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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationRemote Sensing of Clouds and the Atmosphere XXIV
EditorsAdolfo Comeron, Evgueni I. Kassianov, Klaus Schafer, Richard H. Picard, Konradin Weber, Upendra N. Singh
PublisherSPIE
ISBN (Electronic)9781510630079
DOIs
Publication statusPublished - 2019
EventRemote Sensing of Clouds and the Atmosphere XXIV 2019 - Strasbourg, France
Duration: 11 Sep 201912 Sep 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11152
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing of Clouds and the Atmosphere XXIV 2019
CountryFrance
CityStrasbourg
Period11.9.1912.9.19

Keywords

  • Baikal Lake basin
  • Forest Fire Danger
  • NDWI
  • Sentinel-2
  • Supervised Classification
  • Vegetation Mapping

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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