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Data Collection and Processing for Measurement of Time-Variable Gravity Erosion in the Laboratory Study

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Abstract

Researchers face great difficulties that few measurable data of gravity erosion on the Loess Plateau are found due to a lack in observation techniques. A problem common to all of the existing methods is that the data were observed after the failure events, and the gravity erosion was not separated from other forms of erosion. This study presents a novel experimental technique and a reliable data processing method that quantitatively measures the time-variable gravity erosion on the steep loess slope in the laboratory test. A structure with laser based gauge and the Topography Meter was designed and fabricated to monitor the dynamic variation of the steep slope topography under rainfall simulation. As the slope landform deforms over time, the process will be recorded in the video, and then imported into the computer to acquire a snapshot image at particular time instance. Given depth in ArcGIS, the 3D geometric shape of the target surface can be computed accurately. All erosion data in every rainfall event, including the amount of each failure mass, the total amount of soil loss, the total amount of hydraulic erosion, etc., could be calculated according to the videos caught by the Topography Meter. It is recommended to make 3D surface together with R2V and ArcGIS, although ArcGIS is sufficient for 3D surface modelling, because contour tracing in R2V is implemented on the undistorted original image, and R2V is also in much smaller size and easy to operate.

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Acknowledgements

This study is supported by the National Natural Science Foundation of China (51079016; 51179021).

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Correspondence to Xiang-Zhou Xu .

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© 2014 Springer International Publishing Switzerland

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Xu, XZ., Zhan, S., Yan, Q., Zhu, MD. (2014). Data Collection and Processing for Measurement of Time-Variable Gravity Erosion in the Laboratory Study. In: Sassa, K., Canuti, P., Yin, Y. (eds) Landslide Science for a Safer Geoenvironment. Springer, Cham. https://doi.org/10.1007/978-3-319-05050-8_24

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