landslides dataset consists of three objects:
landslides A dataframe of 1535 rows and 3 variables
representing landslide initiation points in the
Reserva Biologica San Francisco (RBSF) area of the tropical Andes
in Southern Ecuador. The variables are:
lslpts landslide initiation point (boolean)
y Coordinates of coordinate reference system
UTM zone 17S (EPSG: 32717)
The landslide inventory was mapped by Stoyan (2000) in the field and by the presence of landslide scars in aerial imagery.
dem Digital elevation model given as a .Rd grid, i.e. a list
consisting of the elements
header (nine properties) and
(grid elevation values in m a.s.l.). The 10 m x 10 m digital elevation model
was triangulated from aerial imagery as described by Jordan et al.
(2005) and provided as a courtesy of Lars Ungerechts (2010).
sf-object representing the outlines of
the natural part of the RBSF study area.
Landslide data provided here are a subset of that used by Muenchow et al. (2012) to predict spatially landslide susceptibility using generalized additive models (GAMs). Specifically, the here provided landslides belong to the "natural" part of the RBSF area. Please refer also to the accompanying vignette for an introductory tutorial on the use of the RSAGA package for terrain analysis, geoprocessing, and model-building using these data.
Please note that loading
landslides overwrites existing objects named
Ungerechts, L. (2010): DEM 10m (triangulated from aerial photo - b/w). Available online:
Jordan, E., Ungerechts, L., Caceres, B. Penafiel, A. and Francou, B. (2005): Estimation by photogrammetry of the glacier recession on the Cotopaxi Volcano (Ecuador) between 1956 and 1997. Hydrological Sciences 50, 949-961.
Muenchow, J., Brenning, A., Richter, R. (2012): Geomorphic process rates of landslides along a humidity gradient in the tropical Andes, Geomorphology 139-140, 271-284. DOI: 10.1016/j.geomorph.2011.10.029.
Stoyan, R. (2000): Aktivitaet, Ursachen und Klassifikation der Rutschungen in San Francisco/Suedecuador. Unpublished diploma thesis, University of Erlangen-Nuremberg, Germany.
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## Not run: library("RSAGA") data(landslides) # Print the DEM header: dem$header # Write the DEM to a SAGA grid: write.sgrd(data = dem, file = "dem", header = dem$header, env = env) # Calculate slope of DEM: rsaga.slope(in.dem = "dem", out.slope = "slope", method = "poly2zevenbergen") # Pick slope values at landslide points, # added to landslides data.frame as variable "slope": landslides <- pick.from.saga.grid(data = landslides, filename = "slope", varname = "slope") ## End(Not run)
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