WWLLN data cluster analysis methods for lightning-caused forest fires monitoring

Nikolay Baranovskiy, Svetlana Krechetova, Marina Belikova, Anton Perelygin

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Storm activity is the main reason for forest fires to occur in remote forested territories. The current article presents the results for cluster analysis of WWLLN data on lightning discharges. It provides the description for clusterization algorithms of lightning discharges over the controlled territory. Research area is Timiryazevskiy forestry of the Tomsk region (Siberia, Russia). We analyzed the applicability of cluster analysis results for monitoring of the forest fire danger caused by storm activity. As a result of the conducted research, we established that the following characteristics of storm activity can be included in deterministic-probabilistic criterion to assess the forest fire danger. The article gives the recommendations how to create new generation information-computer and geoinformation systems for monitoring of the forest fire danger caused by storm activity in the controlled forested territory.

Original languageEnglish
Pages (from-to)3112-3120
Number of pages9
JournalInternational Journal of Electrical and Computer Engineering
Volume6
Issue number6
DOIs
Publication statusPublished - 2016

Fingerprint

Cluster analysis
Lightning
Fires
Monitoring
Forestry

Keywords

  • Cluster analysis
  • Forest fire
  • Lightning monitoring
  • Siberia
  • WWLLN data

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this

WWLLN data cluster analysis methods for lightning-caused forest fires monitoring. / Baranovskiy, Nikolay; Krechetova, Svetlana; Belikova, Marina; Perelygin, Anton.

In: International Journal of Electrical and Computer Engineering, Vol. 6, No. 6, 2016, p. 3112-3120.

Research output: Contribution to journalArticle

Baranovskiy, Nikolay ; Krechetova, Svetlana ; Belikova, Marina ; Perelygin, Anton. / WWLLN data cluster analysis methods for lightning-caused forest fires monitoring. In: International Journal of Electrical and Computer Engineering. 2016 ; Vol. 6, No. 6. pp. 3112-3120.
@article{f4930887792945e5b45d77dfc88fd1ad,
title = "WWLLN data cluster analysis methods for lightning-caused forest fires monitoring",
abstract = "Storm activity is the main reason for forest fires to occur in remote forested territories. The current article presents the results for cluster analysis of WWLLN data on lightning discharges. It provides the description for clusterization algorithms of lightning discharges over the controlled territory. Research area is Timiryazevskiy forestry of the Tomsk region (Siberia, Russia). We analyzed the applicability of cluster analysis results for monitoring of the forest fire danger caused by storm activity. As a result of the conducted research, we established that the following characteristics of storm activity can be included in deterministic-probabilistic criterion to assess the forest fire danger. The article gives the recommendations how to create new generation information-computer and geoinformation systems for monitoring of the forest fire danger caused by storm activity in the controlled forested territory.",
keywords = "Cluster analysis, Forest fire, Lightning monitoring, Siberia, WWLLN data",
author = "Nikolay Baranovskiy and Svetlana Krechetova and Marina Belikova and Anton Perelygin",
year = "2016",
doi = "10.11591/ijece.v6i6.12780",
language = "English",
volume = "6",
pages = "3112--3120",
journal = "International Journal of Electrical and Computer Engineering",
issn = "2088-8708",
publisher = "Institute of Advanced Engineering and Science (IAES)",
number = "6",

}

TY - JOUR

T1 - WWLLN data cluster analysis methods for lightning-caused forest fires monitoring

AU - Baranovskiy, Nikolay

AU - Krechetova, Svetlana

AU - Belikova, Marina

AU - Perelygin, Anton

PY - 2016

Y1 - 2016

N2 - Storm activity is the main reason for forest fires to occur in remote forested territories. The current article presents the results for cluster analysis of WWLLN data on lightning discharges. It provides the description for clusterization algorithms of lightning discharges over the controlled territory. Research area is Timiryazevskiy forestry of the Tomsk region (Siberia, Russia). We analyzed the applicability of cluster analysis results for monitoring of the forest fire danger caused by storm activity. As a result of the conducted research, we established that the following characteristics of storm activity can be included in deterministic-probabilistic criterion to assess the forest fire danger. The article gives the recommendations how to create new generation information-computer and geoinformation systems for monitoring of the forest fire danger caused by storm activity in the controlled forested territory.

AB - Storm activity is the main reason for forest fires to occur in remote forested territories. The current article presents the results for cluster analysis of WWLLN data on lightning discharges. It provides the description for clusterization algorithms of lightning discharges over the controlled territory. Research area is Timiryazevskiy forestry of the Tomsk region (Siberia, Russia). We analyzed the applicability of cluster analysis results for monitoring of the forest fire danger caused by storm activity. As a result of the conducted research, we established that the following characteristics of storm activity can be included in deterministic-probabilistic criterion to assess the forest fire danger. The article gives the recommendations how to create new generation information-computer and geoinformation systems for monitoring of the forest fire danger caused by storm activity in the controlled forested territory.

KW - Cluster analysis

KW - Forest fire

KW - Lightning monitoring

KW - Siberia

KW - WWLLN data

UR - http://www.scopus.com/inward/record.url?scp=85012031587&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85012031587&partnerID=8YFLogxK

U2 - 10.11591/ijece.v6i6.12780

DO - 10.11591/ijece.v6i6.12780

M3 - Article

VL - 6

SP - 3112

EP - 3120

JO - International Journal of Electrical and Computer Engineering

JF - International Journal of Electrical and Computer Engineering

SN - 2088-8708

IS - 6

ER -