In this paper we propose a simple and efficient method of image classification in UAV monitoring application. Taking into consideration the color distribution two types of texture feature are considered: statistical and fractal characteristics. In the learning phase four different and efficient features were selected: energy, correlation, mean intensity and lacunarity on different color channel (R, G and B). Also, four classes of aerial images were considered (forest, buildings, grassland and flooding zone). The method of comparison, based on sub-images, average and the Minkovski distance, improves the performance of the texture-based classification. A set of 100 aerial images from UAV was tested for establishing the rate of correct classification.