Extracting knowledge from aerial photos based on the method of automated processing

摘要

Remote sensing of the Earth (RSE) is one of the main objective sources of information about the earth's surface. With the development of unmanned aerial vehicles (UAVs), it became possible to take aerial photos with high spatial resolution, which can more accurately identify objects. But due to the fact that the mass use of UAVs for remote sensing of the Earth has become relatively recent, there are no ready-made solutions for automated processing of UAV images. The purpose of the study is to increase the reliability of interpretation of UAV images by developing a method of automated processing based on conceptual modeling. Analysis of methods for thematic interpretation of UAV images showed that none of them provides sufficient segmentation quality without additional adjustment to the subject area. It was found that a combination of methods will improve the result of interpretation. When developing the method of automated processing of UAV images and its software implementation, the method of conceptual modeling of subject problems was used, which ensures the adequacy of syntactic representations (including various images), allows you to control the logic of solving problems and reduces the number of errors at the stage of its software implementation. Using the error matrix and the formula for calculating the Kappa Cohen index, the reliability of thematic interpretation of images of forest areas was assessed. 59 (52.2%) of the 113 trees shown in the picture were correctly identified by the standard watershed method, and 80 (70.8%) - by the developed method. Thus, the developed method made it possible to improve the identification of forest objects in UAV images by 18.6%. In the future, the development of this method can be carried out to determine the characteristics of the identified trees: age, species, height, timber stock.