REMOTE SENSING OF SNOWFALLS. REVIEW
Snow is the most common type of solid precipitation, therefore the development of remote sensing methods for studying the characteristics of snow by solving the inverse problems based on a detailed study of properties of such phenomena is of a considerable interest. In general, the calculating probl...
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doaj-89cb628eb77c45578906d994abb89b522020-11-24T21:39:50ZengAkademperiodyka Радиофизика и электроника1028-821X2415-34002015-09-012033848https://doi.org/10.15407/rej2015.03.038REMOTE SENSING OF SNOWFALLS. REVIEWG. Veselovska0O. Ya. Usikov Institute for Radiophysics and Electronics of the National Academy of Sciences of UkraineSnow is the most common type of solid precipitation, therefore the development of remote sensing methods for studying the characteristics of snow by solving the inverse problems based on a detailed study of properties of such phenomena is of a considerable interest. In general, the calculating problem of reflection characteristics for nonspherical particles of precipitation has a long history, but researches of inverse radar scattering of liquid precipitation are characterized by the most completeness. The review of mechanical and electrical properties of snow was performed and the characteristics of physical and numerical modeling of the radar scattering characteristics for precipitation particles are analyzed. The paper shows the feasibility of studying the radar scattering characteristics of precipitation particles and it the advantages and disadvantages of the modern calculation methods of radar scattering characteristics for dielectric objects were analyzed. Remote measurement of integral characteristics of snowfalls over large areas allows determining the reservation of water for agriculture, as well as components of the hydrological forecasts and providing avalanche safety in mountainous areas.http://re-journal.org.ua/sites/default/files/file_attach/2015-3/5.pdfcrystal of snowradar cross sectionrain intensity |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
G. Veselovska |
spellingShingle |
G. Veselovska REMOTE SENSING OF SNOWFALLS. REVIEW Радиофизика и электроника crystal of snow radar cross section rain intensity |
author_facet |
G. Veselovska |
author_sort |
G. Veselovska |
title |
REMOTE SENSING OF SNOWFALLS. REVIEW |
title_short |
REMOTE SENSING OF SNOWFALLS. REVIEW |
title_full |
REMOTE SENSING OF SNOWFALLS. REVIEW |
title_fullStr |
REMOTE SENSING OF SNOWFALLS. REVIEW |
title_full_unstemmed |
REMOTE SENSING OF SNOWFALLS. REVIEW |
title_sort |
remote sensing of snowfalls. review |
publisher |
Akademperiodyka |
series |
Радиофизика и электроника |
issn |
1028-821X 2415-3400 |
publishDate |
2015-09-01 |
description |
Snow is the most common type of solid precipitation, therefore the development of remote sensing methods for studying the characteristics of snow by solving the inverse problems based on a detailed study of properties of such phenomena is of a considerable interest. In general, the calculating problem of reflection characteristics for nonspherical particles of precipitation has a long history, but researches of inverse radar scattering of liquid precipitation are characterized by the most completeness. The review of mechanical and electrical properties of snow was performed and the characteristics of physical and numerical modeling of the radar scattering characteristics for precipitation particles are analyzed. The paper shows the feasibility of studying the radar scattering characteristics of precipitation particles and it the advantages and disadvantages of the modern calculation methods of radar scattering characteristics for dielectric objects were analyzed. Remote measurement of integral characteristics of snowfalls over large areas allows determining the reservation of water for agriculture, as well as components of the hydrological forecasts and providing avalanche safety in mountainous areas. |
topic |
crystal of snow radar cross section rain intensity |
url |
http://re-journal.org.ua/sites/default/files/file_attach/2015-3/5.pdf |
work_keys_str_mv |
AT gveselovska remotesensingofsnowfallsreview |
_version_ |
1725928920036933632 |