This study shows the usage of unmanned aerial vehicle as a platform to collect aerial images. The images are used to generate 3D dense point clouds. This point cloud is investigated with the random sample consensus algorithm in order to detect tree. The trees are assumed as or in a cylinder which is geometrically defined with respect to tree’s parameters such as radius. According to the results, the RANSAC algorithm is successful in the detection of trees from unclassified image-based dense point cloud. The 232 individual trees have managed to extract with a rate of 70.1% from 3 different study sites. Keywords Photogrammetry . SfM . UAV . Tree extraction . RANSAC

Introduction Today, the generation of 3D data which refers as point cloud of an interested object or topography is very easy and widely used in various applications such as artifact modeling, topographic mapping, volume calculation, and forestry. The main reason of this expanding usage of point cloud is the developing technology such as computer vision, photogrammetry, laser scanner, and unmanned aerial vehicle (UAV). The current state of obtaining 3D point cloud is mostly based on laser scanners and imagebased dense point cloud (Uysal et al. 2015; Porway et al. 2008; Bhagavathy and Manjunath 2006; Charaniya et al. 2004; Chen and Zakhor 2009; Uray et al. 2015). Especially due to UAV which allows the acquisition of very high–resolution imagery almost at any time and low cost, the utilization has rapidly Responsible Editor: Biswajeet Pradhan * Nizar Polat [email protected] 1

Faculty of Engineering Geomatics Department, HRU (Harran University), Şanlıurfa 63100, Turkey

2

Faculty of Engineering Geomatics Department, AKU, 03200 Afyonkarahisar, Turkey

increased during the past 5 years and has become a rival 3D data to laser scanners (Thiel and Schmullius 2016). The UAV is cheaper as hardware, easy to use, more portable for transportation study area, and more economic at small local fields such as part of urban settlements. Moreover, the image parameters can be easily determined in terms of image overlap, area of interest, and geometric resolution (Suomalainen et al. 2014). The overlap between the images enables stereoscopic image processing and point cloud generation which is described following sections. The popularity of the point cloud usage makes the researchers, especially

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