calc_sites: Calculate sites for SSN object.

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

Description

A vector (points) map 'sites' is derived and several attributes are assigned.

Usage

calc_sites(
  locid_col = NULL,
  pid_col = NULL,
  predictions = NULL,
  maxdist = NULL
)

Arguments

locid_col	character (optional); column name in the sites attribute table giving a unique site identifier. If not provided, it is created automatically (based on the 'cat' field; default).
pid_col	character (optional); column name in the sites attribute table that distinguishes between repeated measurements at a sampling site, e.g. by date. If not provided, it is created automatically.
predictions	character vector (optional); names for prediction sites (loaded with import_data).
maxdist	integer (optional); maximum snapping distance in map units (see details). Sites farther away from edges will be deleted.

Details

Steps include:

• Snap points to derived network (edges). 'dist' gives the distance of the original position to the closest streams segment. If this is a too large value consider running derive_streams again with smaller value for accum_threshold and/or min_stream_length.

• Save the new point coordinates in NEAR_X and NEAR_Y.

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

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

Often, survey sites do not lay exactly on the stream network (due to GPS imprecision, stream representation as lines, derivation of streams from dem, etc.). To assign an exact position of the sites on the network they are moved to the closest stream segment (snapped) using the GRASS function v.distance.

If locid_col and pid_col are not provided, 'pid' and 'locID' are identical, unique numbers. If they are provided, they are created based on these columns (as numbers, not as text). Note that measurements can be joined to the sites at a later step (including multiple parameters and multiple measurements) using merge_sites_measurements. Then, 'pid' is updated accordingly.

'upDist' is calculated using v.distance with upload = "to_along" which gives the distance along the stream segment to the next upstream node ('distalong'). 'upDist' is the difference between the 'upDist' of the edge the point lies on and 'distalong'.

The unit for distances (= map units) can be found out using execGRASS("g.proj", flags = "p").

If prediction sites have been created outside of this package they can be processed here as well. They must have been imported with import_data before. Alternatively, prediction sites can be created using calc_prediction_sites.

Note

import_data, derive_streams and calc_edges must be run before.

Author(s)

Mira Kattwinkel [e-mail], Eduard Szoecs, [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 and correct complex confluences (there are no complex confluences in this
# example date set; set accum_threshold in derive_streams to a smaller value
# to create complex confluences)
cj <- check_compl_confluences()
if(cj){
  correct_compl_confluences()
}

# Prepare edges
calc_edges()

# Prepare site
calc_sites()

# Plot data
library(sp)
dem <- readRAST('dem', ignore.stderr = TRUE, plugin = FALSE)
edges <- readVECT('edges', ignore.stderr = TRUE)
sites <- readVECT('sites', ignore.stderr = TRUE)
sites_o <- readVECT('sites_o', ignore.stderr = TRUE)
plot(dem, col = terrain.colors(20),axes = TRUE)
lines(edges, col = 'blue')
points(sites, pch = 4)
points(sites_o, pch = 1)
legend("topright", pch = c(1, 4), legend = c("original", "corrected"))

openSTARS documentation built on Feb. 4, 2022, 5:08 p.m.