Quantifying sediment mass redistribution from joint time-lapse gravimetry and photogrammetry surveys
Artikel i vetenskaplig tidskrift, 2020

The accurate quantification of sediment mass redistribution is central to the study of surface processes, yet it remains a challenging task. Here we test a new combination of terrestrial gravity and drone photogrammetry methods to quantify sediment mass redistribution over a 1 km2 area. Gravity and photogrammetry are complementary methods. Indeed, gravity changes are sensitive to mass changes and to their location. Thus, by using photogrammetry data to constrain this location, the sediment mass can be properly estimated from the gravity data. We carried out three joint gravimetry–photogrammetry surveys, once a year in 2015, 2016 and 2017, over a 1 km^2 area in southern Taiwan, featuring both a wide meander of the Laonong River and a slow landslide. We first removed the gravity changes from non-sediment effects, such as tides, groundwater, surface displacements and air pressure variations. Then, we inverted the density of the sediment with an attempt to distinguish the density of the landslide from the density of the river sediments. We eventually estimate an average loss of 3.7 ± 0.4 × 10^9 kg of sediment from 2015 to 2017 mostly due to the slow landslide. Although the gravity devices used in this study are expensive and need week-long surveys, new instrumentation currently being developed will enable dense and continuous measurements at lower cost, making the method that has been developed and tested in this study well-suited for the estimation of erosion, sediment transfer and deposition in landscapes.


Maxime Mouyen

Chalmers, Rymd-, geo- och miljövetenskap, Onsala rymdobservatorium

Philippe Steer

Université de Rennes 1

Kuo-Jen Chang

National Taiwan University of Science and Technology

Nicolas Le Moigne

Université de Montpellier

Cheinway Hwang

National Chiao Tung University

Wen-Chi Hsieh

Industrial Technology Research Institute of Taiwan

Louise Jeandet

Geosciences Rennes

Laurent Longuevergne

Geosciences Rennes

Ching-Chung Cheng

National Chiao Tung University

Jean-Paul Boy

Université de Strasbourg

Frederic Masson

Université de Strasbourg

Earth Surface Dynamics

2196-6311 (ISSN) 2196-632X (eISSN)

Vol. 8 2 555-577





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