Prediction and Influence Factors Analysis of Forest Fire Risk Degree——A Case Study of Daxing'anling Area
Volume 5, Issue 6, November 2017, Pages: 450-456
Received: Nov. 16, 2017;
Published: Nov. 21, 2017
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Li Jing, College of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, China
Yu Qian, College of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, China
Cui Tiejun, College of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, China
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Analyze the risk of forest fire and its influencing factors is of great significance, which can provide scientific basis for forecasting and controlling forest fires, so as to reduce economic losses and casualties. Based on vegetation index data and meteorological data from May 13 to 22, 2017, the forest risk rating was calculated using the evaluation criteria of forest fire hazard in Daxing'anling Area, and then the influencing factors of fire were analyzed. The results show that the reason for the spring fire in Daxing'anling Area is that the spring temperature is gradually increasing, but the precipitation does not increase synchronously, and thus resulting in low air humidity and dryness. Moreover, in spring and summer alternating date, there are usually strong atmospheric activity and high wind speed, which lead the forest fire risk increasing. In this weather conditions, the forest area can easily lead to fire, and the spread of the fire is also difficult to control. However, vegetation coverage increase could reduce the risk of fire. According to this algorithm, it is possible to predict the fire risk level in the forest area so as to determine the high probability of fire occurrence area, which could provides a reference for planning fire prevention measures and reasonable flight routes of UAVs for forest administrator.
Daxing'anling, Vegetation Coverage, Meteorological Factor, Forest Fire Risk Forecast
To cite this article
Prediction and Influence Factors Analysis of Forest Fire Risk Degree——A Case Study of Daxing'anling Area, Science Discovery.
Vol. 5, No. 6,
2017, pp. 450-456.
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