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| 南方林区森林火险精准区划方法 | |
| 引用本文： | 徐爱俊,黄小银,姜广宇,邵建龙.南方林区森林火险精准区划方法[J].浙江林学院学报,2012,29(1):65-71. |
| 作者姓名： | 徐爱俊 黄小银 姜广宇 邵建龙 |
| 作者单位： | 1. 浙江农林大学信息工程学院,浙江临安,311300 2. 浙江农林大学环境与资源学院,浙江临安,311300 3. 浙江省龙泉市林业局,浙江龙泉,323700 |
| 基金项目： | 国家自然科学基金资助项目（30972361）;浙江省自然科学基金资助项目（Y3100352,Y3090346）;浙江省大学生科技创新计划项目（2010R412051） |
| 摘 要： | 基于三维地理信息系统(3D GIS)技术,根据南方集体林区森林火灾的特点,以浙江省临安市为实验区,将森林火灾因子分成社会经济、林学特征、气象特征等三大类11个指标,并赋予相应的权重.在此基础上,构建3个特征向量(社会经济特征向量、林学特征向量、气象特征向量),建立了非线性数学模型——森林火险精准区划模型,并利用最小二乘法等数学方法,对模型进行了求解、优化与验证.结果表明:实验值和理论值的误差均小于0.1.该模型和实验区历史火灾发生情况基本吻合. |
| 关 键 词： | 森林保护学 森林防火 火险区划 精准区划模型 最小二乘法 地理信息系统 |
Precision fire hazard divisions for collective forest in southern China |
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| XU Ai-jun , HUANG Xiao-yin , JIANG Guang-yu , SHAO Jian-long.Precision fire hazard divisions for collective forest in southern China[J].Journal of Zhejiang Forestry College,2012,29(1):65-71. | |
| Authors: | XU Ai-jun HUANG Xiao-yin JIANG Guang-yu SHAO Jian-long |
| Institution: | 1. School of Information Engineering, Zhejiang A ＆ F University, Lin＇an 311300, Zhejiang, China; 2. School of Environmental and Resource Sciences, Zhejiang A ＆ F University, Lin＇an 311300, Zhejiang, China; 3. Forest Enterprise of Longquan City, Longquan 323700, Zhejiang, China) |
| Abstract: | This paper focuses on how to build the model of precision fire hazard divisions in the level of forest forest resources subcompartment.Based on 3D GIS technology and characteristics of forest fires in collective forest of southern China,this study utilized Lin＇an City,Zhejiang Province as the experimental area.Forest fire factors were divided into 11 indexes from the three categories（social and economic factors,forestry characteristics,and meteorological characteristics） and weighted for analysis.Next,three eigenvectors（one for each category） were created to build a nonlinear mathematical model called precision fire hazard divisions for forests.Then,the model was used to optimize and test forest fire hazard divisions with the least squares.Results showed that experimental and theoretical values of error were less than 0.1.Thus,in the experimental area this model and the fire occurrence history matched. |
| Keywords: | forest protection forest fires fire hazard divisions precision classification model least squares geographic informatim system |
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