Time-of-failure prediction of the Achoma landslide, Peru, from high frequency Planetscope satellites
- 1. Université Grenoble Alpes
- 2. INGEMMET
- 3. Edu
Description
Introduction
This repository contains the data used for the study of the slope instability of Achoma, Peru, described in Lacroix et al. (submitted). Specifically, the repository contains a time series of horizontal ground displacements, obtained from high frequency PlanetScope satellite between 2017 and 2020. It also contains two Digital Elevation Models, one from before the Achoma failure obtained with Pléaides stero images, and the other from just after the Achoma failure obtained with drone imagery.
The data and methods used for the elaboration of this data repository are described in detail in Lacroix et al. (submitted). In this repository we also provide a short summary and overview of the data and methods used.
Data
A total of 79 PlanetScope scenes were used to produce the time series of horizontal horizontal ground displacements maps. Table 1 provides an overview of these data.
Table1: Data used for the creation of this repository
|
Application |
Platforms |
Acquisition dates |
|
Pre-failure DEM |
Pléiades
|
2017/05/13 |
|
Post-failure DEM |
Drone |
2020/06/19 |
|
Horizontal ground displacement |
PlanetScope |
79 scenes from 2017/11/27 to 2020/06/17 |
Methods
The horizontal ground displacement maps, both along the NS and the EW directions (file names NSxxxxxxxx.tif and Ewxxxxxxxx.tif, where xxxxxxxx is the date in the format yyyymmdd) were created using the offset tracking methodology described in Bontemps et al. (2018), consisting of: (1) correlation of all the pairs of images using Mic-Mac (Rupnik et al., 2017), (2) masking the low correlation coefficient values (CC<0.7), (3) mosaicking correction, similar to stripe corrections (Bontemps et al., 2018), that we obtained by subtracting the median value of the stacked profile in the along-stripe direction, taking into account only stable areas, (4) least square inversion of the redundant system per pixel, weighted by the time separation between pairs (Bontemps et al., 2018), (5) correction of illumination effects (Lacroix et al., 2019), based on the 2 years of data between November 2017 and December 2019.
The pre-failure DEM was computed from Ames Stereo Pipeline (Shean et al. 2016) and the methodology developed in (Lacroix, 2016) applied to the Pléiades stereo images (file name DEM_20170513_shifted_vertical2.tif ).
The post-failure DEM was processed using the Structure from Motion-Multi View Stereo (SfM-MVS) methodology with the Agisoft Metashape Professional 1.5.5 software applied on 1824 pictures taken from the drone (file name Achoma_DEM_2020.06.20_UTM19S_50cm.tif ).
Acknowledgements
P.L. acknowledge the support from the French Space Agency (CNES) through the TOSCA, PNTS, and ISIS programs.
Dataset attribution
This dataset is licensed under a Creative Commons CC BY 4.0 International License.
Dataset Citation
Lacroix, P., Huanca, J., Angel, L., Taipe, E.: Data Repository: Time-of-failure prediction of the Achoma landslide, Peru, from high frequency Planetscope satellites. Dataset distributed on Zenodo: 10.5281/zenodo.7866962
Files
Achoma_DEM_2020.06.20_UTM19S_50cm.tif
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Additional details
References
- Bontemps, N., Lacroix, P., & Doin, M.-P. (2018). Inversion of deformation fields time-series from optical images, and application to the long term kinemat- ics of slow-moving landslides in peru. Remote Sensing of Environment, 210 , 144–158.
- Rupnik, E., Daakir, M., & Deseilligny, M. P. (2017). Micmac–a free, open-source solution for photogrammetry. Open Geospatial Data, Software and Standards, 2(1), 1–9.
- Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C., & Morin, P. (2016). An automated, open-source pipeline for mass production of digital elevation models (dems) from very-high-resolution commercial stereo satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 116 , 101–117.
- Lacroix, P. (2016). Landslides triggered by the gorkha earthquake in the langtang valley, volumes and initiation processes. Earth, Planets and Space, 68 (1), 46.
- Lacroix, P., Araujo, G., Hollingsworth, J., & Taipe, E. (2019). Self-entrainment mo- tion of a slow-moving landslide inferred from landsat-8 time series. Journal of Geophysical Research: Earth Surface, 124 (5), 1201–1216.