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Study on the Space Modeling of Forest Fire of Hunan Province Process

Author: LiuPingBo
Tutor: ZhangGui
School: Central South University of Forestry Science and Technology
Course: Forest Management
Keywords: Forest fires Space model Self-organized criticality Spatial interpolation Spatial clustering Hunan Province,
CLC: S762
Type: Master's thesis
Year: 2010
Downloads: 60
Quote: 0
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Abstract


The forest is a valuable human material wealth is a renewable natural resource. Development and protection of these resources, not only related to the country's economic construction, and also a direct relationship between the ecological environment construction and protection of the region, this is a power in the contemporary, Yam and descendants of big things. Forest fires are a world-wide, cross-border natural disasters, the devastating forest, deep harm caused very serious economic losses. Hunan has 11,302 mu of forest land, accounting for 35.7% of the total area in Hunan. The forest coverage rate of 34.3%, much higher than the national average. The Hunan land area of ??forest land accounted for 57.4%, is one of the major timber producing southern China forest base. Hunan densely populated, summer and fall drought is more severe, the formation of forests more combustible, more vulnerable ecological environment. The impact of global warming, Hunan Province, high temperature, drought, high winds and other weather disasters increased significantly, resulting in forest fire danger rating persistently high, the number of forest fires, the injured area, tolls substantial increase in the number of casualties, currently Hunan forest fire prevention work is facing the most severe situation in the past 70 years, the task is arduous. This paper reviews the research status and development trend of domestic and international forest fire model. Ecology, forest fire science and space modeling theory for guidance, in-depth investigations and studies Socioeconomic, physical geography, forest fire prevention, the status quo. The use of the system characteristics of self-organized criticality, spatial interpolation techniques, spatial clustering technology, mathematical methods, geostatistics, geographic information systems and computer technology, the model of the Hunan forest fires space research and establishment. The main conclusions of the study are: (1) Forest fire frequency - area distribution to meet a good power-law relationship, and this power law relationship with time stability and scale invariance, Hunan Forest fire system has self-organized critical characteristics, the approximate external conditions, they have a similar or the same as the characteristics of self-organized criticality parameters. So you can use a regional forest fire history data to predict the distribution of future fires. The straight from Hunan Province from 2000 to 2004 fire data fitting logF = -1.17 * log A from 3.41,2005 2009 fire data fitting a straight line logF = -1.17 * log A 3.37 (2 ) use spatial interpolation techniques Hunan samples of forest fire data from the point data into surface data study of the space distribution of the forest fire. The Kriging method spherical model model validation results show that: the the Kriging method works best, inverse distance weighting interpolation method than the radial basis function interpolation; inverse distance weighting interpolation method, the weight value of 2 of the best; interpolation results are good in the ring model. The best local interpolation dome disjunctive kriging interpolation method to establish model: 0.53688 * Circular (1.2078) 0.44541 * Nugget. Trend surface model of the best three global interpolation: The modeling results show that: the the 2000-2009 forest fire in Hunan Province frequency in the southeast - northwest, southwest - northeast direction was anti-U-shaped trend. Quadratic trend surface model space for the parabolic model and the long axis of the front-line of Chenzhou - Zhangjiajie, of Changsha - Yongzhou line for the minor axis, forming an oval high value area, reducing to four weeks divergence. (3) the spatial clustering technology reference to the Hunan forest fire space modeling research. Spatial clustering technology can be quantitatively judge woodland fire data between the degree of similarity to the woodland classified overcome the interference of human factors. Spatial clustering modeling results show that the forest fires in Hunan frequency space has a higher concentration, Geary C index (Getis-Ord general G) statistically significant level in more than 5%, the the Moran Ⅰ index statistics significant level in more than 1% (the lower the percentage of the more significant). The gathering results show that the north-central Hunan Province - Midwest first-line in the past 10 years, the perennial forest fire frequency more than 68, and increased with the rise of the total frequency of the province's forest fire; 2002, Midwest, southwest become a forest fire high-frequency region, the average annual forest fire frequency in more than 237 times; 2008, the forest fire peak years, the total frequency number up to 5076, an area of ??forest fires occurred in Shaoyang 1093; followed in 2005, this year reach the highest level since 2000, the incidence of forest fires and forest fire total frequency 3138 times. The characteristics of the large amount of information, the timeliness of the forest fire modeling work, constantly demanding higher the quality of the model. Continues to mature as the work of forest fire prevention, forest fire modeling approach is constantly evolving. The rapid development of computer technology, geographic information technology to provide a strong technical support for the realization of the spatial model of forest fires. Hunan forest fires by a variety of factors such as social, economic and natural environment, forest fire prevention is a long-term, arduous work. Space model of how to combine the Hunan forest fire characteristics, establish realistic, high effectiveness of forest fires, is a the Hunan forest fire's rapid development key.

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CLC: > Agricultural Sciences > Forestry > Forest Protection > Forest fire
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