The aim of the paper was to classify data from aerial laser scanning and CIR digital images, which were orientated, connected and aligned by the Agisoft Photoscan software. Then, in order to distinguish the ground a point cloud was generated. This was to create a correct terrain mesh and, in consequence, an orthophotomap. The next stage is to develop a new point cloud using ArcGIS. The land cover from the images was combined with the ground mapped by LiDAR. New heights were calculated relative to the ground surface height 0. The point cloud was converted into a raster form, providing a normalized Digital Surface Model (nDSM). It was the first element of the output composition, which also consisted of the NIR and RED channels, acquired from the cloud point generated in Agisoft. The colour composition obtained in such way was subjected to four object-oriented and pixel-oriented classification methods: I – ISO Cluster, II – Maximum Likelihood, III – Random Trees, IV – Support Vector Machine. Object grouping is possible due to information stored in the display content. This technique is prompted by human ability of image interpretation. It draws attention to more variables, so effects similar to human perception of reality are possible to achieve. The unsupervised method is based on a process of automatic search for image fragments, which allows assigning them to individual categories by a statistical analysis algorithm. In turn, supervised method uses “training datasets”, which are used to “teach” the program assigning individual or grouped pixels to classes [Benz UC et al., 2004]. The area studied for land development was the Lutowiska municipality, in the Podkarpackie Voivodeship, Bieszczady County. As a result of the classification, 11 classes of terrain features were distinguished: class 0 – road infrastructure, class 1 – roads, class 2 – buildings, class 3 – waters, class 4 – meadows, class 5 – arable lands, class 6 – pastures, class 7 – high vegetation, class 8 – medium vegetation, class 9 – low vegetation, class 10 – quarry. The area of research covers an area of about 28 km2. Aerial images were made in 2015. Field vision and photopoint measurement was carried out in May 2018.