In the current times we are faced with increasing demands concerning the quality and quantity of work and the saving of resources. Because of that workers are increasingly forced to use modern and new technologies which enable them to increase the quality or quantity of work. Forestry can also not avoid this trend. In this thesis we have pointed out the quality and precision of data provided by the methods of remote ground sensing (DPZ) and aerial laser scanning (ALS). We have researched what possible benefits these methods bring and how they can be correctly applied and used in the practical field. We have presented how an illegal structure can be identified with the use of data from the real estate cadaster and aerial laser scanning. We presented it concretely on a modeled example. The area used was covered by ninety structures. Subsequently we focused on an automatic classification of structures on non-building plots and a subsequent evaluation of the correctness of the classification. Another goal of this thesis was a detailed evaluation of the accuracy of identification and classification of the state of individual plots. We have researched what the influence is of an area selection approach that determines the minimum allowable surface of the plot on its correct qualification. Finally we have recommended in what way the quality of the outputs from the real estate cadaster and aerial laser scanning can be practically improved. We discussed how to prevent various mistakes resulting from automatic classification and identification of structures on various types of plots. With these recommendations we have clearly pointed out how large the possibilities are that result from aerial laser scanning data and how we can increase the quality of the outputs and data through our recommendations and advice.