Precursory Motion and Time‐Of‐Failure Prediction of the Achoma Landslide, Peru, From High Frequency PlanetScope Satellites

Abstract

Landslide time‐of‐failure prediction is crucial in natural hazards, often requiring precise measurements from in situ instruments. This instrumentation is not always possible, and remote‐sensing techniques have been questioned for detecting precursors and predicting landslides. Here, based on high frequency acquisitions of the PlanetScope satellite constellation, we study the kinematics of a large landslide located in Peru that failed in June 2020. We show that the landslide underwent a progressive acceleration in the 3 months before its failure, reaching at most 8 m of total displacement. The high frequency of satellite revisit allows us to apply the popular Fukuzono method for landslide time‐of‐failure prediction, with sufficient confidence for faster moving areas of the landslide. These results open new opportunities for landslide precursors detection from space, but also show the probable seldom applicability of the optical satellites for landslide time‐of‐failure prediction.

Exploring the Behaviors of Initiated Progressive Failure and Slow‐Moving Landslides in Los Angeles Using Satellite InSAR and Pixel Offset Tracking

“…However, there is significant uncertainty in this prediction due to a low signal-to-noise ratio in the InSAR data and limited number of pixels available for analysis. While our results are encouraging, predicting the failure time from satellite remote sensing data needs more validation worldwide (e.g., Intrieri et al, 2019;Lacroix et al, 2023). Nonetheless, we emphasize that for ground deformation sites where no historical movement has occurred, progressive failure is a significant concern that requires close attention.…”

“…Empirical and semi-empirical methods have been used to forecast ground failure time based on its pre-failure velocity and/or acceleration (e.g., Fukuzono, 1985;Lei et al, 2023;Saito, 1969;Voight, 1989). In particular, the inverse velocity method has been widely applied, which shows that in certain cases the inverse velocity decreases linearly toward zero and can be used to forecast ground failure time (Intrieri et al, 2019;Lacroix et al, 2023). Petley et al (2005) analyzed experiments on a clayey slope to investigate the relationship between velocity and the growth of a landslide shear surface.…”

“…On the other hand, some landslides experience rapid acceleration and catastrophic failure, reaching velocities even higher than a few m/s (Hendron & Patton, 1985;Schuster et al, 2002;Stark et al, 2017). It has been observed that these catastrophic landslide events are sometimes preceded by slow creeping movements (Lacroix et al, 2023;Stark et al, 2017;Voight, 1978). Therefore, it is important to examine which types of slope movement can develop into catastrophic failure and to further explore the associated triggering conditions.…”

“…We compare the record of landslide motion with local rainfall conditions to understand how year-to-year changes in seasonal rainfall impact landslide behaviors. We then examine differences in behavior between RHE and the five slow-moving landslides and test the commonly used inverse velocity method (Fukuzono, 1985;Lacroix et al, 2023) to determine if the rapid motion RHE could have been predicted in advance.…”