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Updated: May 4, 2026

07:51
Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs
Published on: August 27, 2019
8.6K
[Lightning-caused fire, its affecting factors and prediction: a review]
Ji-Li Zhang1, Wu Bi2, Xiao-Hong Wang2
1Harbin Research Institute of Forestry Machinery, State Forestry Administration, Harbin 150086, China. xtafktj@126.com
Ying Yong Sheng Tai Xue Bao = the Journal of Applied Ecology
|January 15, 2014
Summary
Predicting lightning-caused fires is crucial for mitigating forest fire damage. This study analyzes key factors like cloud-to-ground lightning, fuel, weather, and terrain, reviewing prediction models and methods.
Area of Science:
- Forestry Science
- Atmospheric Science
- Environmental Science
Context:
- Lightning-caused fires are a primary natural fire ignition source, leading to significant ecological and economic losses globally.
- Accurate prediction of these fires is a growing concern for many nations.
- Understanding the interplay of various factors is essential for effective fire management.
Purpose:
- To analyze the primary factors influencing lightning-caused fire formation and development.
- To review mathematical models and methods used in lightning-caused fire prediction research.
- To introduce lightning-caused fire prediction strategies employed in the US and Canada.
Summary:
- This paper examines the roles of cloud-to-ground lightning, fuel characteristics, meteorological conditions, and terrain in lightning-caused fire initiation and spread.
- It reviews established prediction methodologies, including logistic models and K-functions, and discusses international approaches.
- The research identifies current research limitations and proposes future directions for improving lightning-caused fire prediction.
Impact:
- Provides a theoretical foundation and literature review to support lightning-caused fire prediction efforts in China.
- Aims to enhance the understanding of fire dynamics for improved natural fire management strategies.
- Contributes to the scientific knowledge base for mitigating the adverse effects of forest fires.
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