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 language | English |
|---|---|
| Pages (from-to) | 3112-3120 |
| Number of pages | 9 |
| Journal | International Journal of Electrical and Computer Engineering |
| Volume | 6 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2016 |
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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 journal › Article
}
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
AN - SCOPUS:85012031587
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 -