A study on the use of UAV images to improve the separation accuracy of agricultural land areas

•The accurate classified information on a variety of agricultural crops plays a significant role in product.•The combination of UAV and Landsat8 images affects well to separate pistachio cultivars.•The combination of UAV and Landsat8 images affects well to separate covered with weeds. Classifying satellite images with medium spatial resolution such as Landsat, it is usually difficult to distinguish between plant species, and it is impossible to determine the area covered with weeds. In this study, a Landsat 8 image along with UAV images utilized to separate pistachio cultivars and separate weed from trees. To use the high spatial resolution of UAV images, image fusion was carried out through the high-pass filter, wavelet, principal component transformation, BROVEY, IHS, and Gram Schmidt methods. ERGAS, RMSE, and correlation criteria were applied to assess their accuracy. The results represented that the wavelet method with R2, RMSE, and ERGAS 0.91, 12.22 cm, and 2.05 respectively had the highest accuracy in combining these images. Then, images obtained by this method were chosen with a spatial resolution of 20 cm for classification. Different classification methods including unsupervised method, maximum likelihood, minimum distance, fuzzy artmap, perceptron, and tree methods were evaluated. Moreover, six soil classes, Ahmad Aghaei, Akbari, Kalleh Ghoochi, Fandoghi, and a mixing class of Kalleh Ghoochi and Fandoghi were applied, and also three classes of soil, pistachio tree and weeds were extracted from the trees. The results demonstrated that the fuzzy artmap method had the highest accuracy in separating weeds from trees, differentiating various pistachio cultivars with Landsat image and also classification with combined image and had 0.87, 0.79, and 0.87 kappa coefficients respectively. The comparison between pistachio cultivars through Landsat image and the combined image showed that the validation accuracy obtained from harvest has raised by 17% because of the combination of images. The results of this study indicated that the combination of UAV and Landsat 8 images affects well to separate pistachio cultivars and determine the area covered with weeds.