calc_prediction_sites: Calculate prediction sites for 'SSN' object.

In MiKatt/openSTARS: An Open Source Implementation of the 'ArcGIS' Toolbox 'STARS'

Calculate prediction sites for 'SSN' object.

Description

A vector (points) map of prediction sites is created and several attributes are assigned.

Usage

calc_prediction_sites(predictions, dist = NULL, nsites = 10, netIDs = NULL)

Arguments

predictions	string giving the name for the prediction sites map.
dist	number giving the distance between the points to create in map units.
nsites	integer giving the approximate number of sites to create
netIDs	integer (optional): create prediction sites only on streams with these netID(s).

Details

Either dist or nsites must be provided. If dist is NULL, it is estimated by dividing the total stream length in the map by nsites; the number of sites actually derived might therefore be a bit smaller than nsites.

Steps include:

• Place points on edges with given distance from each other

• Save the point coordinates in NEAR_X and NEAR_Y.

• Assign unique identifiers (needed by the 'SSN' package) 'pid' and 'locID'.

• Get 'rid' and 'netID' of the stream segment the site intersects with (from map 'edges').

• Calculate upstream distance for each point ('upDist').

• Calculate distance ratio ('distRatio') between position of the site on the edge (= distance traveled from lower end of the edge to the site) and the total length of the edge.

'pid' and 'locID' are identical, unique numbers. 'upDist' is calculated using r.stream.distance. Points are created using v.segment.

Note

import_data, derive_streams and calc_edges must be run before.

Author(s)

Mira Kattwinkel [e-mail]

Examples

# Initiate and setup GRASS
dem_path <- system.file("extdata", "nc", "elev_ned_30m.tif", package = "openSTARS")
if(.Platform$OS.type == "windows"){
  grass_program_path = "c:/Program Files/GRASS GIS 7.6"
  } else {
  grass_program_path = "/usr/lib/grass78/"
  }

setup_grass_environment(dem = dem_path, 
                        gisBase = grass_program_path,      
                        remove_GISRC = TRUE,
                        override = TRUE
                        )
gmeta()
                        
# Load files into GRASS
dem_path <- system.file("extdata", "nc", "elev_ned_30m.tif", package = "openSTARS")
sites_path <- system.file("extdata", "nc", "sites_nc.shp", package = "openSTARS")
import_data(dem = dem_path, sites = sites_path)

# Derive streams from DEM
derive_streams(burn = 0, accum_threshold = 700, condition = TRUE, clean = TRUE)

check_compl_confluences()
calc_edges()
calc_sites()
calc_prediction_sites(predictions = "preds", dist = 2500)

library(sp)
dem <- readRAST('dem', ignore.stderr = TRUE, plugin = FALSE)
sites <- readVECT('sites', ignore.stderr = TRUE)
preds <- readVECT('preds', ignore.stderr = TRUE)
edges <- readVECT('edges', ignore.stderr = TRUE)
plot(dem, col = terrain.colors(20))
lines(edges, col = 'blue', lwd = 2)
points(sites, pch = 4)
points(preds, pch = 19, col = "darkred")

MiKatt/openSTARS documentation built on June 17, 2022, 5:08 a.m.