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dc.contributor.author Trifonov Grigory
dc.contributor.author Zhizhin Mikhail
dc.contributor.author Melnikov Dmitry
dc.date.accessioned 2019-09-02T12:49:12Z
dc.date.available 2019-09-02T12:49:12Z
dc.date.issued 2016
dc.identifier http://repo.kscnet.ru/2852/
dc.identifier http://repo.kscnet.ru/2852/1/EGU2016-5409-1.pdf
dc.identifier http://meetingorganizer.copernicus.org/EGU2016/EGU2016-5409-1.pdf
dc.identifier.citation Trifonov Grigory, Zhizhin Mikhail, Melnikov Dmitry (2016) Nightfire method to track volcanic eruptions from multispectral satellite images // EGU General Assembly Conference Abstracts, 17–22 April 2016, Vienna. pp. 5409.
dc.identifier.uri https://repository.geologyscience.ru/handle/123456789/5698
dc.description.abstract This work presents the first results of an application of the Nightfire hotspot algorithm towards volcano activity detection. Nightfire algorithm have been developed to play along with a Suomi-NPP polar satellite launched in 2011, which has a new generation multispectral VIIRS thermal sensor on board, to detect gas flares related to the upstream and downstream production of oil and natural gas. Simultaneously using of nighttime data in SWIR, MWIR, and LWIR sensor bands the algorithm is able to estimate the hotspot temperature, size and radiant heat. Four years of non-filtered observations have been accumulated in a spatio-temporal detection database, which currently totals 125 GB in size. The first part of this work presents results of retrospective cross-match of the detection database with the publicly available observed eruptions databases. The second part discusses how an approximate 3D shape of a lava lake could be modeled based on the apparent source size and satellite zenith angle. The third part presents the results of fusion Landsat-8 and Himawari-8 satellites data with the VIIRS Nightfire for several active volcanoes.
dc.language.iso en
dc.subject 47.49.27 Дистанционное зондирование
dc.subject Вулканы Курило-Камчатского региона
dc.title Nightfire method to track volcanic eruptions from multispectral satellite images
dc.type Конференционный материал


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