README.md

lumpR

Landscape Unit Mapping Program for R

DESCRIPTION

This project deals with an R-package called "lumpR". The package provides functions for a semi-automated approach of the delineation and description of landscape units and partition into terrain components. It can be used for the pre-processing of semi-distributed large-scale hydrological and erosion models using catena-representation (WASA-SED, CATFLOW). It is closely connected to and uses functionalities of GRASS GIS. Additional pre-processing tools beyond the scope of the original LUMP algorithm are included.

INSTALLATION

install.packages("devtools") 
library(devtools)
Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS=TRUE) #tell git_install() to ignore warnings. Otherwise, it gets stuck at each warning
install_github("tPilz/lumpR")

The main branch relies on GRASS7. The migration of the packaga to GRASS8 is underway, but not fully tested: [https://github.com/tpilz/lumpR/tree/grass8]

MORE INFORMATION

Have a look at our wiki for more detailed information: >LINK<

FEEDBACK and BUGS

Feel free to comment via github issues: >LINK<

LICENSE

lumpR is distributed under the GNU General Public License version 3 or later. The license is available in the file GPL-3 of lumpR's source directory or online: >LINK<

NOTE

This package was also known as LUMP and has been renamed by Jan 9th 2017 to distinguish it from the LUMP algorithm published by Francke et al. (2008).

REFERENCES

A paper describing lumpR along with an example study was published in GMD:

Pilz, T., Francke, T., and Bronstert, A.: 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, 2017.

See also the accompanying github repository: https://github.com/tpilz/lumpr_paper

For the original LUMP algorithm see:

Francke, T., Güntner, A., Mamede, G., Müller, E. N., and Bronstert, A.: Automated catena-based discretization of landscapes for the derivation of hydrological modelling units, Int. J. Geogr. Inf. Sci., 22, 111-132, doi:10.1080/13658810701300873, 2008.



tpilz/LUMP documentation built on Aug. 5, 2023, 1:31 a.m.