scholarly journals The maintaining technologies of the basic products bank based on Earth remote sensing data for the tasks of the Russian Federation digital economy

2020 ◽  
Vol 17 (5) ◽  
pp. 79-90
Author(s):  
A.N. Markov ◽  
◽  
A.N. Vasilyev ◽  
N.A. Olshevskiy ◽  
A.V. Krylov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Russian Federation ◽  
Remote Sensing Data ◽  
Digital Economy ◽  
Earth Remote Sensing ◽  
Sensing Data ◽  
The Russian Federation

scholarly journals Technology for developing a prototype of an information system for monitoring remote sensing data for the arctic region

2021 ◽  
Author(s):  
M. Bizyukin ◽  
◽  
G. V. Abrahamyan
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Russian Federation ◽  
Remote Sensing Data ◽  
Arctic Region ◽  
Use Cases ◽  
The Arctic ◽  
Sensing Data ◽  
The Russian Federation ◽  
The Arctic Region

The work is aimed at developing a model of an information system for the analysis and monitoring of remote sensing data by the example of processing hyper- and multispectral satellite images, which are widely used to analyze the state of static and dynamic objects in the Arctic region of the Russian Federation. For automatic analysis and decryption of Arctic data in the development of the model, methods of high-performance computing, radiometric calibration, filtering and clustering of images, as well as intelligent data processing methods using deep learning convolutional neural networks were used. Object-oriented design and united modeling language notation were used to develop the model. A data-level model, a conceptual model of the structure of system modules, including a resource storage center, a resource and results management center, and a presentation-level interface have been developed. To develop a diagram of the use cases of the information system, the structure of actors, use cases and their interrelations were identified. The logical model of the information system was created based on a class diagram consisting of the Resource and Results Manager Center, Intellectual Information System, Functional Neural Modules packages. The practical significance of the study is due to the fact that the results obtained will allow the development of a prototype of an information system that can be used for effective monitoring of “useful data" of the Arctic region of the Russian Federation, as well as to automate the processes of analysis, updating, storage and processing of data from objects in various areas of the Arctic infrastructure.

scholarly journals Use of multi-temporal Earth remote sensing data for the assessment of agricultural area

2021 ◽  
Vol 285 ◽  
pp. 02024
Author(s):  
Anton A. Melentiev
Keyword(s):  
Remote Sensing ◽  
Russian Federation ◽  
National Economy ◽  
Agricultural Soils ◽  
Remote Sensing Data ◽  
Relevant Information ◽  
Earth Remote Sensing ◽  
Sensing Data ◽  
Management Measures ◽  
Structure State

The article discusses the procedure for identifying unused agricultural soils for their use in economic circulation. The object of the research is the Belgorod district of the Belgorod Region, Russian Federation. Methods of planned soil inventory form the basis for identifying unused agricultural soil, the main purpose of which is to assess the reasons for land retirement from active economic circulation, cultural and technical state of landholdings and to prepare recommendations for commissioning soils into agricultural circulation. Agriculture is a vast and vital branch of the national economy of the Russian Federation It is necessary to introduce modern technologies, state-of-the-art machinery, investments as well as to put into action several land management measures in order to facilitate the development of this sector of the national economy. The data provided by Earth remote sensing gives the necessary and relevant information to the customers regarding structure, state and detailed characteristics of agricultural soils and other assets of agricultural production; the line-up, state and growth of crops. Earth remote sensing data allows to solve more complex analytical tasks, such as forecasting crop yield and calculating the optimal doses of fertilizers. It is convenient to use Earth remote sensing data for monitoring and analyzing soils. With the assistance of that data, based on satellite images, it is possible to identify not only the types of crops, but also the degree of weediness, state of yield, accurate field boundaries, sown area and so on and so forth. The aim of this project is to perform automated decryption in ScanEx Web Geomixer software.

scholarly journals APPLICATION OF REMOTE SENSING DATA TO IMPROVE THE SYSTEM OF REGISTRATION OF LANDS OF THE FOREST FUND OF THE RUSSIAN FEDERATION

2019 ◽  
Vol 4 (2) ◽  
pp. 17-22
Author(s):  
Olga Nikolaeva ◽  
Nadezhda Nikitina
Keyword(s):  
Remote Sensing ◽  
Russian Federation ◽  
Remote Sensing Data ◽  
Forest Plot ◽  
Forest Land ◽  
Sensing Data ◽  
The Russian Federation ◽  
Forest Lands

The article considers the issues of necessity of use of remote sensing data to obtain more information on the forest areas within the limits of forest lands. The causes of the lack of uniform methodology for the registration of forest land are identifield. The scheme of the forest plot registration with the use of remote sensing data is proposed.

scholarly journals Efficient land use based on remote sensing data

2021 ◽  
Vol 3 ◽  
pp. 180-185
Author(s):  
Y. M. Kenzhegaliyev ◽  
◽  
◽  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Data ◽  
Crop Productivity ◽  
The State ◽  
Agricultural Crops ◽  
Earth Remote Sensing ◽  
Spectral Reflectivity ◽  
Sensing Data ◽  
Current Location

The goal -is to explore ways of using Earth remote sensing data for efficient land use. Methods - detailed information on current location of certain types of agricultural crops in the study areas has been summarized, which opens up opportunities for the effective use of cultivated areas. It was revealed that the basis of the principle of the method under consideration is the relationship between the state and structure of vegetation types with its reflective ability. It has been determined that information on the spectral reflective property of the vegetation cover in the future can help replace more laborious methods of laboratory analysis. For classification of farmland, satellite images of medium spatial resolution with a combination of channels in natural colors were selected. Results - a method for identifying agricultural plants by classification according to the maximum likelihood algorithm was considered. The commonly used complexes of geoinformation software products with modules for special image processing allow displaying indicators in the form of raster images. It is shown that the use of Earth remote sensing data is the most relevant solution in the field of crop recognition and makes it possible to simplify the implementation of such types of work as the analysis of the intensity of land use, the assessment of the degree of pollution with weeds and determination of crop productivity. Conclusions - the research results given in the article indicate that timely information on the current location of certain types of agricultural crops in the studied territories significantly simplifies the implementation of the tasks and increases the resource potential of agricultural lands. In turn, the timing of the survey and the state of environment affect the spectral reflectivity of vegetation.

scholarly journals Self-Organizing B2B Enterprise of Distributed Photogrammetric Processing of Terrain Images in ETRIS

2020 ◽  
pp. 155-179
Author(s):  
Oleg Karsaev ◽  
Igor Shuklin ◽  
Sergey Yushchenko
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Remote Sensing Data ◽  
Earth Remote Sensing ◽  
Distributed Information System ◽  
Distributed Information ◽  
Sensing Data ◽  
Geographically Distributed ◽  
Software Information ◽  
Self Organizing

An approach to the dynamic formation (adjustment) of schedules for distributed photogrammetric image processing in a network of ground centers included in the United geographically distributed information system for receiving and processing Earth remote sensing data from space is considered. Having the fullest satisfaction of requirements of consumers to the satellite images of necessary areas, the approach provides the formation of self-organizing B2B enterprises in the specified network providing information, software and hardware resources of the ground-based facilities of various departmental and other accessories for photogrammetric processing of any received images of the area from the the United geographically distributed information system. It is shown, that a search in B2B enterprise nodes and borrowing the required resources will allow ground centers to flexibly scale physical and virtual means of photogrammetric processing of Earth remote sensing data, quickly form their local structural and functional organizations depending on the current properties of the consumer requests flow for receiving Earth remote sensing data in the United geographically distributed information system, characteristics of the flow of terrain survey materials from orbital monitoring tools, and also take into account the visual and measuring properties of images of the area subject to photogrammetric processing. A method for truncating the set of potential performers of the application in accordance with the existing semantic and other restrictions on the composition of the desired set of performers is proposed. Also mechanisms to encourage ground centers to provide idle resources to B2B enterprise nodes are proposed. They are based on the possibility of receiving monetary or other remuneration from a ground center for participating in distributed application servicing. The development of a well-known model of a self-organizing B2B enterprise creates conditions for a more efficient organization of servicing the flow of applications in the United geographically distributed information system by attracting unused software, information and hardware resources of ground centers of various departmental affiliations.

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