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Usage opportunities of generating digital elevation model with unmanned aerial vehicles on forestry
- Source :
- İstanbul Üniversitesi Orman Fakültesi Dergisi, Vol 66, Iss 1, Pp 104-118 (2016)
- Publication Year :
- 2016
- Publisher :
- İstanbul University, 2016.
-
Abstract
- Unmanned Aerial Vehicles (UAVs) are sustained in flight by aerodynamic lift and guided without an onboard crew, they may be expandeble or recoverable and can fly autonomously or semiautonomously. Within the scope of study, new generation series autonomous UAV brand which is Trimble UX5 is used for generating high accuracy digital model model and obtaining high accuracy image in Istanbul University research and application forest. These obtained images are evaluated with photogrammetry software Trimble Business Center (TBC) v3.1. In this study it was determined that we can obtan high accuracy data image resolution from 2.4 cm to 24 cm depending on the flight altitude with UAV. It was concluded that UAV systems can contribute in forestry work yo obtain sensitive data because of there is no other high accuracy data such as LIDAR. And lack of trained personnel in UAV flights is disadvantages. In this study, UAV and it’s systems were evaluated and tested in all steps. It was expected that geographic information data which requiered forestry applications, can be easly be obtain with UAV. When Digital surface model (DSM) data was assessed comprehensively, it was concluded that the data which obtained from UAV systems are more cheaper, productive and from LIDAR and IFSAR data. At the same time UAV data are relatively sensitive such LIDAR and IFSAR.
- Subjects :
- Unmanned aerial vehicle
digital elevation model
forestry
Forestry
SD1-669.5
Subjects
Details
- Language :
- English, Turkish
- ISSN :
- 05358418
- Volume :
- 66
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- İstanbul Üniversitesi Orman Fakültesi Dergisi
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f98b46ee5577426aa032edeb4d2b7b0d
- Document Type :
- article
- Full Text :
- https://doi.org/10.17099/jffiu.23976