Modelling Pathways and Movement Potential Within a Landscape
Provides functionality to calculate cost surfaces based on slope (e.g. Herzog, 2010; Llobera and Sluckin, 2007 <doi:10.1016/j.jtbi.2007.07.020>; Par<c3><ad>s Roche, 2002; Tobler, 1993), traversing slope (Bell and Lock, 2000), and landscape features (Llobera, 2000) to be used when modelling pathways and movement potential within a landscape (e.g. Llobera, 2015; Verhagen, 2013; White and Barber, 2012 <doi:10.1016/j.jas.2012.04.017>).
leastcostpath - version 1.2.1
The R library leastcostpath provides the functionality to calculate Least Cost Paths, which are often, but not exclusively, used in archaeological research. This library can be used to apply multiple cost functions when approximating the difficulty of moving across a landscape, as well as incorporating traversal across slope. Furthermore, attraction/repulsion of landscape features can be incorporated within the Least Cost Path calculation.
This library also provides the functionality to calculate movement potential within a landscape through the implementation of From-Everywhere-to-Everywhere (FETE) (White and Barber, 2012), Cumulative Cost Paths (Verhagen, 2013), and Least Cost Path calculation within specified distance bands (Llobera, 2015).
Lastly, the library provides functionality to validate the accuracy of computed Least Cost Paths relative to another path.
This package is built on classes and functions provided in the R package gdistance (Van Etten, 2017).
#install.packages("devtools") library(devtools) install_github("josephlewis/leastcostpath") library(leastcostpath)
Creation of Cost Surfaces
library(leastcostpath) r <- raster::raster(system.file('external/maungawhau.grd', package = 'gdistance')) slope_cs <- create_slope_cs(r, cost_function = 'tobler') traverse_cs <- create_traversal_cs(r) final_cost_cs <- slope_cs * traverse_cs
Least Cost Path computation
loc1 = cbind(2667670, 6479000) loc1 = sp::SpatialPoints(loc1) loc2 = cbind(2667800, 6479400) loc2 = sp::SpatialPoints(loc2) lcps <- create_lcp(cost_surface = final_cost_cs, origin = loc1, destination = loc2, directional = FALSE) plot(raster(final_cost_cs)) plot(lcps[], add = T, col = "red") # location 1 to location 2 plot(lcps[], add = T, col = "blue") # location 2 to location 1
cc <- create_cost_corridor(final_cost_cs, loc1, loc2) plot(cc) plot(loc1, add = T) plot(loc2, add = T)
From-Everywhere-to-Everywhere Least Cost Paths
locs <- spsample(as(r, 'SpatialPolygons'),n=10,'regular') lcp_network <- create_FETE_lcps(cost_surface = final_cost_cs, locations = locs, cost_distance = FALSE, parallel = FALSE) plot(raster(final_cost_cs)) plot(locs, add = T) plot(lcp_network, add = T)
Cumulative Cost Paths
locs <- sp::spsample(as(r, 'SpatialPolygons'),n=1,'random') lcp_network <- create_CCP_lcps(cost_surface = final_cost_cs, location = locs, distance = 50, radial_points = 10, cost_distance = FALSE, parallel = FALSE) plot(raster(final_cost_cs)) plot(locs, add = T) plot(lcp_network, add = T)
Banded Least Cost Paths
locs <- sp::spsample(as(r, 'SpatialPolygons'),n=1,'random') lcp_network <- create_banded_lcps(cost_surface = final_cost_cs, location = locs, min_distance = 20, max_distance = 50, radial_points = 10, cost_distance = FALSE, parallel = FALSE) plot(raster(final_cost_cs)) plot(locs, add = T) plot(lcp_network, add = T)
Least Cost Path Density
cumulative_lcps <- create_lcp_density(lcps = lcp_network, raster = r, rescale = FALSE) plot(cumulative_lcps)
cost_surface <- create_slope_cs(r, cost_function = 'tobler') %>% "*" (create_traversal_cs(r)) %>% "*" (create_feature(raster = r, locations = loc1, x = seq(200, 1, length.out = 20)) lcp <- cost_surface %>% create_lcp(cost_surface = . loc1, loc2) cost_corridor <- cost_surface %>% create_cost_corridor(., loc1, loc2) locs <- sp::spsample(as(r, 'SpatialPolygons'),n=10,'regular') lcp_network <- cost_surface %>% create_FETE_lcps(cost_surface = final_cost_cs, locations = locs,cost_distance = FALSE, parallel = FALSE) cumulative_cost_paths <- cost_surface %>% create_FETE_lcps(cost_surface = final_cost_cs, locations = locs,cost_distance = FALSE, parallel = FALSE) %>% create_cumulative_lcps(lcps = ., raster = r, rescale = FALSE)
Please email josephlewis1992[at]gmail.com to provide your feedback or suggest functionality that you would like implemented.
- version 0.1.0
- First release to Github
- version 0.1.1
- Implemented choice of directionality
- version 0.1.2
- Implemented cost when traversing across slope
- version 0.1.3
- Implemented landscape feature attractions - linear decay rate
- version 0.1.4
- Re-implemented functions so LCP process is broken down and more in line with traditional logic of LCP generation.
- Removal of landscape feature attraction function - this will be re-added at a later date
- version 0.1.5
- Addition of create_cost_corridor function.
- Removal of validate_lcp, create_openness, and create_lcp_network - these will be re-added at a later date
- version 0.1.6
- Addition of create_feature_attraction
- Improved readability of create_traversal_slope function
- version 1.0.0
- Removed create_feature_attraction and replaced with create_feature_cs.
- Re-implemented create_lcp_network. Provides parallel and non-parallel functionality
- version 1.1.0
- Added create_cumulative_lcps function for the creation of cumulative least cost path rasters
- version 1.2.0
- Renamed create_lcp_network to create_FETE_lcps for consistency with academic literature
- Implemented create_CCP_lcps
- Implemented create_banded_lcps
- version 1.2.1
- Maximum slope traversable argument added to create_slope_cs function
- Joseph Lewis - author / creator - Website
Please cite as:
Lewis, J. (2020) leastcostpath: Modelling Pathways and Movement Potential Within a Landscape (version 1.2.1)
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|License||GPL (>= 2)|
|Packaged||2020-03-23 19:10:48 UTC; Joe|
|Date/Publication||2020-03-25 16:30:02 UTC|
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