Joint processing of RS and WWLLN data for forest fire danger estimation: new concept

Baranovskiy, Nikolay V.; Krechetova, Svetlana Yu.; Belikova, Marina; Kocheeva, Nina A.; Yankovich, Elena P.

doi:10.1117/12.2241853

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…The empirical and statistical methods to assess forest fire danger (including thunderstorms) are widely used in recent years [6][7][8]. In addition, deterministic and probabilistic approaches have been developed [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Computing of Coniferous Tree Ignition by the Cloud-to-Ground Lightning Discharge using Joule-Lenz's Law

Baranovskiy

Кузнецов

Nemova

2017

IJECE

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The natural phenomenon of thunderstorm activity is one of many causes of a forest fire. Thunderstorms cause especially intensive fire danger situations within remote areas and highlands. As a rule, a cloud-to-ground lightning discharge is the fire source. The present study is based on the research results of electrical overloads in supply networks. Physical and mathematical formulation and numerical solution for the problem of a coniferous tree (pine) ignited by a cloud-to-ground lightning discharge are presented. The problem is considered in a cylindrical coordinate system in two-dimensional formulation. The features of current passage and heat transfer taking into account the reactive wood localization are investigated. The Joule-Lenz’s law is used to calculate heat production in a tree trunk. Parametric analysis has been conducted and tree trunk ignition conditions have been determined in a typical range for the influencing parameters of negative and positive discharges.

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Section: Introductionmentioning

confidence: 99%

Mathematical Computing of Coniferous Tree Ignition by the Cloud-to-Ground Lightning Discharge using Joule-Lenz's Law

Baranovskiy

Кузнецов

Nemova

2017

IJECE

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Decision Support System Development of Wildland Fire: A Systematic Mapping

Vásquez

Cravero

Castro

et al. 2021

Forests

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Wildland fires have been a rising problem on the worldwide level, generating ecological and economic losses. Specifically, between wildland fire types, uncontrolled fires are critical due to the potential damage to the ecosystem and their effects on the soil, and, in the last decade, different technologies have been applied to fight them. Selecting a specific technology and Decision Support Systems (DSS) is fundamental, since the results and validity of this could drastically oscillate according to the different environmental and geographic factors of the terrain to be studied. Given the above, a systematic mapping was realized, with the purpose of recognizing the most-used DSS and context where they have been applied. One hundred and eighty-three studies were found that used different types of DSS to solve problems of detection, prediction, prevention, monitoring, simulation, administration, and access to routes. The concepts key to the type of solution are related to the use or development of systems or Information and Communication Technologies (ICT) in the computer science area. Although the use of BA and Big Data has increased in recent years, there are still many challenges to face, such as staff training, the friendly environment of DSS, and real-time decision-making.

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Joint processing of RS and WWLLN data for forest fire danger estimation: new concept

Cited by 2 publications

References 24 publications

Mathematical Computing of Coniferous Tree Ignition by the Cloud-to-Ground Lightning Discharge using Joule-Lenz's Law

Mathematical Computing of Coniferous Tree Ignition by the Cloud-to-Ground Lightning Discharge using Joule-Lenz's Law

Decision Support System Development of Wildland Fire: A Systematic Mapping

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