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Fisher?¢????Shannon and detrended fluctuation analysis of MODIS normalized difference vegetation index (NDVI) time series of fire-affected and fire-unaffected pixels

机译:Fisher火灾和未火灾像素的MODIS归一化植被指数(NDVI)时间序列的Fisher香农和去趋势波动分析

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ABSTRACT MODIS-NDVI data from 2002 to 2014 were analysed to evaluate the effect of fire on vegetation in a test site located in Daxing'anling region (Inner Mongolia and Heilongjiang Province). Fire-affected and fire-unaffected areas were processed using two statistical approaches: detrended fluctuation analysis (DFA) and Fisher?¢????Shannon (FS) method. The DFA allows the detection of scaling behaviour in nonstationary signals, whereas the FS method permits to identify the organization/order structure in complex signals. Our findings show that the results obtained by jointly using the two methods are consistent, enabling the characterization and discrimination between the fire-affected and fire-unaffected areas. In particular, among the investigated indices, the mean value of Fisher information measure (FIM) represents the most significant in discriminating between burned and unburned sites; its mean value for burned sites is about 2.5 that is significantly larger than that obtained for unburned sites (?¢????1.3). FIM is also characterized by the larger effectiveness in discriminating the two classes of sites on the base of its receiver operating characteristic based performance. The scaling exponents estimated by means of the DFA of the fire-affected pixels are averagely higher than those of the fire-unaffected ones, which, furthermore, are characterized by lower organization and higher disorder degree. Both of the two methods would contribute to identify the impact of fires on vegetation.
机译:分析了2002年至2014年的抽象MODIS-NDVI数据,以评估火灾对位于大兴安岭地区(内蒙古和黑龙江省)的测试地点的植被的影响。受火灾影响和未受火灾影响的区域使用两种统计方法进行处理:去趋势波动分析(DFA)和费舍尔·香农(FS)方法。 DFA允许检测非平稳信号中的缩放行为,而FS方法允许识别复杂信号中的组织/顺序结构。我们的发现表明,联合使用这两种方法所获得的结果是一致的,从而能够对受火灾地区和未受火灾地区进行表征和区分。特别是,在所调查的指标中,Fisher信息量度(FIM)的平均值在区分烧毁地点和未烧毁地点方面最为显着;其烧成部位的平均值约为2.5,大大高于未烧成部位的平均值(1.3)。 FIM的特征还在于,在基于接收器工作特性的性能基础上区分两类站点的有效性更高。借助火灾影响像素的DFA估计的缩放指数平均要高于不受到火灾影响的像素的缩放指数,而且其特征还在于较低的组织性和较高的无序度。两种方法都将有助于确定火灾对植被的影响。

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