Help for package spcosa

Type:

Package

Title:

Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata

Version:

0.4-4

Date:

2025-06-29

Description:

Spatial coverage sampling and random sampling from compact geographical strata created by k-means. See Walvoort et al. (2010) <doi:10.1016/j.cageo.2010.04.005> for details.

Depends:

R (≥ 4.1.0), rJava (≥ 1.0-0), methods, utils

Imports:

sp (≥ 1.4-6), ggplot2 (≥ 3.3.0)

Suggests:

grid, RUnit (≥ 0.4.32), sf (≥ 1.0-12), knitr (≥ 1.36), rmarkdown (≥ 2.11)

SystemRequirements:

Java (>= 6)

License:

GPL (≥ 3)

URL:

https://git.wur.nl/Walvo001/spcosa

Collate:

class_Stratification.R class_CompactStratification.R class_CompactStratificationEqualArea.R class_CompactStratificationPriorPoints.R class_SamplingPattern.R class_SamplingPatternPurposive.R class_SamplingPatternCentroids.R class_SamplingPatternPriorPoints.R class_SamplingPatternRandom.R class_SamplingPatternRandomSamplingUnits.R class_SamplingPatternRandomComposite.R class_Statistic.R class_SpatialMean.R class_SamplingVariance.R class_StandardError.R class_SpatialVariance.R class_SpatialCumulativeDistributionFunction.R generic_estimate.R generic_getArea.R generic_getRelativeArea.R generic_getAttributes.R generic_getCellSize.R generic_getCentroid.R generic_getSampleSize.R generic_getNumberOfCells.R generic_getNumberOfStrata.R generic_getObjectiveFunctionValue.R generic_stratify.R generic_plot.R methods_estimate.R method_getArea-CompactStratification.R method_getRelativeArea-CompactStratification.R method_getCellSize-CompactStratification.R method_getCellSize-SpatialPixels.R method_getCentroid-CompactStratification.R method_getNumberOfCells-CompactStratification.R method_getNumberOfStrata-CompactStratification.R method_getObjectiveFunctionValue-CompactStratification.R method_getSampleSize-SamplingPattern.R method_getSampleSize-SamplingPatternRandomComposite.R method_initialize-CompactStratification.R method_initialize-CompactStratificationPriorPoints.R method_stratify-SpatialGrid.R method_stratify-SpatialPixels.R method_stratify-SpatialPolygons.R methods_plot.R methods_spsample.R methods_setAs.R method_show-Stratification.R method_show-SamplingPattern.R method_show-Statistic.R onLoad.R onAttach.R

NeedsCompilation:

Packaged:

2025-06-29 21:18:11 UTC; dennis

Author:

Dennis Walvoort

[aut, cre, cph], Dick Brus

[aut, cph], Jaap de Gruijter [aut, cph]

Maintainer:

Dennis Walvoort <dennis.Walvoort@wur.nl>

Repository:

CRAN

Date/Publication:

2025-06-29 22:10:02 UTC

Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata

Description

Algorithms for spatial coverage sampling and for random sampling from compact geographical strata based on k-means.

Details

The spcosa-package provides algorithms for spatial coverage sampling and for random sampling from compact geographical strata based on k-means (see de Gruijter et al., 2006, Walvoort et al., 2010, and kmeans). S4-classes and methods are available for spatial coverage sampling, random sampling from compact geographical strata, and stratified simple random sampling for composites. In case of spatial coverage sampling, existing sampling points may be taken into account. See the package vignette for more information and examples.

Note

In order to get the spcosa-package running, make sure that a recent version of Java is installed.

Author(s)

D.J.J. Walvoort, D.J. Brus, J.J. de Gruijter,

Maintainer: Dennis Walvoort dennis.walvoort@wur.nl

References

Brus, D. J., Spatjens, L. E. E. M., and de Gruijter, J. J. (1999). A sampling scheme for estimating the mean extractable phosphorus concentration of fields for environmental regulation. Geoderma 89:129-148

de Gruijter, J. J., Brus, D. J., Bierkens, M. F. P., and Knotters, M. (2006). Sampling for Natural Resource Monitoring Berlin: Springer-Verlag.

Walvoort, D., Brus, D. and de Gruijter, J. (2009). Spatial Coverage Sampling on Various Spatial Scales. Pedometron 26:20-22

Walvoort, D. J. J., Brus, D. J. and de Gruijter, J. J. (2010). An R package for spatial coverage sampling and random sampling from compact geographical strata by k-means. Computers & Geosciences 36: 1261-1267 (doi:10.1016/j.cageo.2010.04.005)

Class "CompactStratification"

Description

A class for storing a stratification with compact strata.

Objects from the Class

Objects can be created by calls of the form new("CompactStratification", cells, stratumId, centroids, mssd). However, objects are usually created by calling stratify.

Slots

cells:: Object of class "sp::SpatialPixels", representing the area to be partitioned.
stratumId:: Object of class "integer", indicating to which stratum each cell in cells belong.
centroids:: Object of class "sp::SpatialPoints", representing the centers of gravity of each stratum.
mssd:: Object of class "numeric", representing the mean squared shortest distance.

Extends

Class "Stratification", directly.

Methods

coerce: signature(from = "CompactStratification", to = "data.frame"): coerces to "data.frame".
coerce: signature(from = "CompactStratification", to = "SpatialPixels"): coerces to "SpatialPixels".
coerce: signature(from = "CompactStratification", to = "SpatialPixelsDataFrame"): coerces to "sp::SpatialPixelsDataFrame".
estimate: signature(statistic = "SamplingVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the sampling variance. See "SamplingVariance" for more details.
estimate: signature(statistic = "SpatialCumulativeDistributionFunction", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial cumulative distribution function (SCDF). See "SpatialCumulativeDistributionFunction" for more details.
estimate: signature(statistic = "SpatialMean", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial mean. See "SpatialMean" for more details.
estimate: signature(statistic = "SpatialVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial variance. See "SpatialVariance" for more details.
estimate: signature(statistic = "StandardError", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the standard error of the spatial mean. See "StandardError" for more details.
estimate: signature(statistic = "character", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates statistic, one of spatial mean, spatial variance, SCDF, sampling variance, or standard error.
getArea: signature(object = "CompactStratification"): returns the area of each stratum.
getCentroid: signature(object = "CompactStratification"): returns the center of gravity of each stratum.
getNumberOfStrata: signature(object = "CompactStratification"): returns the number of strata.
getObjectiveFunctionValue: signature(object = "CompactStratification"): extracts the mean squared shortest distance.
getRelativeArea: signature(object = "CompactStratification"): returns the relative area of each stratum. The sum of the relative areas equals one.
plot: signature(x = "CompactStratification", y = "missing"): plots stratification x.
plot: signature(x = "CompactStratification", y = "SamplingPattern"): plots sampling pattern y on top of stratification x.
plot: signature(x = "CompactStratification", y = "SamplingPatternPriorPoints"): plots sampling pattern y on top of stratification x.
plot: signature(x = "CompactStratification", y = "SamplingPatternRandomComposite"): plots sampling pattern y on top of stratification x.
spsample: signature(x = "CompactStratification", n = "missing", type = "missing"): returns the centers of gravity of each stratum.
spsample: signature(x = "CompactStratification", n = "numeric", type = "missing"): randomly selects n sampling points in each stratum.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "CompactStratificationEqualArea"

Description

A class for storing a stratification with compact strata of equal size.

Objects from the Class

Objects can be created by calls of the form new("CompactStratificationEqualArea", cells, stratumId, centroids, mssd). However, objects are usually created by calling stratify.

Slots

cells:: Object of class "sp::SpatialPixels", representing the area to be partitioned.
stratumId:: Object of class "integer", indicating to which stratum each cell in cells belong.
centroids:: Object of class "sp::SpatialPoints", representing the centers of gravity of each stratum.
mssd:: Object of class "numeric", representing the mean squared shortest distance.

Extends

Class "CompactStratification", directly. Class "Stratification", by class "CompactStratification", distance 2.

Methods

estimate: signature(statistic = "SamplingVariance", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame"): estimates the sampling variance. See "SamplingVariance" for more details.
estimate: signature(statistic = "SpatialMean", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame"): estimates the spatial mean. See "SpatialMean" for more details.
spsample: signature(x = "CompactStratificationEqualArea", n = "missing", type = "missing"): returns the centers of gravity of each stratum.
spsample: signature(x = "CompactStratificationEqualArea", n = "numeric", type = "missing"): randomly selects n sampling points in each stratum.
spsample: signature(x = "CompactStratificationEqualArea", n = "numeric", type = "character"): randomly selects n sampling points in each stratum. if type = "composite", stratified simple random sampling of n composites.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "CompactStratificationPriorPoints"

Description

A class for storing a stratification with compact strata, given prior sampling locations.

Objects from the Class

Objects can be created by calls of the form new("CompactStratificationPriorPoints", cells, stratumId, centroids, mssd, priorPoints). However, objects are usually created by calling stratify.

Slots

priorPoints:: Object of class "sp::SpatialPoints", containing the coordinates of the existing locations.
cells:: Object of class "sp::SpatialPixels", representing the area to be partitioned.
stratumId:: Object of class "integer", indicating to which stratum each cell in cells belong.
centroids:: Object of class"sp::SpatialPoints", representing the centers of gravity of each stratum.
mssd:: Object of class "numeric", representing the mean squared shortest distance.

Extends

Class "CompactStratification", directly. Class "Stratification", by class "CompactStratification", distance 2.

Methods

spsample: signature(x = "CompactStratificationPriorPoints", n = "missing", type = "missing"): returns the centers of gravity of strata without prior points in addition to the prior points.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingPattern"

Description

A class for storing a sampling pattern.

Objects from the Class

Objects can be created by calls of the form new("SamplingPattern", ...). However, objects are usually created by calling spsample.

Slots

sample:: Object of class "sp::SpatialPoints", containing the sampling locations.

Methods

coerce: signature(from = "SamplingPattern", to = "data.frame"): coerces to "data.frame".
coerce: signature(from = "SamplingPattern", to = "SpatialPoints"): coerces to "sp::SpatialPoints".
getSampleSize: signature(object = "SamplingPattern"): returns the sample size.
plot: signature(x = "CompactStratification", y = "SamplingPattern"): plots sampling pattern y on top of stratification x.
plot: signature(x = "SamplingPattern", y = "missing"): plots sampling pattern x.
show: signature(object = "SamplingPattern"): prints object on the output device.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingPatternCentroids"

Description

A class for storing a sampling pattern, where the sampling locations are the centers of gravity of each stratum.

Objects from the Class

Objects can be created by calls of the form new("SamplingPatternCentroids", ...). However, objects are usually created by calling spsample.

Slots

sample:: Object of class "sp::SpatialPoints", containing the sampling locations

Extends

Class "SamplingPatternPurposive", directly. Class "SamplingPattern", by class "SamplingPatternPurposive", distance 2.

Methods

No methods defined with class "SamplingPatternCentroids" in the signature.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingPatternPriorPoints"

Description

A class for storing a sampling pattern consisting of existing points and new points. The new points are the centers of gravity of their stratum.

Objects from the Class

Objects can be created by calls of the form new("SamplingPatternPriorPoints", ...). However, objects are usually created by calling spsample.

Slots

isPriorPoint:: Object of class "logical", which is TRUE is the location is a prior point, and FALSE if it is not.
sample:: Object of class "sp::SpatialPoints", containing the sampling locations

Extends

Class "SamplingPatternPurposive", directly. Class "SamplingPattern", by class "SamplingPatternPurposive", distance 2.

Methods

plot: signature(x = "CompactStratification", y = "SamplingPatternPriorPoints"): plots sampling pattern y on top of stratification x.
plot: signature(x = "SamplingPatternPriorPoints", y = "missing"): plots sampling pattern x.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingPatternPurposive"

Description

An ancestor class for storing purposive sampling patterns.

Objects from the Class

Objects can be created by calls of the form new("SamplingPatternPurposive", ...).

Slots

sample:: Object of class "sp::SpatialPoints", containing the sampling locations

Extends

Class "SamplingPattern", directly.

Methods

No methods defined with class "SamplingPatternPurposive" in the signature.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingPatternRandom"

Description

An ancestor class for storing random sampling patterns.

Objects from the Class

Objects can be created by calls of the form new("SamplingPatternRandom", ...).

Slots

sample:: Object of class "sp::SpatialPoints", containing the sampling locations

Extends

Class "SamplingPattern", directly.

Methods

No methods defined with class "SamplingPatternRandom" in the signature.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingPatternRandomComposite"

Description

A class for storing composites obtained by random sampling.

Objects from the Class

Objects can be created by calls of the form new("SamplingPatternRandomComposite", ...). However, objects are usually created by calling spsample.

Slots

composite:: Object of class "integer", indicating to which composite sample a sampling unit belongs.
sample:: Object of class "sp::SpatialPoints", containing the sampling locations.

Extends

Class "SamplingPatternRandom", directly. Class "SamplingPattern", by class "SamplingPatternRandom", distance 2.

Methods

coerce: signature(from = "SamplingPatternRandomComposite", to = "data.frame"): coerces to "data.frame".
coerce: signature(from = "SamplingPatternRandomComposite", to = "SpatialPointsDataFrame"): coerces to "sp::SpatialPointsDataFrame".
estimate: signature(statistic = "SamplingVariance", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame"): estimates the sampling variance. See "SamplingVariance" for more details.
estimate: signature(statistic = "SpatialMean", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame"): estimates the spatial mean. See "SpatialMean" for more details.
getSampleSize: signature(object = "SamplingPatternRandomComposite"): returns the sample size per stratum.
plot: signature(x = "CompactStratification", y = "SamplingPatternRandomComposite"): plots sampling pattern y on top of stratification x.
plot: signature(x = "SamplingPatternRandomComposite", y = "missing"): plots sampling pattern x.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingPatternRandomSamplingUnits"

Description

A class for storing sampling units obtained by random sampling.

Objects from the Class

Objects can be created by calls of the form new("SamplingPatternRandomSamplingUnits", ...). However, objects are usually created by calling spsample.

Slots

sample:: Object of class "sp::SpatialPoints", containing the sampling locations.

Extends

Class "SamplingPatternRandom", directly. Class "SamplingPattern", by class "SamplingPatternRandom", distance 2.

Methods

estimate: signature(statistic = "SamplingVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the sampling variance. See "SamplingVariance" for more details.
estimate: signature(statistic = "SpatialCumulativeDistributionFunction", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial cumulative distribution function (SCDF). See "SamplingPatternRandomSamplingUnits" for more details.
estimate: signature(statistic = "SpatialMean", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial mean. See "SpatialMean" for more details.
estimate: signature(statistic = "SpatialVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial variance. See "SpatialVariance" for more details.
estimate: signature(statistic = "StandardError", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the standard error of the spatial mean. See "StandardError" for more details.
estimate: signature(statistic = "character", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates statistic, i.e., "spatial mean", "spatial variance", "sampling variance", "standard error", SCDF.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "SamplingVariance"

Description

The sampling variance is estimated by means of Equation 7.14 in de Gruijter et al., (2006).

Objects from the Class

Objects can be created by calls of the form new("SamplingVariance", ...).

Slots

description:: Object of class "character" A description op the statistic.

Extends

Class "Statistic", directly.

Methods

estimate: signature(statistic = "SamplingVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the sampling variance, given a stratification, a sampling pattern and data.
estimate: signature(statistic = "SamplingVariance", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame"): estimates the sampling variance, given a stratification, a sampling pattern and data.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

References

de Gruijter, J. J., Brus, D. J., Bierkens, M. F. P., and Knotters, M. (2006) Sampling for Natural Resource Monitoring Berlin: Springer-Verlag.

Class "SpatialCumulativeDistributionFunction"

Description

The spatial cumulative distribution function (SCDF) is estimated by applying Equation 7.13 in de Gruijter et al., (2006) to indicator transformations of the data. See also page 83 of de Gruijter et al., (2006).

Objects from the Class

Objects can be created by calls of the form new("SpatialCumulativeDistributionFunction", ...).

Slots

description:: Object of class "character" A description op the statistic.

Extends

Class "Statistic", directly.

Methods

estimate: signature(statistic = "SpatialCumulativeDistributionFunction", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial cumulative distribution function (SCDF), given a stratification, a sampling pattern and data.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

References

de Gruijter, J. J., Brus, D. J., Bierkens, M. F. P., and Knotters, M. (2006) Sampling for Natural Resource Monitoring Berlin: Springer-Verlag.

Class "SpatialMean"

Description

The spatial mean is estimated by means of Equation 7.13 in de Gruijter et al., (2006).

Objects from the Class

Objects can be created by calls of the form new("SpatialMean", ...).

Slots

description:: Object of class "character" A description op the statistic.

Extends

Class "Statistic", directly.

Methods

estimate: signature(statistic = "SpatialMean", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial mean, given a stratification, a sampling pattern and data.
estimate: signature(statistic = "SpatialMean", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame"): estimates the spatial mean, given a stratification, a sampling pattern and data.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

References

de Gruijter, J. J., Brus, D. J., Bierkens, M. F. P., and Knotters, M. (2006) Sampling for Natural Resource Monitoring Berlin: Springer-Verlag.

Class "SpatialVariance"

Description

The spatial variance is estimated by means of Equation 7.16 in de Gruijter et al., (2006).

Objects from the Class

Objects can be created by calls of the form new("SpatialVariance", ...).

Slots

description:: Object of class "character" A description op the statistic.

Extends

Class "Statistic", directly.

Methods

estimate: signature(statistic = "SpatialVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the spatial variance, given a stratification, a sampling pattern and data.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

References

de Gruijter, J. J., Brus, D. J., Bierkens, M. F. P., and Knotters, M. (2006) Sampling for Natural Resource Monitoring Berlin: Springer-Verlag.

Class "StandardError"

Description

The standard error is estimated by means of the square root of Equation 7.14 in de Gruijter et al., (2006).

Objects from the Class

Objects can be created by calls of the form new("StandardError", ...).

Slots

description:: Object of class "character" A description op the statistic.

Extends

Class "SamplingVariance", directly. Class "Statistic", by class "SamplingVariance", distance 2.

Methods

estimate: signature(statistic = "StandardError", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame"): estimates the standard error, given a stratification, a sampling pattern and data.

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

References

de Gruijter, J. J., Brus, D. J., Bierkens, M. F. P., and Knotters, M. (2006) Sampling for Natural Resource Monitoring Berlin: Springer-Verlag.

Class "Statistic"

Description

A superclass (ancestor class) for statistics to estimate.

Objects from the Class

A virtual Class: No objects may be created from it.

Slots

description:: A description op the statistic

Methods

show: signature(object = "Statistic"): prints the statistic

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Class "Stratification"

Description

Virtual class to store a spatial stratification.

Objects from the Class

A virtual Class: No objects may be created from it.

Methods

show: signature(object = "Stratification"): a method for printing objects of class Stratification

Author(s)

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

Examples

showClass("Stratification")

Estimating Statistics

Description

Methods for estimating statistics given a spatial sample.

Methods

statistic = "character", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame": estimates one of the following statistics, depending on the value of argument statistic: spatial mean, spatial variance, sampling variance, standard error, or scdf. See the examples below for details.
statistic = "character", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame": estimates one of the following statistics, depending on the value of argument statistic: spatial mean, sampling variance, or standard error.
statistic = "SamplingVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame": estimates the sampling variance. See "SamplingVariance" for more details.
statistic = "StandardError", stratification = "CompactStratificationEqualArea", samplingPattern = "SamplingPatternRandomComposite", data = "data.frame": estimates the standard error of the spatial mean. See "StandardError" for more details.
statistic = "SpatialCumulativeDistributionFunction", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame": estimates the spatial cumulative distribution function (SCDF). See "SamplingPatternRandomSamplingUnits" for more details.
statistic = "SpatialMean", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame": estimates the spatial mean. See "SpatialMean" for more details.
statistic = "SpatialVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame": estimates the spatial variance. See "SpatialVariance" for more details.

Examples


# Note: the example below requires the 'sf'-package.
if (require(sf)) {
    # read vector representation of the "Mijdrecht" area
    shp <- as(st_read(
        dsn = system.file("maps", package = "spcosa"),
        layer = "mijdrecht"), "Spatial")

    # stratify into 30 strata
    myStratification <- stratify(shp, nStrata = 30, nTry = 10, verbose = TRUE)

    # random sampling of two sampling units per stratum
    mySamplingPattern <- spsample(myStratification, n = 2)

    # plot sampling pattern
    plot(myStratification, mySamplingPattern)

    # simulate data
    # (in real world cases these data have to be obtained by field work etc.)
    myData <- as(mySamplingPattern, "data.frame")
    myData$observation <- rnorm(n = nrow(myData), mean = 10, sd = 1)

    # design-based inference
    estimate("spatial mean", myStratification, mySamplingPattern, myData["observation"])
    estimate("sampling variance", myStratification, mySamplingPattern, myData["observation"])
    estimate("standard error", myStratification, mySamplingPattern, myData["observation"])
    estimate("spatial variance", myStratification, mySamplingPattern, myData["observation"])
    estimate("scdf", myStratification, mySamplingPattern, myData["observation"])
}

Extract the Area of an Object

Description

Methods for extracting the area of objects.

Methods

object = "CompactStratification": returns the area of each stratum.

Extract Centroids

Description

Methods for extracting centroids

Methods

object = "CompactStratification": returns the centers of gravity of each stratum.

Extract the Number of Strata in an Object

Description

Methods for extracting the number of strata of objects.

Methods

object = "CompactStratification": returns the number of strata in a compact stratification.

Extract the Objective Function Value of an Object

Description

Methods for extracting the objective function value

Methods

object = "CompactStratification": extracts the mean squared shortest distance.

Extract the Relative Area of an Object

Description

Methods for extracting relative areas of objects. The total area equals unity.

Methods

object = "CompactStratification": returns the relative area of each stratum. The sum of the relative areas equals 1.

Extract the sample size of an object

Description

Methods for extracting the sample size.

Methods

object = "SamplingPattern": returns the sample size.
object = "SamplingPatternRandomComposite": returns the number of composites

Visualizing Compact Stratifications and Sampling Patterns

Description

The plot method can be used to visualize compact stratifications and sampling patterns. Since it has been built on top of the ggplot2 package, functions provided by this package can be used to modify the plots.

Methods

x = "CompactStratification", y = "missing": plots stratification x.
x = "CompactStratification", y = "SamplingPattern": plots sampling pattern y on top of stratification x.
x = "CompactStratification", y = "SamplingPatternPriorPoints": plots sampling pattern y on top of stratification x.
x = "CompactStratification", y = "SamplingPatternRandomComposite": plots sampling pattern y on top of stratification x.
x = "SamplingPattern", y = "missing": plots sampling pattern x.
x = "SamplingPatternPriorPoints", y = "missing": plots sampling pattern x.
x = "SamplingPatternRandomComposite", y = "missing": plots sampling pattern x.

Spatial Sampling of Compact Strata

Description

Methods for sampling in compact strata.

Methods

x = "CompactStratification", n = "missing", type = "missing": samples the centroids of each stratum.
x = "CompactStratification", n = "numeric", type = "missing": stratified simple random sampling with n samples per stratum.
x = "CompactStratificationEqualArea", n = "numeric", type = "character": if type = "composite", stratified simple random sampling of n composites.
x = "CompactStratificationPriorPoints", n = "missing", type = "missing": spatial infill sampling

Examples

# Note: the example below requires the 'sf'-package.
if (require(sf)) {

    # read a vector representation of the `Farmsum' field
    shpFarmsum <- as(st_read(
        dsn = system.file("maps", package = "spcosa"),
        layer = "farmsum"), "Spatial")

    # stratify `Farmsum' into 50 strata
    # NB: increase argument 'nTry' to get better results
    set.seed(314)
    myStratification <- stratify(shpFarmsum, nStrata = 50, nTry = 1)

    # sample two sampling units per stratum
    mySamplingPattern <- spsample(myStratification, n = 2)

    # plot the resulting sampling pattern on
    # top of the stratification
    plot(myStratification, mySamplingPattern)

}

Stratification

Description

Methods for partitioning a spatial object into compact strata by means of k-means. The objective function to minimize is the mean squared shortest distance (MSSD). Optionally, the strata may be forced to be of equal size. This facilitates field work in case of stratified simple random sampling for composites. Another option is spatial infill sampling, a variant of spatial coverage sampling where existing sampling points are taken into account. Use nTry > 1, to reduce the risk of ending up in an unfavorable local optimum. Better results will generally be obtained by increasing the ratio nGridCells/nStrata and by increasing nTry.

Usage

## S4 method for signature 'SpatialPixels'
stratify(object, nStrata, priorPoints = NULL, maxIterations = 1000, nTry = 1,
    equalArea = FALSE, verbose = getOption("verbose"))
## S4 method for signature 'SpatialGrid'
stratify(object, nStrata, priorPoints = NULL, maxIterations = 1000, nTry = 1,
    equalArea = FALSE, verbose = getOption("verbose"))
## S4 method for signature 'SpatialPolygons'
stratify(object, nStrata, priorPoints = NULL, maxIterations = 1000, nTry = 1,
    nGridCells = 2500, cellSize, equalArea = FALSE, verbose = getOption("verbose"))

Arguments

object

an object of class "sp::SpatialPixels", "sp::SpatialGrid" or "sp::SpatialPolygons"

nStrata

number of strata (nStrata >= 1).

priorPoints

object of class "sp::SpatialPoints", containing the prior (i.e., existing) points

maxIterations

maximum number of iterations.

nTry

the stratify method will try nTry initial configurations and will keep the best solution in order to reduce the risk of ending up with an unfavorable solution.

nGridCells

in case object is an instance of class "sp::SpatialPolygons", the approximate number of grid cells to be used for discretizing the vector map in object.

cellSize

in case object is an instance of class "sp::SpatialPolygons", the cell size to be used for discretizing the vector map in object. Note that cellsize takes precedence over argument nGridCells.

equalArea

If FALSE the algorithm results in compact strata. If TRUE, the algorithm results in compact strata of equal size.

verbose

if TRUE, progress information and intermediate results will be printed to the output device.

Methods

object = "SpatialPixels": Stratify a raster representation of the study area.
object = "SpatialPolygons": Stratify a vector representation of the study area.

Note

When the projection attribute of a map is set to EPSG:4326 (lat/lon), great circle distances will be used for stratification. Otherwise, Euclidean distances will be used.

References

de Gruijter, J. J., Brus, D. J., Bierkens, M. F. P., and Knotters, M. (2006) Sampling for Natural Resource Monitoring Berlin: Springer-Verlag.

Walvoort, D., Brus, D. and de Gruijter, J. (2009). Spatial Coverage Sampling on Various Spatial Scales. Pedometron 26:20-22

Examples

# Note: the example below requires the 'sf'-package
if (require(sf)) {

    # read a vector representation of the `Farmsum' field
    shpFarmsum <- as(st_read(
        dsn = system.file("maps", package = "spcosa"),
        layer = "farmsum"), "Spatial")

    # stratify `Farmsum' into 50 strata
    # NB: increase argument 'nTry' to get better results
    set.seed(314)
    myStratification <- stratify(shpFarmsum, nStrata = 50, nTry = 1)

    # plot the resulting stratification
    plot(myStratification)

}

Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata

Description

Details

Note

Author(s)

References

See Also

Class "CompactStratification"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "CompactStratificationEqualArea"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "CompactStratificationPriorPoints"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "SamplingPattern"

Description

Objects from the Class

Slots

Methods

Author(s)

Class "SamplingPatternCentroids"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "SamplingPatternPriorPoints"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "SamplingPatternPurposive"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "SamplingPatternRandom"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "SamplingPatternRandomComposite"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "SamplingPatternRandomSamplingUnits"

Description

Objects from the Class

Slots

Extends

Methods

Author(s)

Class "SamplingVariance"

Description

Objects from the Class

Slots