Satellite Data Processing for Hydrometeorologal Research with the Use of Neural Network Technologies: The Approaches Used at Planeta State Research Center on Space Hydrometeorology.
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| Title: | Satellite Data Processing for Hydrometeorologal Research with the Use of Neural Network Technologies: The Approaches Used at Planeta State Research Center on Space Hydrometeorology. |
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| Authors: | Bloshchinskiy, V. D.1 (AUTHOR) v.bloshchinsky@dvrcpod.ru, Andreev, A. I.1 (AUTHOR), Kramareva, L. S.1 (AUTHOR), Davidenko, A. N.1 (AUTHOR) |
| Source: | Russian Meteorology & Hydrology. Apr2024, Vol. 49 Issue 4, p304-312. 9p. |
| Subject Terms: | *Hydrometeorology, *Electronic data processing, *Research institutes, *Cloudiness, *Infrared equipment, *Snow cover |
| Abstract: | The paper presents an experience of using artificial intelligence techniques, in particular, neural networks to solve relevant problems of hydrometeorology. The results of the investigations at the Planeta State Research Center on Space Hydrometeorology in detecting clouds and snow cover from the Himawari, Electro-L, and Meteor-M satellite data, as well as on classifying cloud types according to the AHI instrument data (Himawari-8) are reported. The findings of the work on retrieving values of total ozone and water vapor according to the infrared sensing devices are demonstrated. The work on detecting the boundaries of the ice cover and river floods from medium- and high-resolution satellite instruments, as well as the technologies for temperature and humidity sensing in the microwave spectrum are considered. The studies have shown that the use of neural network technologies provides the required accuracy of the received hydrometeorological information and high speed of processing incoming data. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 178129903 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Satellite Data Processing for Hydrometeorologal Research with the Use of Neural Network Technologies: The Approaches Used at Planeta State Research Center on Space Hydrometeorology. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bloshchinskiy%2C+V%2E+D%2E%22">Bloshchinskiy, V. D.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> v.bloshchinsky@dvrcpod.ru</i><br /><searchLink fieldCode="AR" term="%22Andreev%2C+A%2E+I%2E%22">Andreev, A. I.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kramareva%2C+L%2E+S%2E%22">Kramareva, L. S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Davidenko%2C+A%2E+N%2E%22">Davidenko, A. N.</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Russian+Meteorology+%26+Hydrology%22">Russian Meteorology & Hydrology</searchLink>. Apr2024, Vol. 49 Issue 4, p304-312. 9p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Hydrometeorology%22">Hydrometeorology</searchLink><br />*<searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br />*<searchLink fieldCode="DE" term="%22Research+institutes%22">Research institutes</searchLink><br />*<searchLink fieldCode="DE" term="%22Cloudiness%22">Cloudiness</searchLink><br />*<searchLink fieldCode="DE" term="%22Infrared+equipment%22">Infrared equipment</searchLink><br />*<searchLink fieldCode="DE" term="%22Snow+cover%22">Snow cover</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The paper presents an experience of using artificial intelligence techniques, in particular, neural networks to solve relevant problems of hydrometeorology. The results of the investigations at the Planeta State Research Center on Space Hydrometeorology in detecting clouds and snow cover from the Himawari, Electro-L, and Meteor-M satellite data, as well as on classifying cloud types according to the AHI instrument data (Himawari-8) are reported. The findings of the work on retrieving values of total ozone and water vapor according to the infrared sensing devices are demonstrated. The work on detecting the boundaries of the ice cover and river floods from medium- and high-resolution satellite instruments, as well as the technologies for temperature and humidity sensing in the microwave spectrum are considered. The studies have shown that the use of neural network technologies provides the required accuracy of the received hydrometeorological information and high speed of processing incoming data. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=178129903 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3103/S1068373924040034 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 304 Subjects: – SubjectFull: Hydrometeorology Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Research institutes Type: general – SubjectFull: Cloudiness Type: general – SubjectFull: Infrared equipment Type: general – SubjectFull: Snow cover Type: general Titles: – TitleFull: Satellite Data Processing for Hydrometeorologal Research with the Use of Neural Network Technologies: The Approaches Used at Planeta State Research Center on Space Hydrometeorology. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bloshchinskiy, V. D. – PersonEntity: Name: NameFull: Andreev, A. I. – PersonEntity: Name: NameFull: Kramareva, L. S. – PersonEntity: Name: NameFull: Davidenko, A. N. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 10683739 Numbering: – Type: volume Value: 49 – Type: issue Value: 4 Titles: – TitleFull: Russian Meteorology & Hydrology Type: main |
| ResultId | 1 |
