scholarly journals The model of an information system for monitoring remote sensing data of the Arctic region

2021 ◽  
Vol 678 (1) ◽  
pp. 012043
Author(s):  
Makar Bizyukin ◽  
Gennady Abrahamyan
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Remote Sensing Data ◽  
Arctic Region ◽  
The Arctic ◽  
Sensing Data ◽  
The Arctic Region

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 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.

scholarly journals Patterns of Arctic Tundra Greenness Based on Spatially Downscaled Solar-Induced Fluorescence

2019 ◽  
Vol 11 (12) ◽  
pp. 1460 ◽  
Author(s):  
Dongjie Fu ◽  
Fenzhen Su ◽  
Juan Wang ◽  
Yijie Sui
Keyword(s):  
Satellite Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Gross Primary Production ◽  
Remote Sensing Data ◽  
Arctic Region ◽  
Arctic Tundra ◽  
The Arctic ◽  
Global Inventory ◽  
The Arctic Region

A general greening trend in the Arctic tundra biome has been indicated by satellite remote sensing data over recent decades. However, since 2011, there have been signs of browning trends in many parts of the region. Previous research on tundra greenness across the Arctic region has relied on the satellite-derived normalized difference vegetation index (NDVI). In this research, we initially used spatially downscaled solar-induced fluorescence (SIF) data to analyze the spatiotemporal variation of Arctic tundra greenness (2007–2013). The results derived from the SIF data were also compared with those from two NDVIs (the Global Inventory Modeling and Mapping Studies NDVI3g and MOD13Q1 NDVI), and the eddy-covariance (EC) observed gross primary production (GPP). It was found that most parts of the Arctic tundra below 75° N were browning (–0.0098 mW/m2/sr/nm/year, where sr is steradian and nm is nanometer) using SIF, whereas spatially and temporally heterogeneous trends (greening or browning) were obtained based on the two NDVI products. This research has further demonstrated that SIF data can provide an alternative direct proxy for Arctic tundra greenness.

scholarly journals Data assimilation in sea-ice monitoring

2000 ◽  
Vol 31 ◽  
pp. 327-332 ◽  
Author(s):  
Ronald L. S. Weaver ◽  
Konrad Steffen ◽  
John Heinrichs ◽  
James A. Maslanik ◽  
Gregory M. Flato
Keyword(s):  
Remote Sensing ◽  
Data Assimilation ◽  
Sea Ice ◽  
Global Climate ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Physical Processes ◽  
Error Statistics ◽  
Sensing Data ◽  
Ice Model

AbstractThe detection of small changes in concentration or thickness in the Arctic or Antarctic ice cover is an important topic in the current global-climate-change debate. Change detection using satellite data alone requires rigorous error analysis for their derived ice products, including inter-satellite validation for long time series. All models of physical processes are only approximations, and the best models of complicated physical processes have errors and uncertainties. A promising approach is data assimilation, combining model, in situ data and satellite remote-sensing data. Sea-ice monitoring from satellite, ice-model estimates, and the potential benefit of combining the two are discussed in some detail. In a case-study we demonstrate how the sea-ice backscatter for the Beaufort Sea region was derived using a backscattering model in combination with an ice model. We conclude that, for data assimilation, the first steps include the use of simple models, moving, with success at this level, to progressively more complex models. We also recommend reconfiguring the current remote-sensing data to include precise time tags with each pixel. For example, the current Special Sensor Microwave Imager data might be reissued in a time-tagged orbital (or gridded) format as opposed to the currently available daily averaged gridded data. Finally, error statistics and quality-control information also need to be readily available in a form useful for assimilation. The effectiveness of data-assimilation techniques is directly linked to the availability of data error statistics.

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

2020 ◽  
Vol 19 (1) ◽  
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.

scholarly journals Application of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral imagery to mineral and lithologic mapping in southern West Greenland

2018 ◽  
Vol 8 (2) ◽  
pp. 47
Author(s):  
Enton Bedini
Keyword(s):  
Remote Sensing ◽  
Thermal Emission ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Multispectral Imagery ◽  
Alluvial Deposits ◽  
West Greenland ◽  
Sensing Data ◽  
Arctic Regions ◽  
Lithologic Mapping

Remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used for mineral and lithologic mapping at the Sarfartoq carbonatite complex area in southern West Greenland. The geology of the study area consists of carbonatites, fenites, hydrothermal alteration zones, gneisses, alluvial deposits etc. The Adaptive Coherence Estimator algorithm was used to analyze the remote sensing data. The reference spectra were selected from the imagery. The mapping results show the distribution of carbonatite, hydrothermally altered zones, fenite, and sericite. In addition, lichen and tundra green vegetation were also mapped.  Due to the moderate spatial resolution of ASTER SWIR bands, it was not possible to detect and map the rock units in some parts of the study area. The study shows the possibilities and limitations of the use of the ASTER multispectral imagery for geological studies in the Arctic regions of West Greenland. The paper is the first reported study on the use of ASTER data for mineral and lithologic mapping in the Arctic regions of West Greenland. 

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