River Network Distance Computation and Applications

Description

Reads river network shape files and computes network distances. Also included are a variety of computation and graphical tools designed for fisheries telemetry research, such as minimum home range, kernel density estimation, and clustering analysis using empirical k-functions with a bootstrap envelope. Tools are also provided for editing the river networks, meaning there is no reliance on external software.

Details

The riverdist package provides tools for distance calculation along a river network. The river network is imported from a projected shapefile. Spatial point data may be imported from a shapefile as well, or directly from coordinates.

Some basic formatting of the river shapefile may be necessary. If available, formatting in a geographic information system (GIS) prior to importing into R is recommended (projecting, spatial trimming to the study area, and possibly dissolving river segments), but the riverdist package and its dependencies also include tools for accomplishing the necessary formatting within R.

Author(s)

Matt Tyers

Maintainer: Matt Tyers <matttyersstat@gmail.com>

Dataset: Gulkana River

Description

A stretch of Gulkana River and tributaries.

Usage

data(Gulk)

Format

A river network object, see rivernetwork

Dataset: Kenai River 1

Description

A first pass at a messy river network object.

Usage

data(Kenai1)

Format

A river network object, see rivernetwork

See Also

Kenai2, Kenai3

Dataset: Kenai River 2

Description

A second pass at a messy river network object. In this iteration of cleanup, several non-connected segments have been removed.

Usage

data(Kenai2)

Format

A river network object, see rivernetwork

See Also

Kenai1, Kenai3

Dataset: Kenai River 3

Description

A third pass at a messy river network object. In this iteration of cleanup, several non-connected segments have been removed, and several series of segments have been dissolved into single segments.

Usage

data(Kenai3)

Format

A river network object, see rivernetwork

See Also

Kenai1, Kenai2

Dataset: Killey River, West Channel

Description

A messy and braided section of the Kenai River network - actually a subset of Kenai3.

Usage

data(KilleyW)

Format

A river network object, see rivernetwork

Dataset: Koyukuk River 0

Description

An unusably messy river network object, included for the purpose of testing river network editing functions.

Usage

data(Koyukuk0)

Format

A river network object, see rivernetwork

See Also

Koyukuk1, Koyukuk2

Dataset: Koyukuk River 1

Description

A first pass at a messy river network object. The way it was dissolved in ArcGIS makes the endpoints appear disconnected to line2network and the topologies do not work.

Usage

data(Koyukuk1)

Format

A river network object, see rivernetwork

See Also

Koyukuk2

Dataset: Koyukuk River 2

Description

A second pass at a messy river network object, with topologies fixed from Koyukuk1.

Usage

data(Koyukuk2)

Format

A river network object, see rivernetwork

See Also

Koyukuk1

Dataset: A-B Streams

Description

A complex river network object, a subset of the streams in the Absaroka-Beartooth Wilderness.

Usage

data(abstreams)

Format

A river network object, see rivernetwork

Dataset: A-B Streams 0

Description

An unusably messy river network object, included for the purpose of testing river network editing functions.

Usage

data(abstreams0)

Format

A river network object, see rivernetwork

Add Cumulative Distance to a River Network

Description

Adds a vector of cumulative distances to a river network. Called internally.

Usage

addcumuldist(rivers)

Arguments

Value

Returns an object of class "rivernetwork" containing all spatial and topological information. See rivernetwork-class.

Author(s)

Matt Tyers

Examples

Gulk1 <- addcumuldist(rivers=Gulk)

Add Vertices To Maintain a Minimum Distance Between Vertices

Description

In certain cases, such as when there is a lake within a river system, there may be long, straight lines in a river network with vertices only at either end. In these cases, any point data along these stretches would be snapped to the vertices at either end. This function automatically adds equally-spaced vertices along the straight line, according to a specified minimum allowable distance between vertices.

Usage

addverts(rivers, mindist = 500)

Arguments

Value

A new river network object with the specified segments connected (see rivernetwork)

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Kenai3)
Kenai3split <- addverts(Kenai3,mindist=200)

zoomtoseg(seg=c(47,74,78), rivers=Kenai3)
points(Kenai3$lines[[74]])        # vertices before adding

zoomtoseg(seg=c(47,74,78), rivers=Kenai3split)
points(Kenai3split$lines[[74]])   # vertices after adding

Build Lookup Tables for Fast Distance Computation

Description

Adds lookup tables for distance computation, dramatically reducing computation time. It may take some time to calculate, particularly in a braided network.

Usage

buildlookup(rivers)

Arguments

Value

A rivernetwork object, with a new list element, $distlookup, a list of three matrices. Element [i,j] of each matrix corresponds to the route between segment i and j. The distlookup$middist matrix gives the total distance of the "middle" of each route (between the starting and ending segments"), and the distlookup$starttop and distlookup$endtop matrices have value TRUE, FALSE, or NA if the segments at the beginning or end of the route are connected to the rest of the route at the top of the coordinate matrix, bottom of the coordinate matrix, or if the route is contained to just one segment, respectively. (See rivernetwork.)

Note

This will add three n by n matrices to the river network object, which will be very large if the river network has many segments.

This function is called within cleanup, which is recommended in most cases. It is also called within buildsegroutes, and will add lookup tables by default if there are fewer than 400 segments in the river network.

This function can still be called in the presence of a braided network, but all resulting distances used in subsequent analyses will be the shortest route.

If segment routes ($segroutes) are not present, this function may take a very long time to run.

Author(s)

Matt Tyers

Examples

data(abstreams)

abstreams1 <- buildlookup(abstreams)

Build Segment Routes

Description

Adds the travel routes from the mouth (lowest point) of a river network to each segment, and (optionally) distance lookup tables. This greatly reduces the time needed to detect routes, making distance calculation much more efficient, particularly in the case of multiple distance calculations.

Usage

buildsegroutes(rivers, lookup = NULL, verbose = FALSE)

Arguments

Value

A rivernetwork object, with a new list element, $segroutes, which gives the route from the mouth to each rivernetwork segment. Optionally, it may add $distlookup, distance lookup tables for even faster distance computation. (See rivernetwork.)

Note

In the event of braiding (multiple channels), it is likely that there will be differences in the routes detected. If this is the case, building routes will likely result in a shorter and more efficient route. Regardless, extreme caution is always advised in the event of braiding.

The mouth segment and vertex must be specified (see setmouth).

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

Examples

data(abstreams)
plot(x=abstreams)
abstreams1 <- abstreams
abstreams1$segroutes <- NULL #taking out the $segroutes component

# before
tstart <- Sys.time()
detectroute(start=120, end=111, rivers=abstreams1)
Sys.time() - tstart

# after
tstart <- Sys.time()
detectroute(start=120, end=111, rivers=abstreams)
Sys.time() - tstart

Calculate the Connectivity Matrix for a River Network

Description

Calculates the connectivity matrix for a river network, during import and editing. Called internally.

Usage

calculateconnections(lines, tolerance)

Arguments

Value

A matrix with topological information. See the $connections element of the rivernetwork-class.

Author(s)

Matt Tyers

Examples

Gulk_connections <- calculateconnections(lines=Gulk$lines, tolerance=Gulk$tolerance)

Check for Braiding in a River Network

Description

Detects braiding (multiple flow channels between two locations) within a river network object. Braiding can either be checked for in the route between two segments, or in the river network as a whole.

Usage

checkbraided(rivers, startseg = NULL, endseg = NULL, progress = TRUE)

Arguments

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

Examples

data(Gulk)
plot(x=Gulk)
checkbraided(rivers=Gulk)

data(KilleyW)
plot(x=KilleyW)
checkbraided(rivers=KilleyW)

Kenai3.subset <- trimriver(trimto=c(22,2,70,30,15,98,96,89,52,3), rivers=Kenai3)
plot(x=Kenai3.subset)

checkbraided(startseg=1, endseg=7, rivers=Kenai3.subset)
checkbraided(startseg=1, endseg=5, rivers=Kenai3.subset)

Check for Braiding in a River Network

Description

Detects braiding (multiple flow channels between two locations) within a river network object, and returns a logical value for specifying braiding within a river network object.

Usage

checkbraidedTF(rivers, toreturn = "rivers", progress = TRUE)

Arguments

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

Examples

data(Gulk,KilleyW)
Gulk <- setmouth(seg=1, vert=1, rivers=Gulk)
plot(x=Gulk)
checkbraidedTF(rivers=Gulk, toreturn="logical")

KilleyW <- setmouth(seg=1, vert=288, rivers=KilleyW)
plot(x=KilleyW)
checkbraidedTF(rivers=KilleyW, toreturn="logical")
checkbraidedTF(rivers=KilleyW, toreturn="routes")

KilleyW.1 <- checkbraidedTF(rivers=KilleyW, toreturn="rivers")
str(KilleyW.1)

Interactive Cleanup of a River Network

Description

This is the recommended function to use for cleanup of a river network. It calls all available river network editing functions in appropriate sequence, detecting which are needed or recommended, and prompts user input wherever necessary.

Currently, it automatically calls removeduplicates, prompts the user whether to run dissolve, automatically runs removemicrosegs and splitsegments if needed, provides user prompts for addverts and setmouth, detects if segments are unconnected and provides user prompts for removeunconnected or connectsegs, automatically runs checkbraidedTF, and prompts the user whether to run buildsegroutes if no braiding is detected.

Usage

cleanup(rivers)

Arguments

Value

A new river network object, see rivernetwork

Author(s)

Matt Tyers

See Also

line2network

Examples

data(abstreams0,Koyukuk0,Kenai1)

# abstreams_fixed <- cleanup(abstreams0)
# Koyukuk <- cleanup(Koyukuk0)
# Kenai <- cleanup(Kenai1)

Interactive Cleanup of the Vertices of Individual Segments

Description

A trial version of a function for deep-cleaning a river network.

Sometimes a shapefile contains errors that are not obvious at an initial check, typically vertices that should not be there.

This function steps through each segment in sequence, and allows the user to interactively remove vertices.

Usage

cleanup_verts(rivers, startwith = 1)

Arguments

Value

A new river network object, see rivernetwork

Note

Stepping through a large and messy river network can be time-consuming. To resume a cleanup session, use the startwith= argument and the last returned river network. For example, if rivers1 <- cleanup_verts(rivers) were initially called and the user selected "save & close" at segment 100, cleanup can be resumed by calling rivers2 <- cleanup_verts(rivers1, startwith=100).

Author(s)

Matt Tyers

See Also

line2network

Examples

data(abstreams0,Koyukuk0,Kenai1)

# abstreams_fixed1 <- cleanup_verts(abstreams0)
# Koyukuk <- cleanup(Koyukuk0)
# Kenai <- cleanup(Kenai1)

Connect Segments

Description

Provides a method to manually connect unconnected segments within a river network. The nearest endpoint (or vertex) of the second segment is added as a new vertex to the first, and the network topology is then updated.

Usage

connectsegs(
  connect,
  connectto,
  nearestvert = TRUE,
  rivers,
  calcconnections = TRUE
)

Arguments

Value

A new river network object with the specified segments connected (see rivernetwork)

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Koyukuk0)
plot(Koyukuk0, ylim=c(1930500,1931500), xlim=c(194900,195100))
topologydots(Koyukuk0, add=TRUE)

Koyukuk0.1 <- connectsegs(connect=21, connectto=20, rivers=Koyukuk0)
plot(Koyukuk0.1,ylim=c(1930500,1931500), xlim=c(194900,195100))
topologydots(Koyukuk0.1, add=TRUE)

# or the vector version
zoomtoseg(seg=21:23, rivers=Koyukuk0)
Koyukuk0.2 <- connectsegs(connect=c(20,21,22), connectto=c(21,22,23), 
    nearestvert=c(FALSE,FALSE,TRUE), rivers=Koyukuk0)
zoomtoseg(seg=21:23, rivers=Koyukuk0.2)
topologydots(Koyukuk0.2, add=TRUE)

Plot Difference from Mean Kernel Density Using River Distance

Description

Plots kernel density anomaly for each survey, which is defined as the difference between kernel density for each survey and mean kernel density across all surveys. The intent of this function is to highlight areas in which density is higher or lower for specific surveys than it is on average.

The input argument is an object returned from makeriverdensity.

Usage

densityanomaly(
  x,
  whichplots = NULL,
  method = c("overlap", "both", "positive", "negative"),
  negative_ramp = "blue",
  positive_ramp = "red",
  parmfrow = NULL,
  ...
)

Arguments

Value

NULL

Author(s)

Matt Tyers

See Also

makeriverdensity, plot.riverdensity, plotriverdensitypoints

Examples

data(Gulk, fakefish)

Gulk_dens <- makeriverdensity(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, 
  survey=fakefish$flight.date)
  
# first, the behavior of plot.riverdensity
# # 10 plots will be created, recommend calling par(mfrow=c(2,5))
plot(x=Gulk_dens)

# next, showing densityanomaly
densityanomaly(x=Gulk_dens, parmfrow=c(2,5))
densityanomaly(x=Gulk_dens, method="negative", parmfrow=c(2,5))
densityanomaly(x=Gulk_dens, method="positive", parmfrow=c(2,5))

Detect Route

Description

Called internally within riverdistance. Detects the sequential route from one river network segment to another.

Usage

detectroute(
  start,
  end,
  rivers,
  verbose = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A vector of segment numbers corresponding to the ordered route.

Author(s)

Matt Tyers

Examples

data(Gulk)
plot(x=Gulk, cex=1)

detectroute(start=6, end=14, rivers=Gulk)

tstart <- Sys.time()
detectroute(start=120, end=111, rivers=abstreams, algorithm="sequential")
tend <- Sys.time()
tend - tstart

data(abstreams)
tstart <- Sys.time()
detectroute(start=120, end=111, rivers=abstreams, algorithm="Dijkstra")
tend <- Sys.time()
tend - tstart

tstart <- Sys.time()
detectroute(start=120, end=111, rivers=abstreams, algorithm="segroutes")
tend <- Sys.time()
tend - tstart

Dissolve

Description

Acts like a spatial dissolve within a GIS environment. Simplifies a river network object by combining "runs" of segments with no other connections.

Usage

dissolve(rivers)

Arguments

Value

A new river network object with segments combined

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Kenai2)
plot(x=Kenai2)

Kenai2dissolve <- dissolve(rivers=Kenai2)
plot(x=Kenai2dissolve)

Dataset: Fakefish

Description

A set of observations of Fakefish on the Gulkana River and its tributaries.

Usage

data(fakefish)

Format

A data frame

Details

• x. X-coordinate of observation (Alaska Albers Equal Area). Note that the locations do not align with the river network object.

• y. Y-coordinate of observation

• seg. River segment (with x- and y-coordinates snapped to river network object)

• vert. River vertex

• fish.id. Numeric identifier for each fish (individual fish were observed more than once)

• flight. Numeric identifier for each telemetry flight

• flight.date. Date of each telemetry flight

See Also

Gulk

Dataset: Fakefish Density

Description

An object created by riverdensity, describing the density of Fakefish points in the Gulkana River during ten surveys.

Usage

data(fakefish_density)

Format

A river density object, see riverdensity, plotriverdensity, riverdensity-class

Details

Intended for plotting using plotriverdensity.

Highlight Segments

Description

Plots a river network object and displays specified segments in bold, for easy identification.

Usage

highlightseg(seg, rivers, cex = 0.8, lwd = 3, add = FALSE, color = FALSE, ...)

Arguments

Author(s)

Matt Tyers

Examples

data(Kenai3)
plot(Kenai3)
highlightseg(seg=c(10,30,68),rivers=Kenai3)

Home Range

Description

Returns the minimum observed home range for multiple observations of each individual fish.

Usage

homerange(
  unique = NULL,
  survey = NULL,
  seg,
  vert,
  rivers,
  map = FALSE,
  algorithm = NULL,
  main = NULL,
  ...
)

Arguments

Value

An object of the homerange-class. The $ranges element is a data frame with two columns: $ID is a list of unique fish (as specified by unique=), and $range is calculated minimum home range, in the units of the coordinate system (this will likely be meters). The other elements are used for plotting, see homerange-class for more details.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

plot.homerange, homerangeoverlap, plothomerangeoverlap

Examples

data(Gulk, fakefish)
ranges <- with(fakefish, homerange(unique=fish.id, survey=flight, seg=seg, vert=vert, rivers=Gulk))
ranges

# 19 plots will be produced, recommend calling par(mfrow=c(4,5))
plot(ranges)
plot(ranges,cumulative=TRUE,label=TRUE)

homerangeoverlap(ranges)

plothomerangeoverlap(ranges)
with(fakefish, riverpoints(seg=seg, vert=vert, rivers=Gulk))

The "homerange" Class

Description

A class that holds information computed from the homerange function. Contains all information for plotting in plot.homerange.

Elements

ranges:

Object of class "data.frame". Contains a column of the identifiers for each individual, and a column of the associated home ranges.

subseg_n:

List of the number of times each subsegment was traveled. The first level of the list corresponds to individual, the second level to river segment.

subseg_length:

List of lengths of each subsegment.

seg, vert, unique, rivers:

All inputs from the original homerange call.

Author(s)

Matt Tyers

Home Range Overlap

Description

Returns matrices describing the overlap of the minimum observed home range for multiple observations of each individual fish.

Usage

homerangeoverlap(x)

Arguments

Value

A list of three matrices, with $either giving the distances represented by the union of home ranges of each pair of individuals, and $both giving the distances represented by the intersection of home ranges of each pair of individuals. Element $prop_both gives the proportion of overlap, defined as intersection/union.

Author(s)

Matt Tyers

See Also

homerange, plot.homerange, plothomerangeoverlap

Examples

data(Gulk, fakefish)
ranges <- with(fakefish, homerange(unique=fish.id, survey=flight, seg=seg, vert=vert, rivers=Gulk))
ranges

# 19 plots will be produced, recommend calling par(mfrow=c(4,5))
plot(ranges)
plot(ranges,cumulative=TRUE,label=TRUE)

homerangeoverlap(ranges)

plothomerangeoverlap(ranges)
with(fakefish, riverpoints(seg=seg, vert=vert, rivers=Gulk))

Check Flow-Connectedness

Description

Checks to see if two segments are flow-connected. Called internally within riverdirection and upstream.

Usage

isflowconnected(seg1, seg2, rivers, stopiferror = TRUE, algorithm = NULL)

Arguments

Value

Logical TRUE if the two segments are flow-connected, FALSE if they are not

Note

The river mouth must be specified (see setmouth).

Author(s)

Matt Tyers

Examples

data(Gulk)
plot(Gulk)

Gulk <- setmouth(seg=1, vert=1, rivers=Gulk)

isflowconnected(seg1=13, seg2=14, rivers=Gulk)
isflowconnected(seg1=13, seg2=1, rivers=Gulk)

Plotting K-functions for a Set of Surveys

Description

Plots K-functions for locations in each of a set of surveys. In this implementation, this can be interpreted as the proportion of additional fish within a given distance. This will increase as a function of distance, and may provide evidence of clustering or dispersion features, particularly if the envelope is used.

Usage

kfunc(
  seg,
  vert,
  survey = NULL,
  rivers,
  lwd = 2,
  envelope = TRUE,
  envreps = 1000,
  envcol = "grey80",
  envborder = NA,
  maxdist = NULL,
  xlab = "Distance",
  ylab = "% within",
  showN = TRUE,
  whichplots = NULL,
  returnoutput = FALSE,
  ...
)

Arguments

Note

K-function envelopes for each survey are constructed by bootstrapping all within-survey distances, that is, the distances between all individuals within each survey, for all surveys. This results in a confidence envelope under the assumption that spacing is independent of survey; therefore a survey K-function outside the envelope provides evidence of clustering or dispersal in that survey that is outside the typical range. An envelope is not available if only one survey is plotted.

A K-function above the envelope for a given distance range provides evidence of a greater number of individuals than expected at that distance range (clustering); A K-function below the envelope for a given distance range provides evidence of a smaller number of individuals than expected at that distance range (dispersal).

This function is distance-computation intensive, and will be extremely slow-running if a river network is used that does not have segment routes and/or distance lookup tables for fast distance computation. See buildsegroutes and/or buildlookup for more information.

Author(s)

Matt Tyers

Examples

data(Gulk, fakefish)

# # 10 plots will be created - recommend calling
# # par(mfrow=c(3,4))

kfunc(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, survey=fakefish$flight,
envreps=100, maxdist=200000)

# # This shows relatively high amounts of clustering for surveys 1 and 8,
# # and relatively high amounts of dispersal in surveys 5 and 6.


# # plotting the survey locations that led to this calculation, for comparison

# # 10 plots will be created - recommend calling
# # par(mfrow=c(3,4))
for(i in 1:10) {
  plot(x=Gulk, segmentnum=FALSE, color=FALSE, main=i)
  riverpoints(seg=fakefish$seg[fakefish$flight==i], 
  vert=fakefish$vert[fakefish$flight==i], rivers=Gulk, col=2, pch=15)
}

Create a River Network Object from a Shapefile

Description

Uses read_sf in package 'sf' to read a river shapefile, and establishes connectivity of segment endpoints based on spatial proximity.

Usage

line2network(
  sf = NULL,
  path = ".",
  layer = NA,
  tolerance = 100,
  reproject = NULL,
  autofix = TRUE
)

Arguments

Value

Returns an object of class "rivernetwork" containing all spatial and topological information. See rivernetwork-class.

Note

Since distance can only be calculated using projected coordinates, line2network() will generate an error if a non-projected input shapefile is detected. To resolve this, the shapefile can be re-projected in a GIS environment, or using reproject=, shown in the second example below.

Author(s)

Matt Tyers, Jemma Stachelek

Examples

filepath <- system.file("extdata", package="riverdist")

Gulk_UTM5 <- line2network(path=filepath, layer="Gulk_UTM5")
plot(Gulk_UTM5)

## Reading directly from an sf object

sf <- sf::read_sf(dsn = filepath, layer = "Gulk_UTM5")
Gulk_UTM5 <- line2network(sf=sf)
plot(Gulk_UTM5)

## Re-projecting in Alaska Albers Equal Area projection:

AKalbers <- "+proj=aea +lat_1=55 +lat_2=65 +lat_0=50 +lon_0=-154 
    +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80"
    
Gulk_AKalbers <- line2network(path=filepath, layer="Gulk_UTM5", reproject=AKalbers)
plot(Gulk_AKalbers)

Dataset: Line 98 of Kenai River 1 (Long-Lat)

Description

A matrix of coordinates in longitude-latitude, used to illustrate coordinate transformation. Coordinates come from arbitrary line number 98 in the Kenai River 1 shapefile, rendered in long-lat.

Usage

data(line98)

Format

A matrix of values

Calculate Kernel Density Using River Distance

Description

Uses spatial point data (segment and vertex) to calculate a kernel density object to use in the output class plotting method,plot.riverdensity. Scaled kernel density is calculated at approximately regularly-spaced locations, with spacing specified by the user.

If an argument is used in the survey field, kernel densities will be calculated for each unique value of survey, resulting in a separate plot for each.

The purpose of this function is to generate a kernel density object to plot using plot(), see plot.riverdensity.

Usage

makeriverdensity(
  seg,
  vert,
  rivers,
  survey = NULL,
  kernel = "gaussian",
  bw = NULL,
  resolution = NULL
)

Arguments

Value

A river density object, see riverdensity-class.

Note

It is likely that calculation will be very slow. Use of this function with a river network for which segment routes has not yet been calculated is not recommended.

This function is distance-computation intensive, and may be slow-running if a river network is used that does not have segment routes and/or distance lookup tables for fast distance computation. See buildsegroutes and/or buildlookup for more information.

Author(s)

Matt Tyers

See Also

plot.riverdensity, densityanomaly, plotriverdensitypoints

Examples

data(Gulk, fakefish)

Gulk_dens <- makeriverdensity(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, 
  survey=fakefish$flight.date)
  
# # 10 plots will be created, recommend calling par(mfrow=c(2,5))
plot(x=Gulk_dens)

Map Segments by Name

Description

Provides a check that river network segments were appropriately named.

Usage

mapbyname(rivers, scale = TRUE, cex = 0.6, ...)

Arguments

Author(s)

Matt Tyers

Examples

data(Gulk)
str(Gulk)

Gulk$names <- c("Gulkana River","Trib 1","West Fork","Gulkana River","Trib 1",
                "West Fork","Trib 2","West Fork","Twelvemile Creek","Gulkana River",
                "Middle Fork","Gulkana River","Middle Fork","Hungry Hollow")
str(Gulk)

mapbyname(rivers=Gulk)

Generate List of Distance Matrix Between Observations, for All Individuals

Description

Returns a list of matrices, each giving the river distance, direction, or upstream travel distance between all observations of one unique fish. This function is principally intended for producing an object to plot in plotmatbysurveylist.

Usage

matbysurveylist(
  unique,
  survey,
  seg,
  vert,
  rivers,
  indiv = NULL,
  method = "upstream",
  flowconnected = FALSE,
  net = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A list with each element corresponding to a unique fish. Each list element is the output from either riverdistancematbysurvey, riverdirectionmatbysurvey, or upstreammatbysurvey.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdistance, riverdirection, upstream, riverdistancematbysurvey, riverdirectionmatbysurvey, upstreammatbysurvey, plotmatbysurveylist

Examples

data(Gulk, smallset)
matbysurveylist <- matbysurveylist(unique=smallset$id, survey=smallset$flight, seg=smallset$seg, 
   vert=smallset$vert, rivers=Gulk)
plotmatbysurveylist(matbysurveylist)
plotmatbysurveylist(matbysurveylist,type="confint")
plotmatbysurveylist(matbysurveylist,type="dotplot")
   
data(fakefish)
# matbysurveylist <- matbysurveylist(unique=fakefish$fish.id, survey=fakefish$flight, 
#   seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
# plotmatbysurveylist(matbysurveylist)

Distance From Mouth

Description

Calculates distance from river locations (given as vectors of segment and vertex) and the specified mouth of the river network. The mouth must first be specified (see setmouth).

Usage

mouthdist(seg, vert, rivers, stopiferror = TRUE, algorithm = NULL)

Arguments

Value

Distance (numeric)

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

Examples

data(Gulk)

# Mouth must be specified
Gulk$mouth$mouth.seg <- 1
Gulk$mouth$mouth.vert <- 1

mouthdist(seg=4, vert=40, rivers=Gulk)
mouthdist(seg=c(4,5), vert=c(40,20), rivers=Gulk)

Distance From Mouth for All Observations of Individuals

Description

Calculates distance from the mouth of a river network to all observations of each individual (given as segment and vertex). and the specified mouth of the river network. The mouth must first be specified (see setmouth). Returns a matrix of distances, with a row for each unique individual and a column for each survey.

A plotting method is provided for the output; see plotseq.

Usage

mouthdistbysurvey(
  unique,
  survey,
  seg,
  vert,
  rivers,
  logical = NULL,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A vector of river network distances (numeric), with each row corresponding to a unique fish and each column corresponding to a unique survey. Values of NA indicate the individual not being located during the survey in question.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

plotseq

Examples

data(Gulk, fakefish)

seqbysurvey <- mouthdistbysurvey(unique=fakefish$fish.id, survey=fakefish$flight.date, 
    seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
seqbysurvey
plotseq(seqbysurvey)

Pythagorean Distance

Description

Pythagorean distance between two points. Called internally.

Usage

pdist(p1, p2)

Arguments

Value

Distance (numeric)

Author(s)

Matt Tyers

Examples

point1 <- c(1,3)
point2 <- c(4,7)

pdist(point1,point2)

Total Pythagorean Distance

Description

Total Pythagorean distance of a sequence of points. Called internally.

Usage

pdisttot(xy)

Arguments

Value

Distance (numeric)

Author(s)

Matt Tyers

Examples

points <- matrix(c(1:10), nrow=5, ncol=2, byrow=FALSE)

pdisttot(xy=points)

Plot Home Range

Description

Plotting method for home range, the minimum observed home range for multiple observations of each individual fish.

Usage

## S3 method for class 'homerange'
plot(
  x,
  cumulative = FALSE,
  lwd = 3,
  maxlwd = 10,
  col = 4,
  pch = 21,
  label = FALSE,
  main = NULL,
  ...
)

Arguments

Author(s)

Matt Tyers, bug fix by Jordy Bernard

See Also

homerange, homerangeoverlap, plothomerangeoverlap

Examples

data(Gulk, fakefish)
ranges <- with(fakefish, homerange(unique=fish.id, survey=flight, seg=seg, vert=vert, rivers=Gulk))
ranges

# 19 plots will be produced, recommend calling par(mfrow=c(4,5))
plot(ranges)
plot(ranges,cumulative=TRUE,label=TRUE)

homerangeoverlap(ranges)

plothomerangeoverlap(ranges)
with(fakefish, riverpoints(seg=seg, vert=vert, rivers=Gulk))

Plot Kernel Density Using River Distance

Description

Produces a kernel density plot from a kernel density object created by makeriverdensity.

If the kernel density object includes densities from multiple surveys, a new plot will be created for each survey.

Densities can be displayed using either line widths, color, or both.

The relative densities that are displayed in the plot are calculated according to the form (density/maxdensity)^pwr, with the value of pwr set by the pwr argument. Setting pwr to a value less than 1 allows smaller values to be more visible on the plot.

Usage

## S3 method for class 'riverdensity'
plot(
  x,
  whichplots = NULL,
  points = TRUE,
  bycol = TRUE,
  bylwd = TRUE,
  maxlwd = 10,
  pwr = 0.7,
  scalebyN = TRUE,
  ramp = c("grey", "gray", "red", "green", "blue", "heat", "stoplight", "rainbow"),
  lwd = 1,
  linecol = NULL,
  denscol = NULL,
  alpha = 1,
  dark = 1,
  showN = TRUE,
  main = NULL,
  xlab = "",
  ylab = "",
  add = FALSE,
  scalebar = TRUE,
  ...
)

Arguments

Author(s)

Matt Tyers

See Also

makeriverdensity, densityanomaly, plotriverdensitypoints

Examples

data(Gulk, fakefish)

Gulk_dens <- makeriverdensity(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, 
  survey=fakefish$flight.date)
  
# # 10 plots will be created, recommend calling par(mfrow=c(2,5))
plot(x=Gulk_dens)

Plotting a River Network

Description

S3 plotting method for the rivernetwork-class. Produces a map of all river segments of a river network object.

Usage

## S3 method for class 'rivernetwork'
plot(
  x,
  segmentnum = TRUE,
  offset = TRUE,
  lwd = 1,
  cex = 0.6,
  scale = TRUE,
  color = TRUE,
  empty = FALSE,
  linecol = 1,
  xlab = "",
  ylab = "",
  ...
)

Arguments

Note

This function is intended to provide basic visual checks for the user, not for any real mapping.

Author(s)

Matt Tyers

Examples

data(Gulk)
plot(x=Gulk)

Plot Home Range Overlap

Description

Produces a plot of the overlap of the minimum observed home range for multiple observations of each individual fish, with line thickness illustrating the respective number of individuals' homeranges represented.

Usage

plothomerangeoverlap(x, lwd = 3, maxlwd = 10, col = 4, ...)

Arguments

Author(s)

Matt Tyers

See Also

homerange, plot.homerange, homerangeoverlap

Examples

data(Gulk, fakefish)
ranges <- with(fakefish, homerange(unique=fish.id, survey=flight, seg=seg, vert=vert, rivers=Gulk))
ranges

# 19 plots will be produced, recommend calling par(mfrow=c(4,5))
plot(ranges)
plot(ranges,cumulative=TRUE,label=TRUE)

homerangeoverlap(ranges)

plothomerangeoverlap(ranges)
with(fakefish, riverpoints(seg=seg, vert=vert, rivers=Gulk))

Plot Upstream Distance Between Observations of All Individuals

Description

Produces a matrix of plots (boxplots are default), with plot [i,j] giving the distribution of upstream distances from observation i to observation j, for all individuals.

Usage

plotmatbysurveylist(matbysurveylist, type = "boxplot", showN = TRUE, ...)

Arguments

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

upstream, upstreammatbysurvey

Examples

data(Gulk, smallset)
matbysurveylist <- matbysurveylist(unique=smallset$id, survey=smallset$flight, seg=smallset$seg, 
   vert=smallset$vert, rivers=Gulk)
plotmatbysurveylist(matbysurveylist)
plotmatbysurveylist(matbysurveylist,type="confint")
plotmatbysurveylist(matbysurveylist,type="dotplot")
   
data(fakefish)
# matbysurveylist <- matbysurveylist(unique=fakefish$fish.id, survey=fakefish$flight, 
#   seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
# plotmatbysurveylist(matbysurveylist)

Plot Points Used for Kernel Density

Description

Plots the points used to calculate a kernel density object in makeriverdensity.

This function is intended as a visual check that a sufficient resolution was used.

Usage

plotriverdensitypoints(riverdensity)

Arguments

Author(s)

Matt Tyers

See Also

makeriverdensity, plot.riverdensity

Examples

data(Gulk, fakefish)

Gulk_dens <- makeriverdensity(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)

plotriverdensitypoints(riverdensity=Gulk_dens)

Plot Sequence of Observations

Description

Plots the sequence of observations or movements of each individual (given as segment and vertex). This function is primarily intended for use with mouthdistbysurvey, but will also work with riverdistanceseq and upstreamseq.

Usage

plotseq(
  seqbysurvey,
  type = "boxplot",
  xlab = "",
  ylab = "",
  main = "",
  cex.axisX = 0.8,
  lowerbound = NULL,
  upperbound = NULL,
  boundtype = "negative",
  surveysareDates = F,
  ...
)

Arguments

Note

Plots are intended as descriptive only. Any ANOVA-like inference that is suggested from these plots is strongly discouraged. The user is instead advised to use a mixed-effects model or some other inferential tool that accounts for repeated-measures and/or temporal autocorrelation.

Author(s)

Matt Tyers

Examples

data(Gulk, fakefish)

x <- mouthdistbysurvey(unique=fakefish$fish.id, survey=fakefish$flight.date, 
    seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
    
plotseq(seqbysurvey=x)
plotseq(seqbysurvey=x, type="boxline")
plotseq(seqbysurvey=x, type="dotplot")
plotseq(seqbysurvey=x, type="dotline")

plotseq(seqbysurvey=x, type="dotline", surveysareDates=TRUE)

from_upstreamseq <- upstreamseq(unique=fakefish$fish.id, 
   survey=fakefish$flight, seg=fakefish$seg, vert=fakefish$vert, 
   rivers=Gulk)
plotseq(seqbysurvey=from_upstreamseq)

Convert a Point Shapefile to River Locations

Description

This function reads a point shapefile and determines the closest vertex in the river network to each point of XY data, returning a data frame with river locations, defined as segment numbers and vertex numbers, along with the data table read from the input shapefile.

Usage

pointshp2segvert(path = ".", layer, rivers)

Arguments

Value

A data frame of river locations, with segment numbers in $seg, vertex numbers in $vert, snapping distances in $snapdist, snapped x- and y-coordinates in $snap_x and $snap_y, and the remaining columns corresponding to the data table in the input point shapefile.

Note

If the input shapefile is detected to be in a different projection than the river network, the input shapefile will be re-projected before conversion to river locations.

Author(s)

Matt Tyers

See Also

xy2segvert

Examples

filepath <- system.file("extdata", package="riverdist")

fakefish_UTM5 <- pointshp2segvert(path=filepath, layer="fakefish_UTM5", rivers=Gulk)
head(fakefish_UTM5)

plot(x=Gulk)
points(fakefish_UTM5$x, fakefish_UTM5$y)
riverpoints(seg=fakefish_UTM5$seg, vert=fakefish_UTM5$vert, rivers=Gulk, pch=16, col=2)

Remove Duplicates

Description

Removes duplicated line segments, which can sometimes exist within a shapefile.

Usage

removeduplicates(rivers)

Arguments

Value

A new river network object with duplicated segments removed, see rivernetwork

Author(s)

Matt Tyers

See Also

line2network

Examples

data(abstreams0)
zoomtoseg(seg=c(170,171,157),rivers=abstreams0)

abstreams1 <- removeduplicates(rivers=abstreams0)
zoomtoseg(seg=c(166,167,154),rivers=abstreams1)

Remove Segments that are Smaller than the Connectivity Tolerance

Description

Automatically detects and removes segments with total displacement (straight-line distance between endpoints) less than the connectivity tolerance. These segments do not serve any real purpose, are bypassed in routes, and cannot be dissolved.

Usage

removemicrosegs(rivers)

Arguments

Value

A new river network object with the specified segments connected (see rivernetwork)

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(abstreams0)
abstreams1 <- removemicrosegs(abstreams0)

Remove Unconnected Segments

Description

Detects and removes segments that are not connected to the river mouth.

Usage

removeunconnected(rivers)

Arguments

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

Examples

data(Koyukuk2)
Koy_subset <- trimriver(trimto=c(30,28,29,3,19,27,4),rivers=Koyukuk2)
Koy_subset <- setmouth(seg=1,vert=427,rivers=Koy_subset)
plot(Koy_subset)

Koy_subset_trim <- removeunconnected(Koy_subset)
plot(Koy_subset_trim)

The "riverdensity" Class

Description

A class that holds density information computed from point data along a river network.

Details

Created by makeriverdensity from point data and a river network. Contains all information for plotting in plot.riverdensity.

Elements

densities:

Object of class "list". Each list element corresponds to a unique value of survey. Each element is itself of class "list", with each element corresponding to a segment from the associated river network. Each element is a vector of class "numeric", with values equal to the scaled densities calculated at the river network vertices stored in $densverts of the associated river network segment.

endptverts:

List of vectors of class "numeric". Each list element is a vector of the vertices of the endpoints of the subsegments considered for density calculation. Each list element corresponds to a river segment from the associated river network.

densverts:

List of vectors of class "numeric". Each element is a vector of the vertices of the points of the subsegments considered for density calculation, that were used for density calculation. Each list element corresponds to a river segment from the associated river network.

pointsegs:

Vector of class "numeric". Defined as the segment numbers of the point data used for density calculation.

pointverts:

Vector of class "numeric". Defined as the vertex numbers of the point data used for density calculation.

survey:

Vector of class "numeric" or class "character". Defined as the survey identifiers associated with the point data used for density calculation.

rivers:

Object of class "rivernetwork" ; see rivernetwork-class

.

Author(s)

Matt Tyers

River Direction

Description

Calculates direction of travel between two points. Only works if river mouth (lowest point) has been specified (see setmouth).

Usage

riverdirection(
  startseg,
  endseg,
  startvert,
  endvert,
  rivers,
  flowconnected = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

Direction: "up", "down", or "0" (character). Returns NA if flowconnected==TRUE and the two segments are not flow-connected.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

setmouth

Examples

data(Gulk)

# Mouth must be specified
Gulk$mouth$mouth.seg <- 1
Gulk$mouth$mouth.vert <- 1

plot(x=Gulk)
riverdirection(startseg=6, endseg=3, startvert=40, endvert=40, rivers=Gulk)

River Direction Matrix

Description

Returns a matrix of calculated travel direction between every point and every other point of given river locations (segment and vertex), or of a subset. The mouth (lowest point) segment and vertex must be specified (see setmouth).

Usage

riverdirectionmat(
  seg,
  vert,
  rivers,
  logical = NULL,
  ID = NULL,
  flowconnected = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of directions (character) with rows and columns labeled by corresponding values of ID. See riverdirection for additional information.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdirection

Examples

data(Gulk, fakefish)

# Mouth must be specified
Gulk$mouth$mouth.seg <- 1
Gulk$mouth$mouth.vert <- 1

logi1 <- (fakefish$flight.date==as.Date("2015-11-25"))

riverdirectionmat(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, logical=logi1)

River Direction Matrix of All Observations of an Individual

Description

Returns a matrix of travel direction between all observations of one unique fish.

Usage

riverdirectionmatbysurvey(
  indiv,
  unique,
  survey,
  seg,
  vert,
  rivers,
  full = TRUE,
  flowconnected = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of directions (character), with rows and columns defined by survey. In the resulting matrix, the element with the row identified as A and column identified as B is defined as the direction traveled from survey A to survey B. Therefore, it is likely that only the upper triangle of the matrix will be of interest.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdirection

Examples

data(Gulk, fakefish)
riverdirectionmatbysurvey(indiv=1, unique=fakefish$fish.id, survey=fakefish$flight,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
     
riverdirectionmatbysurvey(indiv=1, unique=fakefish$fish.id, survey=fakefish$flight,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, full=FALSE)

River Travel Direction Between Sequential Observations

Description

Returns a matrix of directions traveled by unique fish between sequential surveys. The mouth (lowest point) segment and vertex must be specified (see setmouth).

Usage

riverdirectionseq(
  unique,
  survey,
  seg,
  vert,
  rivers,
  logical = NULL,
  flowconnected = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A data frame of directions (character), with rows defined by unique fish and columns defined by observation increment (1 to 2, 2 to 3, etc.) See riverdirection for additional information.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdirection

Examples

data(Gulk, fakefish)

# Mouth must be specified
Gulk$mouth$mouth.seg <- 1
Gulk$mouth$mouth.vert <- 1

riverdirectionseq(unique=fakefish$fish.id, survey=fakefish$flight, seg=fakefish$seg,
   vert=fakefish$vert, rivers=Gulk)

riverdirectionseq(unique=fakefish$fish.id, survey=fakefish$flight.date, seg=fakefish$seg,
   vert=fakefish$vert, rivers=Gulk)

River Direction Matrix between Two Datasets

Description

Returns a matrix of directions between each river location in two datasets, with one expressed as rows and the other expressed as columns.

Usage

riverdirectiontofrom(
  seg1,
  vert1,
  seg2,
  vert2,
  rivers,
  logical1 = NULL,
  logical2 = NULL,
  ID1 = NULL,
  ID2 = NULL,
  flowconnected = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of directions (character) with rows and columns labeled by corresponding values of ID. See riverdirection for additional information.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdirection

Examples

data(Gulk)

streamlocs.seg <- c(1,8,11)
streamlocs.vert <- c(50,70,90)
streamlocs.ID <- c("A","B","C")

fish.seg <- c(1,4,9,12,14)
fish.vert <- c(10,11,12,13,14)
fish.ID <- c("fish1","fish2","fish3","fish4","fish5")

Gulk <- setmouth(seg=1, vert=1, rivers=Gulk)

riverdirectiontofrom(seg1=streamlocs.seg, vert1=streamlocs.vert,
  seg2=fish.seg, vert2=fish.vert, rivers=Gulk,
  ID1=streamlocs.ID, ID2=fish.ID)

logi1 <- streamlocs.ID=="B" | streamlocs.ID=="C"
logi2 <- fish.ID!="fish3"

riverdirectiontofrom(seg1=streamlocs.seg, vert1=streamlocs.vert,
  seg2=fish.seg, vert2=fish.vert, rivers=Gulk, logical1=logi1,
  logical2=logi2, ID1=streamlocs.ID, ID2=fish.ID)

River Distance

Description

Calculates the total river network distance between two points on the river network, given in river locations (segment and vertex).

Usage

riverdistance(
  startseg = NULL,
  endseg = NULL,
  startvert,
  endvert,
  rivers,
  path = NULL,
  map = FALSE,
  add = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

Total route distance, in the units of the coordinate system used (this will likely be meters).

Note

If a distance lookup table ($distlookup) is present in the river network object, accepting NULL will bypass route detection and return distance automatically, the fastest algorithm of all. This is done automatically in buildsegroutes, but can be called directly using buildlookup.

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

Examples

data(Gulk)
riverdistance(startseg=6, endseg=14, startvert=100, endvert=200, rivers=Gulk)
riverdistance(startvert=100, endvert=200, path=c(6,3,4,10,11,14), rivers=Gulk)
riverdistance(startseg=6, endseg=14, startvert=100, endvert=200, rivers=Gulk, map=TRUE)
      
# speed comparison: 

data(abstreams)

tstart <- Sys.time()
riverdistance(startseg=120, startvert=10, endseg=131, endvert=10, rivers=abstreams, 
              algorithm="sequential")
Sys.time()- tstart

tstart <- Sys.time()
riverdistance(startseg=120, startvert=10, endseg=131, endvert=10, rivers=abstreams, 
              algorithm="Dijkstra")
Sys.time()- tstart

tstart <- Sys.time()
riverdistance(startseg=120, startvert=10, endseg=131, endvert=10, rivers=abstreams)

# Note: it is not necessary to specify the algorithm here: the distance function
# will automatically select the fastest algorithm unless otherwise specified.
Sys.time()- tstart

Multiple River Distances

Description

Used to calculate a list of possible river distances, in the event of braiding. Calls routelist to detect a list of routes from one river location to another, and uses riverdistance to calculate the distances along those routes. Different routes are detected by randomly reordering the segment numbers of the input river network object, thus changing the internal hierarchy of segment selection.

Usage

riverdistancelist(startseg, endseg, startvert, endvert, rivers, reps = 100)

Arguments

Value

A list with two objects, $routes being a list of detected routes in ascending order by distance, and $distances being the respective distances along the routes detected.

Note

Since this function uses randomization, there is no guarantee that the list of routes will be comprehensive. Larger numbers of reps can be tried, but computation can be slow, particularly in the presence of a complex river network. It may be advantageous to use trimriver to create a smaller, more specific river network object to work with.

Author(s)

Matt Tyers

Examples

data(KilleyW)
plot(x=KilleyW)

Killey.dists <- riverdistancelist(startseg=1, endseg=16, startvert=100, endvert=25,
   rivers=KilleyW)
Killey.dists  # 18 routes are detected.

# mapping the shortest route detected... 
riverdistance(startvert=100, endvert=25, path=Killey.dists$routes[[1]], rivers=KilleyW, map=TRUE)

# mapping the shortest longest detected... 
riverdistance(startvert=100, endvert=25, path=Killey.dists$routes[[18]], rivers=KilleyW, map=TRUE)

River Distance Matrix

Description

Returns a matrix of distances between every point and every other point of given river locations (segment and vertex), or of a subset.

Usage

riverdistancemat(
  seg,
  vert,
  rivers,
  logical = NULL,
  ID = NULL,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of distances (numeric) with rows and columns labeled by corresponding values of ID.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdistance

Examples

data(Gulk, fakefish)

logi1 <- (fakefish$flight.date==as.Date("2015-11-25"))

riverdistancemat(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, logical=logi1)

River Distance Matrix of All Observations of an Individual

Description

Returns a matrix of network distances between all observations of one unique fish.

Usage

riverdistancematbysurvey(
  indiv,
  unique,
  survey,
  seg,
  vert,
  rivers,
  full = TRUE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of distances (numeric), with rows and columns defined by survey.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdistance

Examples

data(Gulk, fakefish)
riverdistancematbysurvey(indiv=1, unique=fakefish$fish.id, survey=fakefish$flight,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
     
riverdistancematbysurvey(indiv=1, unique=fakefish$fish.id, survey=fakefish$flight,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, full=FALSE)

River Distance Between Sequential Observations

Description

Returns a matrix of distances traveled by unique fish, between sequential surveys. A plotting method is also provided for the output; see plotseq

Usage

riverdistanceseq(
  unique,
  survey,
  seg,
  vert,
  rivers,
  logical = NULL,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A data frame of distances (numeric), with rows defined by unique fish and columns defined by observation increment (1 to 2, 2 to 3, etc.)

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdistance, plotseq

Examples

data(Gulk, fakefish)
riverdistanceseq(unique=fakefish$fish.id, survey=fakefish$flight,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
     
seqbysurvey <- riverdistanceseq(unique=fakefish$fish.id, survey=fakefish$flight.date,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
seqbysurvey
plotseq(seqbysurvey)

River Distance Matrix between Two Datasets

Description

Returns a matrix of distances between each river location in two datasets, with one expressed as rows and the other expressed as columns.

Usage

riverdistancetofrom(
  seg1,
  vert1,
  seg2,
  vert2,
  rivers,
  logical1 = NULL,
  logical2 = NULL,
  ID1 = NULL,
  ID2 = NULL,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of distances (numeric) with rows and columns labeled by corresponding values of ID.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

riverdistance

Examples

data(Gulk)

streamlocs.seg <- c(1,8,11)
streamlocs.vert <- c(50,70,90)
streamlocs.ID <- c("A","B","C")

fish.seg <- c(1,4,9,12,14)
fish.vert <- c(10,11,12,13,14)
fish.ID <- c("fish1","fish2","fish3","fish4","fish5")

riverdistancetofrom(seg1=streamlocs.seg, vert1=streamlocs.vert,
  seg2=fish.seg, vert2=fish.vert, rivers=Gulk, ID1=streamlocs.ID, ID2=fish.ID)

logi1 <- streamlocs.ID=="B" | streamlocs.ID=="C"
logi2 <- fish.ID!="fish3"

riverdistancetofrom(seg1=streamlocs.seg, vert1=streamlocs.vert,
  seg2=fish.seg, vert2=fish.vert, rivers=Gulk, logical1=logi1, logical2=logi2,
  ID1=streamlocs.ID, ID2=fish.ID)

The "rivernetwork" Class

Description

A class that holds spatial coordinates for river networks, as well as network topology and attributes.

Details

Created by line2network from an input line shapefile. Contains all information for network distance calculation, plotting, etc. in the 'riverdist' package.

Plotting methods are described in plot.rivernetwork.

Elements

sf:

Object of class "sf" from package 'sf'; see sf. This is the original object as read by read_sf, and is preserved to maintain plotting capability.

sf_current:

Object of class "sf" from package 'sf'; see sf. This is an updated sf object generated from the coordinates in the 'lines' element, incorporating any changes to geometry. Any corresponding data will be dropped.

lines:

Object of class "list". Each list element is a matrix of XY coordinates of the vertices of a single river segment.

connections:

Object of class "matrix", with "numeric" elements. Defined as a square matrix, with elements describing the type of connection detected between line segments.

• A value of 1 in element [i,j] indicates that the beginning of segment i is connected to the beginning of segment j.

• A value of 2 in element [i,j] indicates that the beginning of segment i is connected to the end of segment j.

• A value of 3 in element [i,j] indicates that the end of segment i is connected to the beginning of segment j.

• A value of 4 in element [i,j] indicates that the end of segment i is connected to the end of segment j.

• A value of 5 in element [i,j] indicates that segments i and j are connected at both beginning and end.

• A value of 6 in element [i,j] indicates that the beginning of segment i is connected to the end of segment j, and the end of segment i is connected to the beginning of segment j.

• A value of NA in element [i,j] indicates that segments i and j are not connected.

lengths:

Vector of class "numeric". Defined as the calculated total lengths of each river segment.

names:

Vector of class "character". Defined as the names of each river segment.

mouth:

Object of class "list", with two elements. Element mouth.seg gives the segment number of the mouth (lowest point) of the river network, and mouth.vert gives the vertex number.

sequenced:

"logical": has value of TRUE if line vertices have been stored in upstream sequence using sequenceverts.

tolerance:

"numeric": the spatial tolerance that was used in determining river segment endpoint connectivity; see line2network, splitsegments.

units:

"character": the spatial units detected from the input shapefile.

braided:

"logical": Has value of TRUE if checkbraidedTF has detected braiding, FALSE if no braiding has been detected, and NA if braiding has not yet been checked.

cumuldist:

List of class "numeric": Each element is a vector of cumulative distances along each river segment, beginning with 0.

segroutes:

Object of class "list", with each element defined as a vector of class "numeric", describing the route from the mouth segment to the specific segment. This element only exists if buildsegroutes has been run, and can greatly speed up route and distance calculation.

distlookup:

List of three matrices, of class "numeric" or "logical". Element [i,j] of each matrix corresponds to the route between segment i and j. The distlookup$middist matrix gives the total distance of the "middle" of each route (between the starting and ending segments"), and the distlookup$starttop and distlookup$endtop matrices have value TRUE, FALSE, or NA if the segments at the beginning or end of the route are connected to the rest of the route at the top of the coordinate matrix, bottom of the coordinate matrix, or if the route is contained to just one segment, respectively.

Author(s)

Matt Tyers

Draw Points from River Locations

Description

Adds points to an active plot. Works like points but with river locations (segments and vertices) rather than xy coordinates.

Usage

riverpoints(seg, vert, rivers, pch = 1, col = 1, jitter = 0, ...)

Arguments

Author(s)

Matt Tyers

Examples

data(fakefish,Gulk)

plot(x=Gulk, xlim=c(862000,882000), ylim=c(6978000,6993000))
points(x=fakefish$x, y=fakefish$y, pch=16, col=2)
riverpoints(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, pch=15, col=4)

plot(x=Gulk, empty=TRUE)
with(fakefish, riverpoints(seg=seg, vert=vert, rivers=Gulk, 
       pch=16, col=flight, jitter=1000))

Detect Multiple Routes

Description

Called internally within riverdistancelist. Detects all possible routes from one river network segment to another, in the event of braiding.

Usage

routelist(startseg, endseg, rivers, reps = 100)

Arguments

Value

A list of vectors, each describing a route in segment numbers.

Note

The previous version of this function returned many possible routes using randomization - this algorithm now computes all possible routes.

Author(s)

Matt Tyers

Examples

data(KilleyW)
plot(x=KilleyW)

routelist(startseg=1, endseg=16, rivers=KilleyW)

Convert River Locations to XY coordinates

Description

This function is almost the reverse of xy2segvert, and returns a data frame of the XY spatial coordinates corresponding to vectors of segment and vertex. It should be noted that this only returns the spatial coordinates from the river network itself, and will not necessarily correspond to the original set of point data.

Usage

segvert2xy(seg, vert, rivers)

Arguments

Value

A data frame of XY coordinates, given as $snap_x and $snap_y..

Author(s)

Matt Tyers

See Also

xy2segvert, pointshp2segvert

Examples

data(Gulk,fakefish)
head(fakefish)

xy_from_segvert <- segvert2xy(seg=fakefish$seg, vert=fakefish$vert, 
                   rivers=Gulk)
head(xy_from_segvert)

plot(x=Gulk, xlim=c(862000,882000), ylim=c(6978000,6993000))
points(x=fakefish$x, y=fakefish$y, pch=16, col=2)

points(x=xy_from_segvert$snap_x, y=xy_from_segvert$snap_y, pch=15, col=4)

Store Vertices in Ascending Sequence

Description

Rearranges the vertices of a river network object so that vertices are stored sequentially moving up river for all segments (coordinates [1,] are the bottom of each segment).

Usage

sequenceverts(rivers)

Arguments

Value

A new river network object (see rivernetwork)

Note

Even without calling sequenceverts, the vertices will be stored sequentially - either moving up river or down for a given segment. What sequenceverts() adds is a standardized direction.

Currently, no function in package 'riverdist' requires the vertices to be stored sequentially.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Gulk)
Gulk <- setmouth(seg=1, vert=1, rivers=Gulk)
str(Gulk)

Gulk.dir <- sequenceverts(rivers=Gulk)
str(Gulk.dir)

Specify the Segment and Vertex of the Mouth of a River Network Object.

Description

Provides a user-friendly way of specifying the segment and vertex of the mouth (lowest point) of a river network object.

Usage

setmouth(seg, vert, rivers)

Arguments

Value

A new river network object (see rivernetwork)

Note

The mouth segment and vertex can also be specified using direct assignment to the $mouth$seg and $mouth$vert components of the river network object.

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Gulk)

# say we know that segment 1 is the lowest segment in this river network, but we don't know 
# which end is the mouth.
showends(seg=1, rivers=Gulk)

# this means that the mouth is row 1, so we can specify this:
Gulk <- setmouth(seg=1, vert=1, rivers=Gulk)

Identify Vertex Coordinates of Segment Endpoints

Description

Identifies the vertex coordinates (row numbers) of the endpoints of a given segment. The main purpose is determining which of the endpoints is the mouth (or lowest point) of the river system.

Usage

showends(seg, rivers)

Arguments

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

Examples

data(Gulk)

# say we know that segment 1 is the lowest segment in this river network, but we don't know 
# which end is the mouth.
showends(seg=1, rivers=Gulk)

# this means that the mouth is row 1, so we can specify this:
Gulk <- setmouth(seg=1, vert=1, rivers=Gulk)

Dataset: Smallset

Description

A small set of observations of fakefish on the Gulkana River and its tributaries.

Usage

data(smallset)

Format

A data frame

Details

• x. X-coordinate of observation (Alaska Albers Equal Area). Note that the locations do not align with the river network object.

• y. Y-coordinate of observation

• seg. River segment

• vert. River vertex

• fish.id. Numeric identifier for each fish (individual fish were observed more than once)

• flight. Numeric identifier for each telemetry flight

See Also

Gulk

Split a Segment at a Specified Vertex

Description

Splits a segment at a specified vertex, creating two new segments.

Usage

splitsegmentat(seg, vert, rivers)

Arguments

Value

A new, updated river network object

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Gulk)
plot(x=Gulk)

Gulk2 <- splitsegmentat(seg=1, vert=400, rivers=Gulk)
plot(x=Gulk2)

Split Segments by Endpoint Proximity

Description

Detects cases in which segments should be split to establish appropriate topology, and splits them. Specifically, it looks for segment endpoints intersecting (or within a tolerance of) another segment. It then splits the intersected segment at the point where the endpoint of the other segment breaks it.

Usage

splitsegments(
  rivers,
  tolerance = NULL,
  splitthese = NULL,
  splitthemat = NULL,
  one2one = FALSE,
  append = FALSE
)

Arguments

Value

A new, updated river network object

Note

This function is called within cleanup, which is recommended in most cases.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Koyukuk1)
topologydots(rivers=Koyukuk1)
# Segments 7, 8, 13, and 16 need to be split so topologies will work.  
# Since endpoints are not in the same place, they are not detected as 
# being connected.
plot(x=Koyukuk1)

Koyukuk1split <- splitsegments(rivers=Koyukuk1)
topologydots(rivers=Koyukuk1split)
plot(x=Koyukuk1split)

# if only segment 17 were to be split in three places
plot(x=splitsegments(rivers=Koyukuk1, splitthese=c(7,7,7),
        splitthemat=c(14,5,12)))
        
# if only segment 16 were to be split, showing behavior of append=
plot(x=splitsegments(rivers=Koyukuk1, splitthese=c(7,7,7),
        splitthemat=c(14,5,12), append=TRUE))

Check Connectivity of a River Network Object

Description

Produces a graphical check of the connectivity of a river network object. It produces a plot of the river network object, and overlays red dots at non-connected endpoints and green dots at connected endpoints.

Usage

topologydots(rivers, add = FALSE, ...)

Arguments

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Gulk)
topologydots(rivers=Gulk)

Trim a River Network Object to Specified Segments

Description

Removes line segments from a river network object. User can specify which segments to remove (trim) or which segments to keep (trimto).

Usage

trimriver(trim = NULL, trimto = NULL, rivers)

Arguments

Value

A new river network object

Note

Specifying segments in both trim and trimto arguments will result in an error.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Kenai1)
plot(x=Kenai1)

Kenai1.trim <- trimriver(trim=c(46,32,115,174,169,114,124,142,80), rivers=Kenai1)
plot(x=Kenai1.trim)
 
Kenai1.trim.2 <- trimriver(trimto=c(20,57,118,183,45,162,39,98,19), rivers=Kenai1)
plot(x=Kenai1.trim.2)

Trim a River Network to a Set of X-Y Coordinates

Description

Removes line segments from a river network object that are not adjacent to a set of point data, given in X-Y coordinates.

Usage

trimtopoints(x, y, rivers, method = "snap", dist = NULL)

Arguments

Value

A new river network object (see rivernetwork)

Note

If method=="buffer", only distances to segment endpoints and midpoints are checked, and still only whole segments are removed.

Author(s)

Matt Tyers

See Also

line2network

Examples

data(Koyukuk2)
x <- c(139241.0, 139416.1, 124600.1, 122226.8)
y <- c(1917577, 1913864, 1898723, 1898792)

plot(x=Koyukuk2)
points(x, y, pch=15, col=4)
legend(par("usr")[1], par("usr")[4], legend="points to buffer around", pch=15, col=4, cex=.6)

Koyukuk2.buf1 <- trimtopoints(x, y, rivers=Koyukuk2, method="snap")
plot(x=Koyukuk2.buf1)
points(x, y, pch=15, col=4)

Koyukuk2.buf2 <- trimtopoints(x, y, rivers=Koyukuk2, method="snaproute")
plot(x=Koyukuk2.buf2)
points(x, y, pch=15, col=4)

Koyukuk2.buf3 <- trimtopoints(x, y, rivers=Koyukuk2, method="buffer", dist=1000)
plot(x=Koyukuk2.buf3)
points(x, y, pch=15, col=4)

Upstream River Distance

Description

Calculates river network distances as +/-, defined as upriver/downriver.

Specifying net=TRUE will compute net upriver distance (3 river km down a tributary and then 15 river km up the mainstem will mean 12 rkm net. Otherwise the function will return 18 rkm upriver travel.)

The mouth (lowest point) segment and vertex must be specified (see setmouth).

Usage

upstream(
  startseg,
  endseg,
  startvert,
  endvert,
  rivers,
  flowconnected = FALSE,
  net = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

Upstream distance (numeric). Returns NA if flowconnected has value TRUE and the two segments are not flow-connected.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

setmouth

Examples

data(Gulk)

# Mouth must be specified
Gulk$mouth$mouth.seg <- 1
Gulk$mouth$mouth.vert <- 1

plot(x=Gulk)
riverpoints(seg=c(6,4), vert=c(140,140), pch=16, col=2, rivers=Gulk)
upstream(startseg=6, endseg=4, startvert=140, endvert=40, rivers=Gulk, net=TRUE)
upstream(startseg=6, endseg=4, startvert=140, endvert=40, rivers=Gulk, net=FALSE)
upstream(startseg=6, endseg=4, startvert=140, endvert=40, rivers=Gulk, flowconnected=TRUE)

Upstream Distance Matrix

Description

Returns a matrix of upstream distance between every point and every other point of given river locations (segment and vertex), or of a subset. The mouth (lowest point) segment and vertex must be specified (see setmouth).

Usage

upstreammat(
  seg,
  vert,
  rivers,
  logical = NULL,
  ID = NULL,
  flowconnected = FALSE,
  net = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of upstream distances (numeric) with rows and columns labeled by corresponding values of ID. See upstream for additional information.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

upstream

Examples

data(Gulk, fakefish)

# Mouth must be specified
Gulk$mouth$mouth.seg <- 1
Gulk$mouth$mouth.vert <- 1

logi1 <- (fakefish$flight.date==as.Date("2015-11-25"))

upstreammat(seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, logical=logi1)

Upstream Distance Matrix of All Observations of an Individual

Description

Returns a matrix of upstream travel distance between all observations of one unique fish.

Usage

upstreammatbysurvey(
  indiv,
  unique,
  survey,
  seg,
  vert,
  rivers,
  full = TRUE,
  flowconnected = FALSE,
  net = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of upstream distances (numeric), with rows and columns defined by survey. In the resulting matrix, the element with the row identified as A and column identified as B is defined as the upstream distance traveled from survey A to survey B. Therefore, it is likely that only the upper triangle of the matrix will be of interest.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

upstream

Examples

data(Gulk, fakefish)
upstreammatbysurvey(indiv=1, unique=fakefish$fish.id, survey=fakefish$flight,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk)
     
upstreammatbysurvey(indiv=1, unique=fakefish$fish.id, survey=fakefish$flight,
      seg=fakefish$seg, vert=fakefish$vert, rivers=Gulk, full=FALSE)

Upstream Distance Between Sequential Observations

Description

Returns a matrix of distance with direction by unique fish between sequential surveys. The mouth (lowest point) segment and vertex must be specified (see setmouth). A plotting method is provided for the output; see plotseq.

Usage

upstreamseq(
  unique,
  survey,
  seg,
  vert,
  rivers,
  logical = NULL,
  flowconnected = FALSE,
  net = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A data frame of upstream distances (numeric), with rows defined by unique fish and columns defined by observation increment (1 to 2, 2 to 3, etc.) See upstream for additional information.

Note

Returns either net upstream distance (net=TRUE) or total distance (net=FALSE, default). See upstream.

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

upstream, plotseq

Examples

data(Gulk, fakefish)

# Mouth must be specified
Gulk$mouth$mouth.seg <- 1
Gulk$mouth$mouth.vert <- 1

upstreamseq(unique=fakefish$fish.id, survey=fakefish$flight, seg=fakefish$seg,
      vert=fakefish$vert, rivers=Gulk)

seqbysurvey <- upstreamseq(unique=fakefish$fish.id, survey=fakefish$flight.date, seg=fakefish$seg,
      vert=fakefish$vert, rivers=Gulk)
seqbysurvey
plotseq(seqbysurvey)

Upstream Distance Matrix between Two Datasets

Description

Returns a matrix of upstream distances between each river location in two datasets, with one expressed as rows and the other expressed as columns.

Usage

upstreamtofrom(
  seg1,
  vert1,
  seg2,
  vert2,
  rivers,
  logical1 = NULL,
  logical2 = NULL,
  ID1 = NULL,
  ID2 = NULL,
  net = FALSE,
  flowconnected = FALSE,
  stopiferror = TRUE,
  algorithm = NULL
)

Arguments

Value

A matrix of upstream distances (numeric) with rows and columns labeled by corresponding values of ID. See upstream for additional information.

Note

Building routes from the river mouth to each river network segment and/or distance lookup tables will greatly reduce computation time (see buildsegroutes).

Author(s)

Matt Tyers

See Also

upstream

Examples

data(Gulk)

streamlocs.seg <- c(1,8,11)
streamlocs.vert <- c(50,70,90)
streamlocs.ID <- c("A","B","C")

fish.seg <- c(1,4,9,12,14)
fish.vert <- c(10,11,12,13,14)
fish.ID <- c("fish1","fish2","fish3","fish4","fish5")

Gulk <- setmouth(seg=1, vert=1, rivers=Gulk)

upstreamtofrom(seg1=streamlocs.seg, vert1=streamlocs.vert,
  seg2=fish.seg, vert2=fish.vert, rivers=Gulk,
  ID1=streamlocs.ID, ID2=fish.ID)

logi1 <- streamlocs.ID=="B" | streamlocs.ID=="C"
logi2 <- fish.ID!="fish3"

upstreamtofrom(seg1=streamlocs.seg, vert1=streamlocs.vert,
  seg2=fish.seg, vert2=fish.vert, rivers=Gulk, logical1=logi1,
  logical2=logi2, ID1=streamlocs.ID, ID2=fish.ID)

Check Which Segments are Connected to a Given Segment.

Description

Returns which segments are connected to a specified segment within a river network. It may be useful for error checking.

Usage

whoconnected(seg, rivers)

Arguments

Value

A vector of segment numbers

Author(s)

Matt Tyers

Examples

data(Gulk)
plot(Gulk)
whoconnected(seg=4, rivers=Gulk)

Convert XY Coordinates to River Locations

Description

This function determines the closest vertex in the river network to each point of XY data and returns a list of river locations, defined as segment numbers and vertex numbers.

Usage

xy2segvert(x, y, rivers)

Arguments

Value

A data frame of river locations, with segment numbers in $seg, vertex numbers in $vert, and the snapping distance for each point in $snapdist. Two additional columns are $snap_x and $snap_y, which give the x- and y-coordinates snapped to the river network.

Note

Conversion to river locations is only valid if the input XY coordinates and river network are in the same projected coordinate system. Point data in geographic coordinates can be projected using sf_project in package 'sf', and an example is shown below.

Author(s)

Matt Tyers

See Also

pointshp2segvert, segvert2xy

Examples

data(Gulk,fakefish)
head(fakefish)

fakefish.riv <- xy2segvert(x=fakefish$x, y=fakefish$y, rivers=Gulk)
head(fakefish.riv)

plot(x=Gulk, xlim=c(862000,882000), ylim=c(6978000,6993000))
points(fakefish$x, fakefish$y, pch=16, col=2)
riverpoints(seg=fakefish.riv$seg, vert=fakefish.riv$vert, rivers=Gulk, pch=15, col=4)


## converting a matrix of points stored in long-lat to Alaska Albers Equal Area:
data(line98, Kenai1)
head(line98)  # note that coordinates are stored in long-lat, NOT lat-long

line98albers <- sf::sf_project(pts=line98, to="+proj=aea +lat_1=55 +lat_2=65 
    +lat_0=50 +lon_0=-154 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs 
    +ellps=GRS80")
head(line98albers)

zoomtoseg(seg=c(162,19), rivers=Kenai1)
points(line98albers)

Zoom to segment

Description

Calls plot.rivernetwork and automatically zooms to a specified segment or vector of segments. Not intended for any real mapping - just investigating and error checking.

Usage

zoomtoseg(seg, rivers, ...)

Arguments

Author(s)

Matt Tyers

Examples

data(Kenai3)
plot(x=Kenai3)

# checking out a particularly messy region...
zoomtoseg(c(110,63), rivers=Kenai3)