Title:	Spatial Interpolation by Inverse Path Distance Weighting
Description:	Functions are provided to interpolate geo-referenced point data via Inverse Path Distance Weighting. Useful for coastal marine applications where barriers in the landscape preclude interpolation with Euclidean distances.
Version:	2.0-0
URL:	https://github.com/jsta/ipdw
BugReports:	https://github.com/jsta/ipdw/issues
Depends:	R (≥ 3.0.2),gdistance
Imports:	sf,raster,methods
Suggests:	gstat,gdata,spatstat, testthat, knitr, rmarkdown
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Encoding:	UTF-8
RoxygenNote:	7.2.3
VignetteBuilder:	knitr
NeedsCompilation:	no
Packaged:	2022-12-28 19:59:35 UTC; jemma
Author:	Jemma Stachelek [aut, cre]
Maintainer:	Jemma Stachelek <jemma.stachelek@gmail.com>
Repository:	CRAN
Date/Publication:	2023-01-05 17:50:05 UTC

Generate a cost Raster

Description

Generate a cost raster from an object of class sf with point or polygon geometries

Usage

costrasterGen(xymat, pols, extent = "polys", projstr, resolution = 1)

Arguments

Details

Ensure that the projection of the xymat coordinates and pols match. If they do not match use the st_transform command.

Value

RasterLayer

See Also

rasterize

Examples

## Not run: 
library(sf)
Sr1 <- st_polygon(list(cbind(c(0, 0, 1, 1, 0), c(0, 12, 12, 0, 0))))
Sr4 <- st_polygon(list(cbind(c(9, 9, 10, 10, 9), c(0, 12, 12, 0, 0))))
Sr2 <- st_polygon(list(cbind(c(1, 1, 9, 9, 1), c(11, 12, 12, 11, 11))))
Sr3 <- st_polygon(list(cbind(c(1, 1, 9, 9, 1), c(0, 1, 1, 0, 0))))
Sr5 <- st_polygon(list(cbind(c(4, 4, 5, 5, 4), c(4, 8, 8, 4, 4))))
pols <- st_as_sf(st_sfc(Sr1, Sr2, Sr3, Sr4, Sr5,
  crs = "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))

# using a matrix object
xymat <- matrix(3, 3, nrow = 1, ncol = 2)
costras <- costrasterGen(xymat, pols, projstr = NULL)

# plotting
plot(costras)
points(xymat)

## End(Not run)

Generate interpolation error stats from validation datasets

Description

Generate error statistics from validation point datasets overlaid on a raster surface

Usage

errorGen(
  finalraster,
  validation.sf_ob,
  validation.data,
  plot = FALSE,
  title = ""
)

Arguments

Value

List of error statistics

Examples

library(sf)
validation.data <- data.frame(rnorm(10, mean = 0.2, sd = 1))
names(validation.data) <- c("validation")
validation.sf_ob <- validation.data
validation.data <- as.numeric(unlist(validation.data))
xy <- data.frame(x = c(0:9), y = rep(1, 10))
validation.sf_ob <- st_as_sf(cbind(validation.sf_ob, xy), coords = c("x", "y"))

m <- matrix(NA, 1, 10)
out.ras <- raster(m, xmn = 0, xmx = ncol(m), ymn = 0, ymx = nrow(m))
out.ras[] <- validation.data + rnorm(ncell(out.ras), mean = 0.01, sd = 0.2)

valid.stats <- errorGen(out.ras, validation.sf_ob, validation.data, plot = TRUE,
  title = "Validation Plot")
valid.stats

Inverse Path Distance Weighting

Description

Interpolate geo-referenced point data using inverse path distance weighting.

Usage

ipdw(
  sf_ob,
  costras,
  range,
  paramlist,
  overlapped = FALSE,
  yearmon = "default",
  removefile = TRUE,
  step = 16,
  dist_power = 1,
  trim_rstack = FALSE
)

Arguments

Details

This is a high level function that interpolates an sf object with point geometries in a single pass.

Points must be located within a single contiguous area. The presence of "landlocked" points will cause errors. It may be necessary to increase the value assigned to land areas when using a large range value in combination with a large sized cost rasters (grain x extent). In these cases, the value of land areas should be increased to ensure that it is always greater than the maximum accumulated cost path distance of any given geo-referenced point.

Value

RasterLayer

Examples

# see vignette

Inverse Distance Weighting with custom distances

Description

This function takes a rasterstack of pathdistances and generates surfaces by weighting parameter values by these distances

Usage

ipdwInterp(
  sf_ob,
  rstack,
  paramlist,
  overlapped = FALSE,
  yearmon = "default",
  removefile = TRUE,
  dist_power = 1,
  trim_rstack = FALSE
)

Arguments

Details

Under the hood, this function evaluates:

V = \frac{\sum\limits_{i=1}^n v_i \frac{1}{d_i^p}}{\sum\limits_{i=1}^n \frac{1}{d_i^p}}

where d is the distance between prediction and measurement points, v_i is the measured parameter value, and p is a power parameter.

Value

RasterLayer

Examples

library(sf)
sf_ob <- data.frame(rnorm(2))
xy    <- data.frame(x = c(4, 2), y = c(8, 4))
sf_ob <- st_as_sf(cbind(sf_ob, xy), coords = c("x", "y"))

m <- matrix(NA, 10, 10)
costras <- raster(m, xmn = 0, xmx = ncol(m), ymn = 0, ymx = nrow(m))

# introduce spatial gradient
costras[] <- runif(ncell(costras), min = 1, max = 10)
for (i in 1:nrow(costras)) {
  costras[i, ] <- costras[i, ] + i
  costras[, i] <- costras[, i] + i
}

rstack <- pathdistGen(sf_ob, costras, 100, progressbar = FALSE)
final.raster <- ipdwInterp(sf_ob, rstack, paramlist = c("rnorm.2."), overlapped = TRUE)
plot(final.raster)
plot(sf_ob, add = TRUE)

Generate a stack of path distance raster objects

Description

Generate a stack of path accumulated distance raster objects

Usage

pathdistGen(sf_ob, costras, range, yearmon = "default", progressbar = TRUE)

Arguments

Value

RasterStack object of path distances

Examples

library(sf)
sf_ob <- data.frame(rnorm(2))
xy   <- data.frame(x = c(4, 2), y = c(8, 4))
sf_ob <- st_as_sf(cbind(sf_ob, xy), coords = c("x", "y"))

m <- matrix(NA, 10, 10)
costras <- raster(m, xmn = 0, xmx = ncol(m), ymn = 0, ymx = nrow(m))
costras[] <- runif(ncell(costras), min = 1, max = 10)
# introduce spatial gradient
for (i in 1:nrow(costras)) {
  costras[i, ] <- costras[i, ] + i
  costras[, i] <- costras[, i] + i
}

rstack <- pathdistGen(sf_ob, costras, 100, progressbar = FALSE)

Remove NA points features and drop corresponding raster stack layers

Description

Remove NA points features and drop corresponding raster stack layers

Usage

rm_na_pointslayers(param_name, sf_ob, rstack)

Arguments