Mapping of laurel (Laurus nobilis L.) distribution areas with a multispectral camera in Karacabey State Forest Enterprise

In forest areas, inventory studies of non-wood forest products require quite a long time and intensive labor. Nowadays, with the development of technology, studies are carried out to shorten this intensive labor and the long required time in inventory studies. In this study; it is aimed to determine and map the distribution of the laurel plant species, which are found in forest areas for the first time in our country, using an Unmanned Aerial Vehicle (UAV) integrated with a multispectral camera. Our study areas were determined as all areas where laurel spreads or may potentially spread in Bursa Regional Directorate of Forestry Karacabey State Forest Enterprise. Sampling areas were determined as a result of the draft laurel inventory study carried out by the technical personnel of Bursa Regional Directorate of Forestry, and flights were made with UAVs in order to produce orthophotos in these areas. The UAV used for flying is the DJI Matrice 210 V2 series, and a Micasence RedEdge MX multi-band camera is integrated on it as a multispectral camera. In Karacabey State Forest Enterprise, 30 sampling areas (42.5 hectare) are determined. In this study, the sampling rate was calculated as a minimum of 22.6%. The flights were made between 10:00 and 15:00 for the purpose of benefitting from the sunlight at the maximum level. Five-band (red, green, blue, red edge and near infrared) images were obtained with the multispectral camera which is integrated into the UAV in 44 flights. All of these 44 flights made in the determined sample areas were set to cover 80% from the front and 70% from the side in order to obtain the best quality data from 120 meters altitude using the mission flight mode. Five band orthophotos were obtained in Agisoft Metashape and Pix4D Mapper softwares using the produced images. Plant indices were derived by applying various band combinations on the produced orthophotos, and object-based classification was made using eCognation Developer software by making use of these indices. In order to make classification, ground control points were taken from the laurel quarry areas in the field by using precision Differential GPS (DGPS) to create a reference. By using these terrestrial control points, classifications were made and their controls were provided. As a result of the analysis, Kappa values were found between 0.56 and 0.92 in all sampling areas. The maps of the laurel distribution areas were determined on ArcMap and integrated into the stand maps.