The rapid growth of geographic information technologies in the field of processing and analysis of spatial data has led to a significant increase in the role of geographic information systems in various fields of human activity. However, solving complex problems requires the use of large amounts of spatial data, efficient storage of data on on-board recording media and their transmission via communication channels. This leads to the need to create new effective methods of compression and data transmission of remote sensing of the Earth. The possibility of using fractal functions for image processing, which were transmitted via the satellite radio channel of a spacecraft, is considered. The information obtained by such a system is presented in the form of aerospace images that need to be processed and analyzed in order to obtain information about the objects that are displayed. An algorithm for constructing image encoding–decoding using a class of continuous functions that depend on a finite set of parameters and have fractal properties is investigated. The mathematical model used in fractal image compression is called a system of iterative functions. The encoding process is time consuming because it performs a large number of transformations and mathematical calculations. However, due to this, a high degree of image compression is achieved. This class of functions has an interesting property—knowing the initial sets of numbers, we can easily calculate the value of the function, but when the values of the function are known, it is very difficult to return the initial set of values, because there are a huge number of such combinations. Therefore, in order to de-encode the image, it is necessary to know fractal codes that will help to restore the raster image.

Our paper describes the methodology of an effective system construction based on information systems self-diagnosis using the case of Ukrainian enterprises in metallurgy, energy, and chemical industry. It describes the method of organization and implementation of self-diagnosis, mechanisms of detection, as well as the identification and localization of failed modules. The results formulate the criteria of sufficiency of efficiency of diagnostic information in the absence of restrictions on performance of elementary checks. Moreover, it yields the criterion of sufficiency of diagnostic information in the presence of restrictions on performance of elementary checks.

Monitoring of the forests with the help of remote sensing of the Earth systems is actual on the present stage of people development. Existing systems of research do not allow to use geographic information databases and don't include the spectrum of exploration that are presented in our work. The aim of this article is to develop the method of identification of tree species composition of forests on the basis of geographic information database in the integration with correlation analysis. It will give the possibility to find the most negative things that influence on the condition of forest ecosystems and neutralize them at the first stage of their influence. Satellite images that are received from the satellites Landsat 5 and 8 are used to make the database. Tree species composition of Mozhariv forest during 20 years is analyzed as an example in this article. Classification of tree species composition of forests using space images is made on the basis of Bayes classifier. There is a special geographic information database for further data processing and identification of tree species composition is developed. Forest is analyzed on the number of trees in each species during continuous time measures (in 2000, 2010 and 2020) in this article. Results of the work are presented with the help of graphics. Correlation analysis, which helps to make the analysis of tightness of connections between changes trees in number and different forest criteria, is made to identify tree species composition of forest. Developed method together with well-known methods of monitoring of forests help us to make effective application for analysis of tree species composition of forest changes and to make better existing information systems including different quality demands. Peculiarity of developed information system is in using of the data processing module as a part of geographic information system and implementing correlation analysis with identification of factors that influence each other. It helps to increase quality in management and monitoring of forest resources. Geographic information becomes available for users.

With the development of industry, the issue of environmental safety of countries worldwide has become increasingly acute. Currently, there is a deficiency of information systems capable of effectively and comprehensively informing the public about the state of the environment, analyzing the dynamics of environmental indicators, and assessing regional disparities in terms of environmental safety. The objective of this study is to develop an information system for monitoring the environmental condition of a country's territory based on geoinformation technologies, considering emissions of pollutants. This system is conceived as a multi-regional monitoring system focused on industrial areas. It incorporates a geo-module for user location determination and data representation tailored to the user's location. Additionally, the system regularly updates information on hazardous enterprises and notifies the population in case of emergencies.

This study considers the issue of assessing the time changes in forest plantations and constructing an algorithmic and software system for monitoring these changes. Modern systems that study vegetation changes do not have the necessary functionality and do not cover the range of observations discussed in this paper. Existing research methods are intended only to record changes that occur in forest ecosystems and take into consideration the peculiarities of a certain natural zone, which limits their use. At the same time, it should be understood that the requirements for modern systems should include additional components that could make the system universal and mobile. A comparative analysis of satellite images acquired from remote sensing by the Landsat 8 satellite system has been carried out to determine the areas affected by forest fires. During the classification, spectral analysis was used, and an index of fires was determined to indicate the burned areas. To analyze the changes that occur in forests due to fires, correlation-regression analysis is used. It has been proven that the area of sanitary felling after fires and the area of forest land traversed by fires demonstrated the greatest interconnection. The extrapolation and forecasting were carried out using a regression data model, the effectiveness of which is confirmed by a coefficient of determination of 0.87. The dependences built make it possible to conclude that by 2030 the number of forest fires will increase while the area of burned forests will not decrease. The developed mobile application could be popular among a significant group of users to monitor fire events. The practical result is the introduction of the built system, which makes it possible to quickly monitor forest plantations after fires and assess the areas that were affected.