Multispectral camera integrations and agricultural applications with unmanned aerial vehicle

This study focuses on increasing productivity in agriculture and analysis of agricultural areas with developing technology. Although high-resolution satellite images are being use to increase agricultural productivity and sustainable agriculture, these technologies are not sufficient in terms of actuality. In addition, the data of the study area is often out of date or low resolution. Recently, the use of unmanned aerial vehicles has increased considerably. With the decrease in costs and increase in accessibility, it has started to be adopted not only in defense industry but also in construction, advertising, mining, search and rescue. In this study, multi-band images taken from an agricultural area with on unmanned aerial vehicle were analyzed. Data and analysis such as number and area of trees, possible diseases, plant height, high resolution orthophoto map of the agricultural area were created with the help of Pix4D and MATLAB software. In this study, images of 7.35 hectares of agricultural land located at the intersection of Çukurova University and Adana ring road were taken in 5 bands (Blue, Green, Red, Red Edge, Near IR). With the help of Pix4D Mapper, high resolution orthophoto maps and digital surface model were produced with these images (GPS data matching). The generated map can be displayed in ndvi, nir and red, green, blue spectral bands. In addition, on this map, an application written in MATLAB, the number of trees was calculated with low error rate. The aim of this study is to create orthophoto images with high spatial and radiometric resolution with the help of UAV and multispectral camera integration from an agricultural application area in Çukurova University Campus, to analyze this image in terms of plant health and to make tree detection with a software developed. The results obtained from the study area including orange and corn fields are aimed to support the sensitive agriculture studies in our country. The study is a good example for unmanned aerial vehicles to produce more sensitive, low cost and faster solutions in agricultural applications than clasic remote sensing methods. In this way, it is aimed to contribute to the development of innovative methods to reduce costs and increase productivity by developing correct irrigation and fertilization methods.