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The paper presents an overview of existing thematic services based on Earth remote sensing data from space and aimed at monitoring and analysis of forest vegetation and dynamics of its changes.

The article presents the results of adaptation and application of two-dimensional hydrodynamic model STREAM_2D to reproduce the characteristics of ice-jam-induced floods in the vicinity of the city of Velikiy Ustyug (the Northern Dvina river basin, Vologda region, Russia). The additional hydraulic resistance due to ice roughness and the decrease in the flow cross-section area due to ice-caused congestion were taken into account for modeling of ice-jam-induced water level variations. The corresponding model parameters were estimated on the basis of numerical experiments and flood modeling for the period from 1980 to 2016, which includes more than 18 significant cases of ice-jamming. Grouping of model parameters by the height of the ice-jam-induced water level rises could be useful for the application of the developed model in the framework of an intelligent information system of river flood monitoring.

The research is aimed at the development and testing of the system for operational river flood forecasting. The system is based on the use of a complex of hydrological and hydrodynamic models, as well as in situ and satellite data integrated processing, and implemented on the basis of a service-oriented architecture. A distinctive feature of the system is the complete automation of the entire simulation cycle - from loading initial data to interpreting results, visualizing and alerting interested parties. The theoretical basis for ensuring the coordinated functioning of all system components is the qualimetry of models and polymodel complexes. The practical implementation is carried out using open codes, free software and GIS platform «RegionView». All the complexity associated with the use of heterogeneous geographically distributed information resources is hidden from the user. This allows the system to be used not only by specialists in GIS, IT or relevant subject area, but also by other users interested in the results of flood monitoring and forecasting - emergency services, local authorities, commercial organizations and citizens. The described technologies and the system of operational flood forecasting were tested in the Russian Federation on the Northern Dvina River, from the city of Velikiy Ustyug to the city of Kotlas in 2014-2019. Given test results prove that the application of such an approach ensures full implementation of the required functionality of operational flood forecasting systems, the fulfilment of the basic requirements for such systems and also indicate the possibility of a widespread use of such systems authorities and emergency services.

This paper presents the research results related to the development of an intelligent system for monitoring and assessing the state of natural systems (PROSTOR), which was tested in the area from the city of Velikiy Ustyug to the city of Kotlas on the Northern Dvina River. It is one of the most vulnerable places in Russia to spring snow-melt and ice-jams induced floods.The proposed automated flood forecasting technology is based on the concept of a multi-model description of complex natural objects implementing a mechanism of the selection and adaptation of parameters of the most adequate model for each specific situation. The computational core of PROSTOR is the two-dimensional hydrodynamic model STREAM_2D and its newer version STREAM_2D_CUDA based on the numerical solution of the shallow water equations with discontinuous bottom. Additional hydraulic resistance due to the ice roughness and decrease in the flow cross-section due to ice-caused congestion were taken into account for modeling the ice-jams water levels. The forecasting capabilities of the system are secured by the prediction of water levels at the gauging stations located upstream from Velikiy Ustyug basing either on neural networks, or by means of linking with the runoff formation model ECOMAG and using prognostic meteorological information.The system was built with the use of a service-oriented architecture, that provides flexible interaction between software modules, implementing hydrodynamic and hydrological models; modules of collecting and processing of heterogeneous data, including data from gauging stations and remote sensing data; control modules, etc. All system components are realized as web services and can be geographically distributed and localized in various organizations, cities and countries. All results of the system implementation, including the results of flooded zones calculations, flow parameters there, as well as satellite images are available via the geoportal.Models parameters were justified on the base of numerical experiments and simulations of the floods of 1980-2016 period, including more than 18 significant cases of ice-jamming. Grouping of model parameters according to the height of the ice-jam induced water levels suggested for the implementation of the hydrodynamic model incorporated into intelligent information system of river floods monitoring. Operational flood forecasting mode of the system was tested during 2017 – 2019 years under support of Russian Science Foundation project № 17-11-01254.

The structure of the Intellectual Information Platform (IIP) and examples of its application for decision-making support in environmental management are considered. The IIP structure is based on a service-oriented architecture. The flexible nature of IIP software allows to integrate a wide range of environmental parameters assessment models and diverse initial data, including earth remote sensing data. Results of case studies for different IIP applications such as water bodies monitoring, forestry management, flood forecasting, etc., showed full-scale implementation of the IIP required functionality.

The paper considers methods and information technologies for full automatization of forest ecosystems sustainability estimation. Analysis of forest ecosystem sustainability is explored as a multi-objective problem with applying a complex of models for calculating partial indicators of sustainability. Earth observation (EO) data is used as an essential component of information support for estimating forest ecosystems sustainability indicators. Methodological framework of automatization consists of complex modelling, application of models qualimetry methods for selecting specific calculation models, and methods for multi-criteria analysis to estimate generalized indicators of sustainability. A software architecture is proposed in order to implement procedures of complex modelling with integrated processing EO and field data.

The paper proposes a method and a multi-model complex for managing computations, which make it possible to increase the efficiency of production processes at existing and prospective industrial enterprises due to the optimal (rational) functioning of their information systems. The features of computational processes and architectures of information systems of modern enterprises based on the concept of Industry 4.0 are considered. A brief description of the software package is given, in which the task of structural-functional synthesis of the structure of an enterprise information system, as well as the task of building an operational schedule for its work, are simultaneously solved in an automated (automatic) mode.

The chapter presents a holistic system that implements an advanced river flood modeling and forecasting approach. This approach extends traditional methods based on separate satellite monitoring or river physical processes modeling, by integration of different technologies such as satellite and in situ data processing, input data clustering and filtering, digital mapping of river valleys relief, data crowdsourcing, hydrodynamic modeling, inundation visualization, and also duly warning of stakeholders.

Design, planning and management of opencast and underground mining require safety control of mining operations. Geodynamic monitoring of mining areas is necessary for operational forecasting and prevention of dangerous deformation processes. The identification of geodynamic active zones and forecasting of geodynamic risks are based on systematic observations of the surface and mining facilities. A promising method of obtaining timely spatial information to solve the problems mentioned is the satellite radar imagery. The integration of radar products and intelligent information systems improves the efficiency and accuracy of data analysis. The paper presents the methods of radar image processing in order to conduct comprehensive monitoring of the Earth’s surface and infrastructure in mining enterprises. For efficient use of thematic processing products the results were placed on the web server in the information-analytical system “RegionView” providing distributed access to spatial data through the web interface and standard protocols.

In this paper the concept of integrated modeling and simulation of the processes of the Complex Technical–Organizational System (CTOS) is presented. Practical directions of the remote sensing for environmental monitoring of the protected area are proposed by the authors. Methodical basis of the integrated modeling and simulation, the process of CTOS operation, and the technology of the remote sensing for environmental monitoring are considered. Results of CTOS remote sensing are shown to adapt models to a changing environment.