Spatial data: calculating the distance of points from the maximum point value and plotting

Question

My question is similar to this post where the distance between each point was calculated.

In my case, I am looking to find the distance of each point to the point with the highest value. I would also like to plot this relationship with lm(), but I am struggling to achieve both tasks with spatial data objects.

My data does not need CRS, it is based on the Euclidean distance (because these points are in a room).

A mock example of the data below, where column variable is of interest.

> dput(dat)
structure(list(date.hour = structure(c(1551057840, 1551057840, 
1551057840, 1551057840, 1551057840, 1551057840, 1551057840), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), id = c(2, 5, 7, 8, 9, 10, 11), variable = c(456, 
27, 130, 116, 92, 141, 145), xy_coord = c("6.2 14.8", "8.2 8.9", 
"4.2 8.9", "2.2 8.9", "8.2 3.5", "6.2 3.5", "4.2 3.5")), row.names = c(NA, 
-7L), groups = structure(list(id = c(2, 5, 7, 8, 9, 10, 11), 
    date.hour = structure(c(1551057840, 1551057840, 1551057840, 
    1551057840, 1551057840, 1551057840, 1551057840), tzone = "UTC", class = c("POSIXct", 
    "POSIXt")), .rows = structure(list(1L, 2L, 3L, 4L, 5L, 6L, 
        7L), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr", 
    "list"))), row.names = c(NA, -7L), class = c("tbl_df", "tbl", 
"data.frame"), .drop = TRUE), class = c("grouped_df", "tbl_df", 
"tbl", "data.frame"))

> dat
# A tibble: 7 x 4
# Groups:   id, date.hour [7]
  date.hour              id variable xy_coord
  <dttm>              <dbl>    <dbl> <chr>   
1 2019-02-25 01:24:00     2      456 6.2 14.8
2 2019-02-25 01:24:00     5       27 8.2 8.9 
3 2019-02-25 01:24:00     7      130 4.2 8.9 
4 2019-02-25 01:24:00     8      116 2.2 8.9 
5 2019-02-25 01:24:00     9       92 8.2 3.5 
6 2019-02-25 01:24:00    10      141 6.2 3.5 
7 2019-02-25 01:24:00    11      145 4.2 3.5 
>

Turning the data frame into a SpatialPointsDataFrame with the sp() package:

#Split x and y to separate columns 
dat$x <- sapply(strsplit(as.character(dat$xy_coord), " "), "[", 1); dat$x <- as.numeric(dat$x)
dat$y <- sapply(strsplit(as.character(dat$xy_coord), " "), "[", 2); dat$y <- as.numeric(dat$y)

#SpatialPointsDataFrame
coordinates(dat) <- ~x+y

This is the point where I don't know what steps to take, but I want to know the distance of all the points to the highest value:

which.max(dat@data$variable)

And then plot this relationship with base plot().

If my question is unclear please let me know.

What do you mean by "plot this relationship with lm()"? Which relationship? — agila, Nov 21 '21 at 10:40
Plot the effect of distance from the point with the highest value. — kpm, Nov 21 '21 at 11:03
Not sure if my explanation is confusing, but I am using the highest value as proxy of the independent variable. — kpm, Nov 21 '21 at 11:25
So you want to create a plot where the x values represent the distance from the point with the highest value of a covariate and what are the y values? the same covariate? — agila, Nov 21 '21 at 13:24

score 1 · Accepted Answer · answered Nov 22 '21 at 13:14

I'm still not sure I understand your question but I propose the following answer.

Load packages

library(sf)
#> Linking to GEOS 3.9.1, GDAL 3.2.1, PROJ 7.2.1
library(tidyr)

Load data

dat = structure(
  list(
    date.hour = structure(
      c(
        1551057840, 1551057840, 1551057840, 1551057840, 1551057840, 
        1551057840, 1551057840
      ), 
      tzone = "UTC", 
      class = c(
        "POSIXct",
        "POSIXt"
      )
    ), 
    id = c(2, 5, 7, 8, 9, 10, 11), 
    variable = c(
      456, 27, 130, 116, 92, 141, 145
    ), 
    xy_coord = c(
      "6.2 14.8", "8.2 8.9", "4.2 8.9", "2.2 8.9", "8.2 3.5", "6.2 3.5", 
      "4.2 3.5"
    )
  ), 
  row.names = c(NA,-7L), 
  groups = structure(
    list(
      id = c(2, 5, 7, 8, 9, 10, 11),
      date.hour = structure(
        c(
          1551057840, 1551057840, 1551057840, 1551057840, 1551057840, 
          1551057840, 1551057840
        ), 
        tzone = "UTC", 
        class = c(
          "POSIXct",
          "POSIXt"
        )
      ), 
      .rows = structure(
        list(1L, 2L, 3L, 4L, 5L, 6L, 7L), 
        ptype = integer(0), 
        class = c(
          "vctrs_list_of", "vctrs_vctr", "list"
        )
      )
    ), 
    row.names = c(NA, -7L), 
    class = c("tbl_df", "tbl", "data.frame"), 
    .drop = TRUE
  ), 
  class = c("grouped_df", "tbl_df", "tbl", "data.frame")
)

Separate the xy_coord column, convert columns to numeric and create an sf object

dat_sf <- st_as_sf(
  separate(dat, xy_coord, c("x", "y"), sep = " ", convert = TRUE), 
  coords = c("x", "y")
)

Find the maximum of variable

which.max(dat_sf[["variable"]])
#> [1] 1

Compute all distances

dat_sf[["distances"]] <- st_distance(dat_sf, dat_sf[1, ])

Plot

plot(variable ~ distances, data = dat_sf)

^{Created on 2021-11-22 by the reprex package (v2.0.1)}

You can also remove the first point (with distance = 0).

Spatial data: calculating the distance of points from the maximum point value and plotting

1 Answers1