Lightning fire daily occurrence probability predicting method based on space grids

A technology of occurrence probability and spatial grid, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as inability to use climate change scenario data analysis, and inability to forecast lightning strikes and fires

Inactive Publication Date: 2014-06-25
INST OF FOREST ECOLOGY ENVIRONMENT & PROTECTION CHINESE ACAD OF FORESTRY
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Problems solved by technology

[0003] The forecast of lightning strike fire is an important content of forest fire forecast. The existing lightning strike fire forecast relies on the lightning monitoring network, which i...

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  • Lightning fire daily occurrence probability predicting method based on space grids
  • Lightning fire daily occurrence probability predicting method based on space grids
  • Lightning fire daily occurrence probability predicting method based on space grids

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Embodiment Construction

[0052] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and through specific implementation methods.

[0053] combine figure 1 and figure 2, taking the Greater Khingan Mountains (including the Greater Khingan Mountains in Heilongjiang and most of the Greater Khingan Mountains in Inner Mongolia) as an example to model and simulate the probability of lightning strike fire day occurrence.

[0054] Step 1 101. Determine the factors affecting lightning fire and collect relevant data, wherein the test area is divided into uniform grids, each grid unit is regarded as an independent space, and the calculated lightning fire occurrence probability is each grid unit The probability of lightning strike fire occurrence.

[0055] (1) Collect lightning fire data from 1972 to 2006 in Heilongjiang Province and the Greater Khingan Mountains of Inner Mongolia Autonomous Region, including the date of occurrence of li...

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Abstract

The invention discloses a method for predicting daily occurrence probability of lightning fire. The method includes: building a data file, and taking each grid point and all fire points in a testing area as sampling points; performing multi-collinearity diagnose through data; selecting factors evidently influencing fire occurrence through Logistic Forward Wald analysis; building a daily occurrence probability model of the lightning fire through a Logistic model so as to analyze daily occurrence probability of the lightning fire, determining a lightning fire ignition threshold through a secondary judging theory, and calculating precision so as to perform precise analysis; on the basis of GIS, substituting day value data into the model for calculation so as to complete forecast of the daily occurrence probability of the lightning fire, and the like. The method has the advantages that the problem that the existing lightning fire predicting models rely on a lightning monitoring network is solved, wide application is achieved, the method can be used for calculating the daily occurrence probability of the lightning fire and analyzing future lightning fire occurrence trend, and the existing lightening fire pre-warning models are supplemented effectively.

Description

technical field [0001] The patent of the present invention relates to a method for predicting the occurrence probability of a lightning strike and fire day, in particular to a method for predicting the occurrence probability of a lightning strike and fire day based on a spatial grid. Background technique [0002] Lightning is considered to be one of the most important natural causes of vegetation fires. Thunderstorms and lightning are very frequent all over the world. The countries with the most forest fires caused by lightning strikes are mainly the United States, Canada, Russia and Australia. The United States, Canada and other countries have more serious lightning fires. Lightning strike fires in our country are also quite serious in a few areas, mainly in Daxing'an Mountains in Heilongjiang, Humeng in Inner Mongolia and Altai Mountains in Xinjiang, among which the Daxing'an Mountains and Humeng forest areas are particularly prominent. Daxing'an Mountains are almost cause...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 王明玉舒立福田晓瑞赵凤君
Owner INST OF FOREST ECOLOGY ENVIRONMENT & PROTECTION CHINESE ACAD OF FORESTRY
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