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首页> 外文期刊>Stochastic environmental research and risk assessment >A MODIS-based method for detecting large-scale vegetation disturbance due to natural hazards: a case study of Wenchuan earthquake stricken regions in China
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A MODIS-based method for detecting large-scale vegetation disturbance due to natural hazards: a case study of Wenchuan earthquake stricken regions in China

机译：基于MODIS的自然灾害引起的大规模植被扰动检测方法-以中国汶川地震灾区为例

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In the global carbon cycle, terrestrial biomass plays an important role in both as a sink and source. To evaluate biomass variation due to various natural hazards, it is necessary to detect the location, extent and duration of vegetation disturbance at a large spatial scale with an efficient method. This study contributes to develop such a method, and only the moderate resolution imaging spec-troradiometer (MODIS) MOD13Q1 enhanced vegetation index (EVI) products are used to generate a continuous vegetation damage index (CVDI) for detecting severe vegetation disturbance in large areas. To verify the performance of this new index, this study takes the identification of the vegetation damage due to the Wenchuan earthquake in China occurred on 12 May 2008 as a case study. This study calculates the CVDI for the earthquake stricken areas, and delineates the regions with considerable EVI abnormal variation. The study result reveals that those delineated regions with severe vegetation damage are normally consistent with the areas with the landslides caused by the earthquake. Moreover, according to the changes of other vegetation-related MODIS datasets since 12 May 2008, this study discloses that the EVI value in most of the areas, where the vegetation was damaged due to the earthquake, has not reached to the normal value in 2012, which is 4 years after the earthquake. Finally, to validate the vegetation damage areas determined by CVDI method, the high resolution images and field survey information are used. This study confirms that CVDI method can effectively delineate large-scale terrestrial biomass disturbance due to the earthquake and can accurately identify the vegetation recovery process.
机译：在全球碳循环中，陆地生物量作为汇和源都发挥着重要作用。为了评估由于各种自然灾害引起的生物量变化，有必要使用一种有效的方法在较大的空间尺度上检测植被扰动的位置，程度和持续时间。这项研究为开发这种方法做出了贡献，只有中分辨率成像光谱仪（MODIS）MOD13Q1增强植被指数（EVI）产品用于生成连续植被破坏指数（CVDI），以检测大面积的严重植被干扰。为了验证该新指标的性能，本研究以2008年5月12日发生的中国汶川地震造成的植被破坏为例。这项研究计算了地震受灾地区的CVDI，并描绘出EVI异常变化较大的地区。研究结果表明，那些划定的植被严重受损的地区通常与地震造成的滑坡地区一致。此外，根据自2008年5月12日以来与植被有关的其他MODIS数据集的变化，该研究表明，由于地震而植被遭到破坏的大多数地区的EVI值在2012年仍未达到正常值。 ，这是地震发生后的4年。最后，为了验证通过CVDI方法确定的植被破坏区域，使用了高分辨率图像和现场调查信息。这项研究证实，CVDI方法可以有效地描述由于地震引起的大规模陆地生物量扰动，并且可以准确地识别植被恢复过程。

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