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Application of Fracture Induced Electromagnetic Radiation (FEMR) technique to detect landslide-prone slip planes

机译:裂缝诱导电磁辐射(FEMR)技术检测滑坡 - 易发滑坡的应用

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摘要

Landslides are one of the many catastrophic events which result in massive destruction and loss of lives across the globe. Hence, an appropriate forecasting technique is essential in order to predict such potential weak slip planes which may eventually lead to landslides. Here, we present a study where Fracture Induced Electromagnetic Radiation (FEMR) technique has been used to identify such regions of potential "activity" in a study area around IISER Bhopal Hill, India, stretched along a length of approximately 1 km. The hill is majorly composed of basaltic rocks belonging to the Deccan traps which have been heavily weathered and have resulted in the formation of unconsolidated soil cover. In numerous locations, it has been observed that natural gullies have formed as a result of the breakage of masses from weak slip planes. In this study, we have taken linear measurements along four different profiles along and across the hill using a portable measuring device ANGEL-M. Anomalously high amplitudes of FEMR values are obtained in the regions which consist of weak slip planes which can be considered to be potential zones of future landslides. The results were further verified by calculating the factor of safety for a few locations along the profiles where anomalies in the FEMR data were compared. Consequently, predicting areas prone to natural calamities such as landslides has always been a priority in terms of current research. Hence, we have made an active endeavor to propose a new technique in order to identify landslide-prone areas by detecting the adjoining weak slip planes.
机译:Landslides是众多灾难性事件之一,导致全球生命的巨大破坏和丧失。因此,适当的预测技术是必不可少的,以预测这种潜在的弱滑坡,最终可能导致山体滑坡。在这里,我们提出了一项研究,其中骨折诱导的电磁辐射(FEMR)技术已被用于识别印度艾塞博巴尔山周围的研究区域的潜在“活动”区域,沿着约1公里的长度延伸。山丘主要由属于Deccan Traps的玄武岩岩石组成,这些陷阱受到严重风化并且导致未覆盖的土壤覆盖物形成。在许多位置,已经观察到天然沟渠作为来自弱滑坡的质量破裂而形成的。在这项研究中,我们使用便携式测量装置Angel-M沿着山坡沿着四个不同的剖面进行线性测量。在由弱滑坡组成的区域中获得了异常高幅度,该区域可以被认为是未来滑坡的潜在区域。通过计算沿着分析件的少数位置的安全因子来进一步验证结果,其中比较了分析数据中的异常。因此,预测易于自然灾害的地区,例如Landslides始终是当前研究方面的优先事项。因此,我们已经积极努力提出一种新技术,以通过检测相邻的弱滑坡来识别滑坡易发的区域。

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