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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Using MODIS NDVI Time Series to Identify Geographic Patterns of Landslides in Vegetated Regions
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Using MODIS NDVI Time Series to Identify Geographic Patterns of Landslides in Vegetated Regions

机译：利用MODIS NDVI时间序列识别植被带滑坡的地理格局

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摘要

The 2008 Wenchuan Earthquake that occurred in a mountainous region of China induced massive landslides and caused numerous casualties and property losses. Analyzing the disturbances on vegetation detected from the abnormal sudden drops of the normalized difference vegetation index (NDVI) within a short period can be used for the purpose of rapid landslide identification. Although much research has confirmed the necessity of high-resolution satellite images in landslides identification, Moderate Resolution Imaging Spectroradiometry (MODIS) products still have their usefulness for high temporal resolution, as investigated by the authors. Using MODIS MOD09Q1 NDVI products at a temporal interval of 8 days during 2008, this letter presents a method that has been developed to identify landslide distribution and evolution patterns. First, to find the optimal threshold, the MODIS NDVI time series are analyzed in a training area by an iteration searching procedure. Second, the chosen threshold is used in a larger validation area. To examine the effectiveness of the proposed method, the results are compared to interpreted landslides using SPOT5 images with a spatial resolution of 2.5 m acquired before and after the main shock. An overall 75% accuracy is achieved, and better consistency is observed for landslides extending over one MODIS pixel. The proposed method has also been applied to the Wenchuan earthquake affected areas with seismic intensity IX and greater, and the similar spatial pattern of landslides distribution is obtained when compared with results by using high-resolution images and field investigation. This technique can be applied practically for rapid landslide assessment at a relatively large region after a major earthquake or other severe disturbance events.
机译：2008年发生在中国山区的汶川地震引发了巨大的山体滑坡，造成大量人员伤亡和财产损失。分析在短时间内从归一化植被指数（NDVI）的异常突然下降中检测到的植被扰动可用于快速识别滑坡。尽管许多研究已经证实了在滑坡识别中使用高分辨率卫星图像的必要性，但正如作者所研究的那样，中分辨率成像光谱法（MODIS）产品仍具有其对高时间分辨率的有用性。在2008年以8天的时间间隔使用MODIS MOD09Q1 NDVI产品的情况下，这封信提出了一种已开发出的方法，用于识别滑坡的分布和演化模式。首先，为了找到最佳阈值，通过迭代搜索过程在训练区域中分析了MODIS NDVI时间序列。其次，所选阈值用于更大的验证区域。为了检验所提方法的有效性，将结果与使用SPOT5图像的解释性滑坡进行了比较，该图像具有在主震之前和之后获取的2.5 m空间分辨率。总体上达到了75％的精度，并且在一个MODIS像素上扩展的滑坡具有更好的一致性。所提出的方法也已经应用于地震烈度为IX或更大的汶川地震灾区，并且与高分辨率图像和野外调查的结果相比，获得了相似的滑坡分布空间格局。在发生大地震或其他严重扰动事件后，该技术可实际用于相对较大区域的快速滑坡评估。

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