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Mapping forest fire risk zones with spatial data and principal component analysis

机译:利用空间数据和主成分分析绘制森林火灾危险区

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By integrating forest inventory data with remotely sensed data, new data layers for factors that affect forest fire potentials were generated for Baihe Forestry Bureau in Jilin Province of China. The principle component analysis was used to sort out the relationships between forest fire potentials and environmental factors. The classifications of these factors were performed with GIS, generating three maps: a fuel-based fire risk map, a topography-based fire risk map, and an anthropogenic-factor fire risk map. These three maps were then synthesized to generate the final fire risk map. The linear regression method was used to analyze the relationship between an area-weighted value of forest fire risks and the frequency of historical forest fires at each forest farm. The results showed that the most important factor contributing to forest fire ignition was topography, followed by anthropogenic factors.
机译:通过将森林清查数据与遥感数据集成,为中国吉林省白河林业局生成了影响森林火灾隐患因素的新数据层。用主成分分析法对森林火灾潜力与环境因素之间的关系进行分类。使用GIS对这些因素进行分类,生成了三张地图:基于燃料的火灾风险图,基于地形的火灾风险图和人为因素火灾风险图。然后将这三个图合成以生成最终的火灾风险图。使用线性回归方法来分析森林火灾风险的面积加权值与每个林场的历史森林火灾发生频率之间的关系。结果表明,导致森林火灾着火的最重要因素是地形,其次是人为因素。

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