Mapping of vegetation cover using Sentinel-2 to estimate forest fire danger

Elena P. Yankovich, Ksenia S. Yankovich, Nikolay V. Baranovskiy, Alexander V. Bazarov, Roman S. Sychev, Nimazhap B. Badmaev

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

2 Цитирования (Scopus)

Аннотация

Vegetation maps play a key role in an estimation of forest fire danger. To estimate forest fire danger, a vegetation type map of Gilbirinsky forestry situated in the Lake Baikal basin was created on basis of both the remote sensing data and field study. A Sentinel-2A satellite image was classified by the maximum likelihood method. Zones with different levels of forest fire danger have been identified: coniferous forests-extremely dangerous level, mixed forests-high level, and deciduous forests-moderate level of forest fire danger. Normalized Difference Water Index has been calculated and moisture content in vegetation has been evaluated.

Язык оригиналаАнглийский
Название основной публикацииRemote Sensing of Clouds and the Atmosphere XXIV
РедакторыAdolfo Comeron, Evgueni I. Kassianov, Klaus Schafer, Richard H. Picard, Konradin Weber, Upendra N. Singh
ИздательSPIE
ISBN (электронное издание)9781510630079
DOI
СостояниеОпубликовано - 2019
СобытиеRemote Sensing of Clouds and the Atmosphere XXIV 2019 - Strasbourg, Франция
Продолжительность: 11 сен 201912 сен 2019

Серия публикаций

НазваниеProceedings of SPIE - The International Society for Optical Engineering
Том11152
ISSN (печатное издание)0277-786X
ISSN (электронное издание)1996-756X

Конференция

КонференцияRemote Sensing of Clouds and the Atmosphere XXIV 2019
СтранаФранция
ГородStrasbourg
Период11.9.1912.9.19

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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