prof_class | R Documentation |
Classifies mean catenas derived from area2catena
into Landscape
Units and Terrain Components.
prof_class(catena_file = NULL, catena_head_file = NULL,
svc_column = "svc", dir_out = "./", luoutfile = "lu.dat",
tcoutfile = "tc.dat", lucontainstcoutfile = "lucontainstc.dat",
tccontainssvcoutfile = "r_tc_contains_svc.dat",
terraincomponentsoutfile = "terraincomponents.dat",
recl_lu = "reclass_lu.txt", saved_clusters = NULL, seed = 1312,
resolution = NULL, classify_type = " ", max_com_length = NULL,
com_length = NULL, make_plots = F, eha_subset = NULL,
eha_blacklist = NULL, overwrite = F, silent = F,
plot_silhouette = T)
catena_file |
Name of file containing mean catena information derived from
|
catena_head_file |
Name of file containing meta-information for classification
derived from |
svc_column |
Field name in |
dir_out |
Character string specifying output directory (will be created; nothing will be overwritten). |
luoutfile |
Output: Name of file containing the average properties of Landscape Units. |
tcoutfile |
Output: Name of file containing the average properties of Terrain Components. |
lucontainstcoutfile |
Output: Name of file containing information wich LU contains which TCs. |
tccontainssvcoutfile |
Output: Name of file containing information wich TC contains which SVCs. |
terraincomponentsoutfile |
Output: Name of file containing general properties of TCs. |
recl_lu |
Output: Name of GRASS reclassification file: EHA -> LU. |
saved_clusters |
Output: Name of R file that can be used to store LU characteristics for later re-use; set to NULL to omit output (default). |
seed |
Integer specifying seed for random processes in cluster analysis. |
resolution |
Integer specifying resolution of profiles/spacing of samples.
Typically the resolution of your GRASS location used for |
classify_type |
Type of classification: |
max_com_length |
Integer defining the maximum common length of profiles, i.e. the maximum number of support points representing each catena during the classification procedure. Too large values consume more memory and computational effort. |
com_length |
Integer giving common length of profiles, i.e. the number of support points representing each catena during the classification procedure. Too large values consume more memory and computational effort. Overwrites max_com_length. |
make_plots |
logical; visualisation of classification results written into
sub-directory plots_prof_class. WARNING: Consumes a lot of processing
time and memory. Default: |
eha_subset |
NULL or integer vector with subset of EHA ids that shall be processed (for debugging and testing). |
eha_blacklist |
NULL or integer vector with subset of EHA ids that will be excluded (use this for manual exclusion of strange profiles). |
overwrite |
|
silent |
|
plot_silhouette |
|
This function first resamples the catenas derived from area2catena
to a common length (com_length
or the median number of support points
of all catenas but not more than max_com_length
). Second, k-means clustering
is employed to group the catenas into representative Landscape Units
according to parameters given via catena_head_file
taking into account
hillslope length, shape, and supplemental properties. Third, each group is further
partitioned into a given number of Terrain Components in a way that the
variance within each TC is minimized considering slope gradient and supplemental
information.
Function returns nothing. Output files are written into output directory as specified in arguments.
Function uses output of area2catena
. However, no GRASS
session needs to be started in this case.
After applying recl_lu
, the resulting landscape units raster map in your GRASS
location might show gaps depending on the number of generated landscape units
as each landscape unit refers to the representative EHA. The gaps can be filled
with GRASS function r.grow
.
In case of long computation times or memory issues, try make_plots = FALSE
and specify an RData file as catena_file
(already in area2catena
).
Tobias Pilz tpilz@uni-potsdam.de, Till Francke francke@uni-potsdam.de
Source code based on SHELL
and MATLAB
scripts of Till Francke.
lumpR package introduction with literature study and sensitivity analysis:
Pilz, T.; Francke, T.; Bronstert, A. (2017): lumpR 2.0.0: an R package facilitating
landscape discretisation for hillslope-based hydrological models.
Geosci. Model Dev., 10, 3001-3023, doi: 10.5194/gmd-10-3001-2017
Theory of LUMP:
Francke, T.; Guentner, A.; Mamede, G.; Mueller, E. N. and Bronstert, A (2008):
Automated catena-based discretization of landscapes for the derivation of
hydrological modelling units. International Journal of Geographical
Information Science, Informa UK Limited, 22(2), 111-132, DOI: 10.1080/13658810701300873
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