Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies

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

1 Citation (Scopus)

Abstract

Timiryazevskiy forestry of Tomsk region (Siberia, Russia) is a study area elaborated in current research. Forest fire danger assessment is based on unique technology using probabilistic criterion, statistical data on forest fires, meteorological conditions, forest sites classification and remote sensing data. MODIS products are used for estimating some meteorological conditions and current forest fire situation. Geonformation technologies are used for geospatial analysis of forest fire danger situation on controlled forested territories. GIS-engine provides opportunities to construct electronic maps with different levels of forest fire probability and support raster layer for satellite remote sensing data on current forest fires. Web-interface is used for data loading on specific web-site and for forest fire danger data representation via World Wide Web. Special web-forms provide interface for choosing of relevant input data in order to process the forest fire danger data and assess the forest fire probability.

Original languageEnglish
Title of host publicationFourth International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016
PublisherSPIE
Volume9688
ISBN (Electronic)9781628419238
DOIs
Publication statusPublished - 2016
Event4th International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016 - Paphos, Cyprus
Duration: 4 Apr 20168 Apr 2016

Conference

Conference4th International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016
CountryCyprus
CityPaphos
Period4.4.168.4.16

Fingerprint

WebGIS
forest fires
Forest Fire
sunlight
Geographic information systems
hazards
Fires
World Wide Web
remote sensing
Remote sensing
Satellite Remote Sensing
Siberia
Forestry
websites
MODIS
MODIS (radiometry)
Russian Federation
Remote Sensing
engines
Websites

Keywords

  • Assessment
  • Danger
  • Forest fire
  • Remote sensing
  • Sunlight
  • Web-GIS

ASJC Scopus subject areas

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

Cite this

Baranovskiy, N. V., Sherstnyov, V. S., Yankovich, E. P., Engel, M. V., & Belov, V. V. (2016). Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies. In Fourth International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016 (Vol. 9688). [968823] SPIE. https://doi.org/10.1117/12.2240378

Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies. / Baranovskiy, Nikolay V.; Sherstnyov, Vladislav S.; Yankovich, Elena P.; Engel, Marina V.; Belov, Vladimir V.

Fourth International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016. Vol. 9688 SPIE, 2016. 968823.

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

Baranovskiy, NV, Sherstnyov, VS, Yankovich, EP, Engel, MV & Belov, VV 2016, Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies. in Fourth International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016. vol. 9688, 968823, SPIE, 4th International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016, Paphos, Cyprus, 4.4.16. https://doi.org/10.1117/12.2240378
Baranovskiy NV, Sherstnyov VS, Yankovich EP, Engel MV, Belov VV. Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies. In Fourth International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016. Vol. 9688. SPIE. 2016. 968823 https://doi.org/10.1117/12.2240378
Baranovskiy, Nikolay V. ; Sherstnyov, Vladislav S. ; Yankovich, Elena P. ; Engel, Marina V. ; Belov, Vladimir V. / Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies. Fourth International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016. Vol. 9688 SPIE, 2016.
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