Remote sensing provides data that can be used in a variety of projects. One such project is the preparation for sending a manned flight to Mars. Before the departure of the expedition it is very important to carefully select a place of high scientific value and a high security level for the members of the flight. Remote sensing methods allow getting the whole set of necessary data, which will later be used for the flight equipment properly, as well as to adapt the lander design. Currently, robotic probes that send the collected information to Earth are engaged in the collection of the necessary data. There, the data, in turn, can be processed by specialists, as well as provided for the general public for informational purposes only.
The article touches upon the issue of automatic recognition and subsequent processing of data on natural and industrial objects of the world. The obtained data is a result of laser scanning. For data analysis in 2018 a research group, consisting of specialists from Kuban State Technological University, Kuban State University, Kuban State Agrarian University and Aerogeomatics Company, conducted a joint research on the decoding of forest cover based on the data of airborne laser scanning under various landscape conditions. The analysis of existing software was performed through the comparison of various methods of automated decoding and the subsequent decoding of points on the basis of airborne laser scanning. Various research results on this topic, including foreign studies, are analyzed. The authors made the conclusions about the quality and reliability of the information provided by each of the products and the level of development of this software segment as a whole. The alternative development options for this industry based on the use of neural networks are given. Keywordslaser scanning; classification of cloud of laser points; neural networks. I.
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