Package 'sfcentral'

Spatial centrality

Description

Functions to find spatial measures of gravity centers.

Usage

st_central_point(.x, .y, ...)

## S3 method for class 'sfg'
st_central_point(
  .x,
  .y = NULL,
  weights = NULL,
  method = c("mean", "median", "geometric", "feature", "min.dist"),
  ...
)

## S3 method for class 'sf'
st_central_point(
  .x,
  .y = NULL,
  weights = NULL,
  method = c("mean", "median", "geometric", "feature", "min.dist"),
  ...
)

## S3 method for class 'sfc'
st_central_point(
  .x,
  .y = NULL,
  weights = NULL,
  method = c("mean", "median", "geometric", "feature", "min.dist"),
  ...
)

Arguments

.x, .y	sf points 2D or 3D
...	arguments to be passed to or from other methods
weights	Numeric. Used in for weigthed Mean Center. Has to be same length as number of points.
method	Character. Type of center point to calculate
dist	Atomic numeric, Default 100. Starting distance value for center moving during iterations.

Details

Spatial centers are spatial measures of the gravity center.

methods options are: "mean" is the mean center (equivalent to centroid of the points) calculated by the arithmetic mean of each axis; "geometric", is the corresponding geometric mean of each axis; "median", is the median center, a pair of c(median(x), median(y)) coordinates; "feature", is a minimization of the sum of distances from ith point to every point; "min.dist", is iterative looking for the closest point in bbox of .x that minimizes the sum of distances from ith point to every point in the dataset

Value

"Simple Features" of lenght 1.

Note

Inspired on ⁠aspace::*()⁠ from Ron Buliung & Randy Bui (2012)

Author(s)

Gabriel Gaona

Examples

requireNamespace("ggplot2", quietly = TRUE)
library(sf, quietly = TRUE)
library(ggplot2)
bbx <- matrix(c(697047,9553483,
                696158,9560476,
                700964,9561425,
                701745,9555358),
              byrow = TRUE,
              ncol = 2)
bbx <- st_multipoint(bbx)
bbx <- st_cast(bbx,"POLYGON")
bbx <- st_sfc(bbx, crs = 31992)
set.seed(1234)
points <- st_sf(geometry = st_sample(bbx, 100))
mean_center <- st_central_point(points, method = "mean")
median_center <- st_central_point(points, method = "median")
geom_center <- st_central_point(points, method = "geometric")
central_feature <- st_central_point(points, method = "feature")
min_dist_center <- st_central_point(points, method = "min.dist")
ggplot() +
  geom_sf(data = points, color = "steelblue", size = 0.5) +
  geom_sf(data = mean_center, color = "blue", size = 3) +
  geom_sf(data = median_center, color = "red") +
  geom_sf(data = geom_center, color = "grey80") +
  geom_sf(data = central_feature, color = "orange") +
  geom_sf(data = min_dist_center, color = "green")

---

Standard deviation box calculator in 2D or 3D

Description

Calculate the spatial deviaction box from a points sf dataset. #' @author Gabriel Gaona

Usage

st_sd_box(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfg'
st_sd_box(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sf'
st_sd_box(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfc'
st_sd_box(.x, centre = NULL, weights = NULL, ...)

Arguments

.x	sf points 2D or 3D
centre	Numeric. Coordinates 2D or 3D of central point. Default NULL, performs a calculation of mean_centre() from point localities
weights	Numeric. Same length of number of .x.
...	ignored

Value

Depends on input, "coords" returns a data.frame of 2 or 3 columns and 4 or 8 point coordinates. "param" returns a data.frame with centre coordinates, standard deviation in each axis, space(area for 2D, volume for 3D) and number of dimensions in coordinates.

Examples

requireNamespace("ggplot2", quietly = TRUE)
 library(sf, quietly = TRUE)
 library(ggplot2)
 bbx <- matrix(c(697047,9553483,
                 696158,9560476,
                 700964,9561425,
                 701745,9555358),
               byrow = TRUE,
               ncol = 2)
 bbx <- st_multipoint(bbx)
 bbx <- st_cast(bbx,"POLYGON")
 bbx <- st_sfc(bbx, crs = 31992)
 set.seed(1234)
 points <- st_sf(geometry = st_sample(bbx, 100))
 SD_BOX <- st_sd_box(points)
 ggplot() +
   geom_sf(data = SD_BOX, fill = NA, color = "darkolivegreen") +
   geom_sf(data = points, color = "steelblue", size = 0.5)

---

Standard deviation distance calculator

Description

Calculate the spatial deviaction distance from a points sf dataset.

Usage

st_sd_distance(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfg'
st_sd_distance(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sf'
st_sd_distance(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfc'
st_sd_distance(.x, centre = NULL, weights = NULL, ...)

Arguments

.x	sf points 2D or 3D
centre	One central point of class sf, sfc, numeric (length 2), matrix (2 col, 1 row), data.frame (2 col, 1 row), or list (length 2). Default NULL, means a calculation of the st_central_point() from .x localities.
weights	Numeric. Same length as number of points in .x.
...	other parameters for sf::st_distance()

Value

A sf "POLYGON" with atributes:

• radius (standard deviation distance)

• area surrounding,

• perimeter,

• center coordinates,

• weigted indicator if weights were used or not in the calculaton.

Author(s)

Gabriel Gaona

Examples

requireNamespace("ggplot2", quietly = TRUE)
  library(sf, quietly = TRUE)
  library(ggplot2)
  bbx <- matrix(c(697047,9553483,
                  696158,9560476,
                  700964,9561425,
                  701745,9555358),
                byrow = TRUE,
                ncol = 2)
  bbx <- st_multipoint(bbx)
  bbx <- st_cast(bbx,"POLYGON")
  bbx <- st_sfc(bbx, crs = 31992)
  set.seed(1234)
  points <- st_sf(geometry = st_sample(bbx, 100))
  SDD <- st_sd_distance(points)
  ggplot() +
    geom_sf(data = SDD, fill = NA, color = "darkolivegreen") +
    geom_sf(data = points, color = "steelblue", size = 0.5)

---

Standard deviation ellipse calculator

Description

Calculate the spatial deviaction ellipse from a points sf dataset.

Usage

st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfg'
st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sf'
st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfc'
st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

Arguments

.x	sf points 2D or 3D
centre	Numeric. Coordinates 2D of central point. Default NULL, performs a calculation of mean_centre() from point localities
weights	Numeric. Same length of number of points.
...	ignored

Value

simple features as "POLYGON" with atributes: centre coordinates, values for mayor and minor axis radius (sigma.x and sigma.y), rotation (theta and theta_corrected) and geometry properties (eccentricity, area and perimeter)

Author(s)

Gabriel Gaona

Examples

requireNamespace("ggplot2", quietly = TRUE)
  library(sf, quietly = TRUE)
  library(ggplot2)
  bbx <- matrix(c(697047,9553483,
                  696158,9560476,
                  700964,9561425,
                  701745,9555358),
                byrow = TRUE,
                ncol = 2)
  bbx <- st_multipoint(bbx)
  bbx <- st_cast(bbx,"POLYGON")
  bbx <- st_sfc(bbx, crs = 31992)
  set.seed(1234)
  points <- st_sf(geometry = st_sample(bbx, 100))
  SDE <- st_sd_ellipse(points)
  ggplot() +
    geom_sf(data = SDE, fill = NA, color = "darkolivegreen") +
    geom_sf(data = points, color = "steelblue", size = 0.5)

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