Multifractal behavior of wild-land and forest fire time series in Brazil

雩风三日

Multifractal behavior of wild-land and forest fire time series in Brazil
巴西野外和森林火灾时间序列的多重分形行为

        We examine statistical properties of a daily hot pixel time series recorded in Brazil during the period 1998–2006, using Multifractal Detrended Fluctuation Analysis (MF-DFA). We find that generalized scaling exponent h(q) is a decreasing function of q, indicating multifractal behavior of hot pixel dynamics.Wealso calculate multifractal spectra f (α) and use fourth-degree polynomial regression to estimate complexity parameters that describe the degree of multifractality of the underlying process. After July 2002, when a significant increase of the number of hot pixel observations is recorded, the complexity of the series
is reduced (manifested by the reduction of width of the f (α) spectrum), while small fluctuations increase their dominance over large scale fluctuations (manifested by the increase of skew parameter r). These results should be taken into account when devising ecological and climatic models for Brazil, that contemplate the phenomena of wild-land and forest fires.
      使用多重分形去趋势波动分析(MF-DFA)，我们检验了1998年至2006年期间记录在巴西的每日热像素时间序列的统计特性。我们发现广义标度指数h(q)是q的递减函数，表明热像元动力学的多重分形行为。我们还计算了多重分形谱f (α)，并利用四次多项式回归估计了描述潜在过程多重分形程度的复杂参数。2002年7月后,当数量的显著增加热像素的观测记录,系列的复杂性降低(通过减少f(α)谱)的宽度,而小波动增加他们统治的大规模波动(由斜参数r)的增加体现。这些结果设计时应考虑生态和气候模型对巴西,考虑荒地和森林火灾的现象。

Keywords:Forest fires；Hotspots；Power law；Multifractal detrended fluctuation analysis
关键词:森林火灾；热点；幂律；多重分形去趋势波动分析