Description Format Details Source Examples
The landslide dataset consists of landslide initiation points in the Reserva Biológica San Francisco (RBSF) area of the tropical Andes in Ecuador. The landslide inventory was mapped by Stoyan (2000) in the field and by the presence of landslide scars in aerial imagery. The 10 m x 10 m digital elevation model (DEM) was triangulated from aerial imagery as described by Jordan et al. (2005) and provided as a courtesy of Lars Ungerechts (2010).
A data frame of 1535 rows and 3 variables:
x
: the x coordinate of the sample point
y
: the y coordinate of the sample point
lslpts
: this column informs if the corresponding point is a
landslide (TRUE
) or not (FALSE
).
A digital elevation model as a .Rd grid dem
$header
list of 8 DEM header properties
$data
grid elevation values (m ASL)
Loading this dataset also loads the object dem
. Existing objects named
dem
may be overwritten.
Landslide data provided here are a subset of that used by Muenchow et al. (2012) to predict spatially landslide susceptibility using generalized additive models (GAMs). Specifically, the here provided landslides belong to the "natural" part of the RBSF area. Please refer also to the accompanying vignette for an introductory tutorial on the use of the RSAGA package for terrain analysis, geoprocessing, and model-building using these data.
DEM:
Ungerechts, L. (2010): DEM 10m (triangulated from aerial photo - b/w). Available online:
http://www.tropicalmountainforest.org/data_pre.do?citid=901
Jordan, E., Ungerechts, L., Caceres, B. Penafiel, A. and Francou, B. (2005): Estimation by photogrammetry of the glacier recession on the Cotopaxi Volcano (Ecuador) between 1956 and 1997. Hydrological Sciences, 50, 949-961
Landslide Data:
Muenchow, J., Brenning, A., Richter, R. (2012): Geomorphic process rates of landslides along a humidity gradient in the tropical Andes, Geomorphology, 139-140, 271-284
Stoyan, R. (2000): Aktivitat, Ursachen und Klassifikation der Rutschungen in San Francisco/Südecuador. Unpublished Diploma Thesis, University of Erlangen-Nuremberg, Germany.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## Not run:
library("RSAGA")
data(landslides)
# Print the DEM header:
dem$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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