A field survey–based method to characterise landslide development: a case study at the high bluff of the Danube, south-central Hungary
There are several common tools and practices to record surface displacement, monitor and characterise landslide development. However, is it possible to use only total station monitoring network to gain useful information for mass movement detection characterisation? In our study, we focus on the fie...
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Veröffentlicht in: | Landslides 2019-08, Vol.16 (8), p.1567-1581 |
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Sprache: | eng |
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Zusammenfassung: | There are several common tools and practices to record surface displacement, monitor and characterise landslide development. However, is it possible to use only total station monitoring network to gain useful information for mass movement detection characterisation? In our study, we focus on the field monitoring of the Castle Hill area (south-eastern Transdanubia, Hungary) and provide a methodology to monitor and characterise displacement processes. A 5 × 5 m resolution grid network was set up to cover active and stable parts of the hill and was surveyed 27 times between 2011 and 2016 using a total station device. The total station–based monitoring network was found suitable for the detailed monitoring of the study area at a low cost, with low maintenance, quick data processing capabilities and moderate but manageable precision. Using 3D coordinates, we differentiated the individual parts of the moving block (MB), knowing that the displacements of the MB were several orders of magnitude greater than the precision of the actual surveillance method. The main displacement component (direction) was the vertical subsidence here, which was less than 4 m on the northern MB and exceeded 4 m on the southern MB. The whole MB moved to the east; however, the southern MB moved to the east 1 m shorter distance than the northern MB.
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component movements ranged between 125 and − 271 mm over the entire MB. Small-scale displacements have been detected on the stable background (BA) using normality testing of data, and displacements were identified on the field as shallow hollows (growth cracks). |
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ISSN: | 1612-510X 1612-5118 |
DOI: | 10.1007/s10346-019-01205-8 |