Abstract:

Unpiloted aerial vehicles with built-in power system, carrying useful freight, let to fly automatically or by a remote control system are called Unmanned Aerial Vehicles. The UAVs used for various purposes in civil and military fields today, too, have exhibited development as result of developments in aviation, electronics, communications and navigation technologies in parallel with the developments which occurred in the field of science and technology in the 20. century. These have ensured ease of use and exhibited a rapid increase due to reasons such as, the sensor systems have become smaller, mobility has increased and they can fly at lower altitudes. Use of Unmanned Aerial Vehicles (UAVs) has become widespread in recent times as result of this. Particularly, in addition to imaging studies, use of UAV vehicles has come in the agenda for photogrammetric surveys in small scale areas against manned air vehicles, landslide and erosion monitoring, and for purposes of observing agricultural activities (determining the agricultural crop pattern, observing plant diseases, steering small scale agricultural policies, etc.). In this study the TM-GEO1 unmanned aerial vehicle designed and produced by the Gaziosmanpaşa University (GOU) Geomatics Engineering Department and the firm TEKNOMER has been used. Gaziosmanpaşa University Taşlıçiftlik Campus agricultural land and the Tokat Agricultural Research Institute pilot lands have been selected as the study area.. The test study surface areas are 342,37 hectare and 9 hectare, respectively and the flight altitude has been planned as 100 meters, the flight columns as 80% longitudinal and 60% transversal overlapped. Total 3044 numbers of photos within the campus area and 60 numbers of photos in the agricultural area have been evaluated. The photos obtained have been evaluated by PIX4D software and the image classifications have been made by using the Ecognition Developer software. 41 numbers of Ground Control Points have been included in the evaluation; images have been produced by pixel matching algorithms for the agricultural area. As result of evaluation it has been obtained as RMS=±0.015 m.

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