İnsansız hava araçları ile yüksek hassasiyette sayısal yükseklik modeli üretimi ve ormancılıkta kullanım olanakları

Akgül, Mustafa; Yurtseven, Hüseyin; Demir, Murat; Akay, Abdullah; Gülci, Sercan; Öztürk, Tolga

doi:10.17099/jffiu.23976

Cited by 27 publications

(8 citation statements)

References 21 publications

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“…Briefly, topographic maps with high resolution can be derived from the use of UAV systems. It provides convenience for researchers by removing time and area constraints (Akgül et al, 2016). The orthophotos can be produced by RGB (Red-greenblue) images obtained with UAV , herewith information on terrain topography, land cover and soil erosion can be evaluated (d'Oleire-Oltmanns et al, 2012;Bendinget al, 2014;Inan and Öztürk, 2016).…”

Section: Results and Findingsmentioning

confidence: 99%

“…UAV classes, the specification of mounted sensors, flight height and speed may vary according to the aim and specific scope of the research (Watts et al, 2012;Wings et al, 2014;Gülci and Akay, 2016). The UAV-based studies that include before and after the flight stages, should be well designed for the quality of produced photogrammetric data and security (Akgül et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Generation and Assessment of High Resolution Digital Surface Model by Using Unmanned Air Vehicle Based Multicopter

Gülci

Dindaroğlu

Gündoğan

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Unmanned air vehicle systems (UAVSs), which are presently defined as effective measuring instruments, can be used for measurements and evaluation studies in fields. Furthermore, UAVs are effective tools that can produce high-precision and resolution data for use in geographic information system-based work. This study examined a multicopter (hexacopter) as an air platform to seek opportunity in generating DSM with high resolution. Flights were performed in Kahramanmaras Sutcu Imam University Campus area in Turkey. Pre-assessment of field works, mission, tests and installation were prepared by using a Laptop with an adaptive ground control station. Hand remote controller unit was also linked and activated during flight to interfere with emergency situations. Canon model IXSUS 160 was preferred as sensor. As a result of this study, as mentioned previous studies, .The orthophotos can be produced by RGB (Red-green-blue) images obtained with UAV, herewith information on terrain topography, land cover and soil erosion can be evaluated.

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Section: Results and Findingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Generation and Assessment of High Resolution Digital Surface Model by Using Unmanned Air Vehicle Based Multicopter

Gülci

Dindaroğlu

Gündoğan

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…During the first stage of the study, current status of the road should be primarily modeled on computer environment in an accurate manner in order to conduct driving analyses on Plateia 2013 software and to be able to obtain healthy results. Nowadays in forestry applications, RTK GPS (Gulci et al 2015), Satallite data (Jacobsen 2013;White et al 2010), Airborne Lidar system (Azizi et al 2014;Guan et al 2014) and UAV systems (Akgul et al 2016;Uysal et al 2015) are used to generate Digital Elevation Model (DTM) with high precision.…”

Section: Road Data Inputmentioning

confidence: 99%

Investigation of recreational vehicles maneuverability on forest roads by computer-aided driving analysis

Akgül

Demir

Öztürk

et al. 2016

The Baltic Journal of Road and Bridge Engineering

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Forest road planning is a time-consuming and complicated process both because it requires environmentfriendly road building, and due to the requirement to observe economic costs. This costs will be increase depending on maneuverability requirements of vehicle dimension. The main aim of this study is to analyze maneuverability of recreational vehicles on forest roads that primarily serve utilization of vehicles intended for production as well as geometrical characteristics of roads on computer environment. Both dynamic horizontal driving analysis and dynamic vertical driving analysis can be made with Autopath driving analysis module of Plateia 2013 software. Computer-aided horizontal driving analysis, which is used in examination of opportunities for utilization of available roads by different vehicle types, appears as an effective method for the decision maker in consideration of geometrical standards of vehicles during decision-making process. Graphical report is another output of driving analysis which visually presents vehicle maneuverability. In this context, Maneuverability of automobile, midibus and bus were analyzed on forest road with 4 m platform width. As a results of this study, it was concluded that computer-aided driving analysis is a beneficial tool in decision making process for re-planning of forest roads. As a consequence, it is considered that driver safety, as well as project costs, would increase by utilization of driving analysis during forest road planning and design.

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“…Over the last decade UAV map production systems have become an important technology for different disciplines (Akgül et al 2016;Öztürk et al 2017;Ulvi 2018;Ulvi and Toprak 2016;Ulvi et al 2020). The main reason for the spread of this system is the availability of flight platforms and technology for civilian users, as well as reductions in costs.…”

Section: Introductionmentioning

confidence: 99%

Classification of UAV point clouds by random forest machine learning algorithm

Zeybek

2021

Turkish Journal of Engineering

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Unmanned aerial vehicle Point cloud Classification Random forestToday, unmanned aerial vehicle (UAV)-based images have become an important data sources for researchers who deals with mapping from various disciplines on photogrammetry and remote sensing. Reconstruction of an area with three-dimensional (3D) point clouds from UAV-based images are an essential process to be used for traditional 2D cadastral maps or to produce a topographic maps. Point clouds should be classified since they subjected to various analyses for extraction for further information from direct point cloud data. Due to the high density of point clouds, data processing and gathering information makes the classification of point clouds a challenging task and may take a long time. Therefore, the classification processing allows an optimal solution to acquire valuable information. In this study, random forest machine learning algorithm for classification processing is applied with radiometric features (Red band, Green band and Blue band) and geometric characteristics derived from covariance feature (curvature, omnivariance, flatness, linearity, surface variance, anisotropy and normalized terrain surface) of points. In addition, the case study is presented in order to test applicability of the proposed methodology to acquire an accuracy and performance of random forest method on the UAV based point cloud. After the classification processing, a class assigned each point from the model was compared with the reference data class. Lastly, the overall accuracy of the classification was achieved as 96% and the Kappa index was reached to 91% on data set.

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İnsansız hava araçları ile yüksek hassasiyette sayısal yükseklik modeli üretimi ve ormancılıkta kullanım olanakları

Cited by 27 publications

References 21 publications

Generation and Assessment of High Resolution Digital Surface Model by Using Unmanned Air Vehicle Based Multicopter

Generation and Assessment of High Resolution Digital Surface Model by Using Unmanned Air Vehicle Based Multicopter

Investigation of recreational vehicles maneuverability on forest roads by computer-aided driving analysis

Classification of UAV point clouds by random forest machine learning algorithm

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