evacpath is an R package for road-constrained pedestrian evacuation modeling using least-cost path analysis. It takes generic hazard, road/pathway, and elevation inputs, then returns distance-to-safety and evacuation-time outputs for any projected study area.
The package is designed around a simple idea:
hazard zone + roads/pathways + DEM + projected CRS -> distance-to-safety and evacuation-time outputs
The workflow builds on open-source least-cost path methods for evacuation planning (Cordero et al. 2025) and uses leastcostpath for least-cost path and movement-potential modeling (Lewis 2023; Lewis 2021).
Current status
This is an initial package scaffold, not a polished CRAN release. It is ready for local development with devtools::load_all() and devtools::document().
Core workflow
library(evacpath) result <- run_evacpath( hazard_zone = "path/to/hazard_zone.tif", roads = "path/to/roads.gpkg", dem = "path/to/dem.tif", target_crs = "EPSG:XXXX", region_name = "Study area", road_buffer_m = 2, escape_buffer_m = 5, final_road_buffer_m = 3, seed = 23401, walking_speed_mps = 1.22, clip_mode = "hazard", progress = TRUE ) result$evac_polygons result$distance_points write_evac_outputs( result, output_dir = "outputs", prefix = "study_area" )
Main package functions
| Function | Purpose |
|---|---|
read_spatial() |
Reads either a file path or an existing terra object. |
prepare_hazard_zone() |
Converts an inundation raster into a hazard-zone raster or polygon. |
clean_roads() |
Removes roads/pathways based on user-defined attributes. |
prepare_evac_inputs() |
Reads and projects the hazard zone, roads, and DEM. |
make_evac_grid() |
Creates the evacuation grid over the hazard zone. |
find_escape_points() |
Finds candidate exits where roads cross the hazard boundary. |
make_road_mask() |
Buffers roads and escape points to constrain the DEM. |
make_road_origins() |
Creates road-based origin points inside the hazard zone. |
make_conductance_surface() |
Builds the slope-based conductance surface. |
calc_min_distance_to_safety() |
Calculates minimum least-cost distance to safety. |
calc_evac_time() |
Converts distance to evacuation time. |
make_evac_polygons() |
Creates Voronoi evacuation-distance/time polygons. |
run_evacpath() |
Runs the full workflow. |
write_evac_outputs() |
Writes the main outputs to disk. |
Customizable assumptions
Most modeling assumptions are explicit parameters:
run_evacpath( ..., target_crs = "EPSG:XXXX", grid_resolution = NULL, grid_resolution_factor = 5, road_buffer_m = 2, escape_buffer_m = 5, final_road_buffer_m = 3, dem_resolution = NULL, walking_speed_mps = 1.22, clip_mode = "hazard" )
Tsunami preprocessing
Some coastal workflows need two tsunami zones. The land-only inundation zone is used for origins and mapping. A second zone combines the land inundation footprint with water so that the coastline is not treated as an artificial escape boundary.
library(terra) library(evacpath) tsunami <- rast("path/to/inundation.nc") dem <- rast("path/to/topography.nc") roads <- vect("path/to/roads.shp") zones <- prepare_tsunami_zones( inundation = tsunami, dem = dem, target_crs = "EPSG:XXXX", inundation_threshold = 0, dem_sign_multiplier = 1 ) roads <- clean_roads( roads, exclude = list(field = "road_type", values = "pier"), target_crs = "EPSG:XXXX" ) result <- run_evacpath( hazard_zone = zones$hazard_zone, # land-only TEZ for origins/output escape_zone = zones$escape_zone, # TEZ + water for true inland escape boundary roads = roads, dem = zones$dem, target_crs = "EPSG:XXXX", region_name = "Study area" )
Do not use the land-only hazard_zone to find escape points in tsunami workflows unless you intentionally want the coastline to act as a boundary. In most tsunami cases, use escape_zone = zones$escape_zone.
Local development
From the parent directory of the package:
install.packages(c("devtools", "terra", "remotes")) remotes::install_github("josephlewis/leastcostpath") # if leastcostpath is not on CRAN for your setup devtools::load_all("evacpath") devtools::document("evacpath") devtools::check("evacpath")
Notes
- Use a projected CRS in meters before distance modeling.
- Keep case-specific preprocessing outside the core package when possible.
- Do not assume every DEM needs to be multiplied by
-1; make that decision per dataset. - Do not assume every road layer has the same fields; use
clean_roads()with region-specific settings. - Use
max_originsfor exploratory runs and remove or increase it for final production runs.
Time-grid output
By default, run_evacpath() now clips result$evac_polygons / result$time_grid to the full hazard zone, not just the buffered road network. Movement is still calculated using the road-constrained conductance surface, but the mapped time grid is a Voronoi-style surface over the hazard/inundation zone. Use clip_mode = "road_hazard" only when you want the older road-buffer-limited output.
Example data and figures
Small example inputs are included in inst/extdata/:
inst/extdata/dem.tif
inst/extdata/rds.gpkg
inst/extdata/tsunami_inundation_depth.tif
These files are from the Jakarta example dataset and are used only to demonstrate how to load package data:
dem <- terra::rast(system.file("extdata/dem.tif", package = "evacpath")) roads <- terra::vect(system.file("extdata/rds.gpkg", package = "evacpath")) inundation <- terra::rast(system.file("extdata/tsunami_inundation_depth.tif", package = "evacpath"))
The detailed diagnostic example is available at vignettes/diagnostic-example.Rmd and inst/examples/diagnostic-example.Rmd. It walks through each major function separately, including tsunami-specific zone preparation, inset cropping of roads used for escape-point detection, road-aware escape-boundary generation, least-cost-path testing, and final time-grid mapping.
The README figures are generated with terra plotting code in inst/scripts/make-readme-figures.R. The figures use a focused projected window (x = 669000 to 675000, y = 9223000 to 9225000) so the examples stay readable.
For tsunami workflows, the preferred escape-point pattern is:
zones <- prepare_tsunami_zones(inundation, dem, target_crs = target_crs) roads_for_escape <- crop_roads_to_inner_extent( roads = roads, zone = zones$escape_zone, inset_x_m = 250, inset_y_m = 250 ) escape_boundary_zone <- make_road_aware_escape_zone( escape_zone = zones$escape_zone, roads = roads_for_escape, road_buffer_m = 2, crop_buffer_m = 3 ) escape_points <- find_escape_points( hazard_zone = escape_boundary_zone, roads = roads_for_escape )
Use ?evacpath after running devtools::document() or installing the package to view the package-level help page.
References
Cordero, E., Ruiz Vélez, R., Huérfano Moreno, V., Sherman, C., 2025. Enhancing tsunami evacuation strategies in Puerto Rico using open-source least-cost path analysis. J. Disaster Sci. Manag. 1, 18. https://doi.org/10.1007/s44367-025-00018-y
Lewis, J., 2023. leastcostpath: Modelling Pathways and Movement Potential Within a Landscape.
Lewis, J., 2021. Probabilistic Modelling for Incorporating Uncertainty in Least Cost Path Results: a Postdictive Roman Road Case Study. Journal of Archaeological Method and Theory 28, 911-924. https://doi.org/10.1007/s10816-021-09522-w

