title: [Lightning-caused fire, its affecting factors and prediction: a review].
abstract: Lightning-caused fire is the most important natural fire source. Its induced forest fire brings enormous losses to human beings and ecological environment. Many countries have paid great attention to the prediction of lightning-caused fire. From the viewpoint of the main factors affecting the formation of lightning-caused fire, this paper emphatically analyzed the effects and action mechanisms of cloud-to-ground lightning, fuel, meteorology, and terrain on the formation and development process of lightning-caused fire, and, on the basis of this, summarized and reviewed the logistic model, K-function, and other mathematical methods widely used in prediction research of lightning-caused fire. The prediction methods and processes of lightning-caused fire in America and Canada were also introduced. The insufficiencies and their possible solutions for the present researches as well as the directions of further studies were proposed, aimed to provide necessary theoretical basis and literature reference for the prediction of lightning-caused fire in China.
authors.affiliation: Harbin Research Institute of Forestry Machinery, State Forestry Administration, Harbin 150086, China. xtafktj@126.com
authors.forename: Ji-Li
authors.initials: JL
authors.lastname: Zhang
authors.affiliation: Harbin Research Institute of Forestry Machinery, State Forestry Administration, Harbin 150086, China.
authors.forename: Wu
authors.initials: W
authors.lastname: Bi
authors.affiliation: Harbin Research Institute of Forestry Machinery, State Forestry Administration, Harbin 150086, China.
authors.forename: Xiao-Hong
authors.initials: XH
authors.lastname: Wang
authors.affiliation: Harbin Research Institute of Forestry Machinery, State Forestry Administration, Harbin 150086, China.
authors.forename: Zi-Bo
authors.initials: ZB
authors.lastname: Wang
authors.affiliation: Harbin Research Institute of Forestry Machinery, State Forestry Administration, Harbin 150086, China.
authors.forename: Di-Fei
authors.initials: DF
authors.lastname: Li
mesh_terms: D017753:Ecosystem; D004784:Environmental Monitoring; D005390:Fires / Q000517:prevention & control; D005544:Forecasting; D008030:Lightning; D012044:Regression Analysis; D014197:Trees