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A comparison of forest fire indices for predicting fire risk in contrasting climates in China.

机译:比较森林火灾指数以预测中国气候对比下的火灾风险。

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The relationships between fire danger indices and fire risk have been extensively studied in many regions of the world. This work uses partial effect analysis in semiparametric logistic regression models to assess the nonlinear relationships among location, day, altitude, fire danger indices, normalized difference vegetation index (NDVI), and fire ignition from 1996 to 2008 in four different climatic regions in China. The four regions are North China (NR), Northeast China (NE), Southeast China (SE), and Southwest China (SW). The three main results are as follows: First, different fire danger indices are selected as significant variables dependent on the region. The inter-regional difference could be partially explained by difference in local weather and vegetation conditions. Second, spatial location exerts highly significant effects in all four regions. NDVI values are selected as explained variable for NR, NE, and SE on fire ignitions. On a daily scale, altitude influences fire ignition for NR, SE, and SW. Third, the robustness of the probability models used in NE, SE, and SW is better than that in NR on a daily scale. The semiparametric logistic regression model used in this study is useful for assessing the ability of fire danger indices to estimate probabilities of fire ignition on a daily scale. This study encourages further research on assessing the predictive ability of fire danger indices developed at other temporal and spatial scales in China.
机译:火灾危险指数与火灾危险之间的关系已在世界许多地区进行了广泛的研究。这项工作在半参数对数回归模型中使用局部效应分析来评估1996年至2008年中国四个不同气候区域的位置,日,海拔,火灾危险指数,归一化植被指数(NDVI)和火灾点火之间的非线性关系。这四个地区分别是华北(NR),东北(NE),东南(SE)和西南(SW)。三个主要结果如下:首先,根据区域不同,选择不同的火灾危险指数作为重要变量。区域间的差异可以部分由当地天气和植被状况的差异来解释。其次,空间位置在所有四个区域都发挥着非常重要的作用。选择NDVI值作为火警时NR,NE和SE的解释变量。在日常尺度上,海拔高度会影响NR,SE和SW的着火。第三,在日尺度上,NE,SE和SW中使用的概率模型的鲁棒性优于NR中的概率模型。本研究中使用的半参数对数回归模型可用于评估火灾危险指数的能力,以估计日尺度上的着火概率。这项研究鼓励对评估中国其他时空尺度上制定的火灾危险指数的预测能力进行进一步研究。

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