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摘要

引用本文:

DOI:

10.11834/jrs.20208330

收稿日期:

2018-08-10

修改日期:

2019-02-20

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植被异常特征的遥感判识对潜在滑坡演化的研究——以四川叠溪新磨村滑坡为例
郭忻怡, 郭擎, 冯钟葵
中国科学院遥感与数字地球研究所
摘要:

滑坡监测是预测滑坡地质灾害发生的有效手段。但是,有些山体高位滑坡因其地势高而陡峭、植被覆盖茂密、隐蔽性强,使得GPS技术、InSAR技术以及部分地面监测手段难以开展,这些问题已经成为目前滑坡监测的重要阻碍。光学遥感技术具有非接触、大范围、周期观测和数据存档多的优势,可以在一定程度上弥补上述监测方式的不足,对防灾减灾工作具有重要意义。同时,滑坡蠕变会引起岩体、土壤、水分等环境条件的改变,进而使得滑坡前上覆植被生长状况出现异常,在野外地质调查过程中,也发现了这种异常的存在。本文以这种植被异常为依据,利用高分辨率光学遥感影像,对滑坡发生前坡体上覆植被异常特征进行遥感判识,建立起潜在滑坡阶段遥感影像上的植被异常与滑坡蠕变的关系,分析潜在滑坡的演化过程,借助这种新的滑坡间接监测手段,为滑坡预测研究做准备。以植被覆盖度较高的新磨村山体高位滑坡为例,首先,根据各类资料的综合推断,将新磨村滑坡区域分为上部滑坡隐患区、中部潜在影响区和下部人类活动区3部分;其次,计算各分区的植被覆盖度,并生成上部滑坡隐患区的缓冲区;最后,利用缓冲区和植被覆盖度分析遥感影像上的植被异常与滑坡蠕变的关系,并根据滑后遥感影像和实地考察情况进行验证。滑坡前连续3年的同期高分辨率遥感影像处理结果显示:在上部滑坡隐患区,受滑坡蠕变的影响,滑坡的主要物源区和变形体上方细长局部崩滑区的植被覆盖度呈现明显的下降趋势;随着距裸地边缘空间距离的增大,植被受滑坡蠕变的影响变小,植被生长状况逐渐变好;随着滑坡发生时间的临近,植被受滑坡蠕变的影响变大,植被生长状况变差。在中部潜在影响区,随滑坡发生时间的临近,植被受滑坡蠕变的影响变大,泉眼及冲沟周边的植被生长状况变差。在下部人类活动区,植被变化没有明显的规律性。这表明,上部滑坡隐患区和中部潜在影响区的植被异常与滑坡蠕变存在明显的时空相关性,体现了潜在滑坡阶段植被异常与滑坡蠕变的内在联系,反映了潜在滑坡的演化过程,可以为进一步预测滑坡的发生提供依据。

Prediction of landslide evolution based on remote sensing identification of vegetation anomalies: A case study of the Xinmocun landslide in Diexi Town, Sichuan Province
Abstract:

Objective Landslides is of great perniciousness in mountainous area of China. In recent years, catastrophic high position landslides often occur after Wenchuan earthquake. Some are located in the mountains which have high terrain, steep terrain and dense vegetation coverage. The Xinmocun landslide is one of the typical cases, which occurred at Diexi Town, Maoxian County, Sichuan Province on June 24, 2017. Because of the characteristics of high position and high concealment, this kind of landslide is difficult to be detected by GPS, InSAR and other traditional investigation methods. It is suggested that some technologies should be promoted and applied to detect and prevent such high concealed landslides at high position. The optical remote sensing technology, owning a special capability with large-range, non-contact, periodic coverage and abundant data, has great potentiality in making up for the investigation weakness of the above methods, which is of great significance to disaster prevention and mitigation. The creep of landslide causes changes in environmental conditions, such as loosening of rock mass, change of soil nutrient, uneven distribution of water and so on. The changes in environmental conditions cause the changes of vegetation growth. In situ investigation, the anomaly of vegetation growth before landslide is observed. Therefore, based on the vegetation anomaly, this paper establishes a new indirect landslide monitoring method to prepare for the study of landslide prediction. This method identifies the vegetation anomaly on the landslide body by high-resolution optical remote sensing images, establishes the relationship between the creep of landslide and the vegetation anomaly, and analyzes the evolution process of the landslide creep at the stage of potential landslides.

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