Type: | Package |
Title: | Kernel Density Estimation for Spatial Data |
Version: | 0.8.2 |
URL: | https://jancaha.github.io/SpatialKDE/index.html, https://github.com/JanCaha/SpatialKDE |
Description: | Calculate Kernel Density Estimation (KDE) for spatial data. The algorithm is inspired by the tool 'Heatmap' from 'QGIS'. The method is described by: Hart, T., Zandbergen, P. (2014) <doi:10.1108/PIJPSM-04-2013-0039>, Nelson, T. A., Boots, B. (2008) <doi:10.1111/j.0906-7590.2008.05548.x>, Chainey, S., Tompson, L., Uhlig, S.(2008) <doi:10.1057/palgrave.sj.8350066>. |
License: | MIT + file LICENSE |
Encoding: | UTF-8 |
RoxygenNote: | 7.2.3 |
VignetteBuilder: | knitr |
LinkingTo: | cpp11, progress |
Imports: | sf, dplyr, glue, magrittr, rlang, vctrs, methods, raster |
Suggests: | tmap, sp, knitr, rmarkdown, testthat (≥ 2.99.0), xml2 |
Config/testthat/edition: | 3 |
NeedsCompilation: | yes |
Packaged: | 2023-02-18 14:21:48 UTC; cahik |
Author: | Jan Caha |
Maintainer: | Jan Caha <jan.caha@outlook.com> |
Repository: | CRAN |
Date/Publication: | 2023-02-18 15:10:02 UTC |
Pipe operator
Description
See magrittr::%>%
for details.
Usage
lhs %>% rhs
Create grid
Description
Create grid of equally spaced rectangles or hexagons. The distance between centre points
in both x and y dimension is equal to cell_size
. The function is effectively a wrapper around
st_make_grid
with a little bit of preprocessing including generation of grid only inside
st_convex_hull
.
Usage
create_grid_rectangular(
geometry,
cell_size,
side_offset = 0,
only_inside = FALSE
)
create_grid_hexagonal(
geometry,
cell_size,
side_offset = 0,
only_inside = FALSE
)
Arguments
geometry |
|
cell_size |
|
side_offset |
|
only_inside |
|
Value
sf
data.frame
.
Functions
-
create_grid_rectangular()
: Create rectangular grid -
create_grid_hexagonal()
: Create hexagonal grid
Examples
library(sf)
nc <- st_read(system.file("shape/nc.shp", package = "sf")) %>% st_transform(32031)
grid <- create_grid_hexagonal(nc, cell_size = 100000)
grid <- create_grid_rectangular(nc, cell_size = 100000, only_inside = TRUE)
Create raster
Description
Create raster of equally spaced cells. The distance between centre of cells
in both x and y dimension is equal to cell_size
.
Usage
create_raster(geometry, cell_size, side_offset = 0)
Arguments
geometry |
|
cell_size |
|
side_offset |
|
Value
Examples
library(sf)
nc <- st_read(system.file("shape/nc.shp", package = "sf")) %>% st_transform(32031)
raster <- create_raster(nc, cell_size = 100000)
Kernel Density Estimation
Description
KDE for spatial data. The algorithm is heavily inspired by Heatmap tool in QGIS. The help for QGIS tools is provided at the QGIS website. The a tutorial is provided here.
Usage
kde(
points,
band_width,
decay = 1,
kernel = c("quartic", "uniform", "triweight", "epanechnikov", "triangular"),
scaled = FALSE,
weights = c(),
grid,
cell_size,
quiet = FALSE
)
Arguments
points |
|
band_width |
|
decay |
|
kernel |
|
scaled |
|
weights |
|
grid |
either |
cell_size |
|
quiet |
Should printing of progress bar be suppressed? Default 'FALSE'. |
Details
grid
parameter specifies output of the function. KDE is calculated on the specified grid
.
If grid is Raster-class
then outcome is also Raster-class
.
If grid is sf
data.frame
then outcome is also sf
data.frame
.
Value
either sf
data.frame
or Raster-class
depending on class of grid
parameter.
Examples
library(sf)
nc <- st_read(system.file("shape/nc.shp", package = "sf")) %>% st_transform(32031)
grid <- create_grid_hexagonal(nc, cell_size = 100000)
points <- st_sample(nc, 500) %>% st_as_sf()
kde_estimate_grid <- kde(points, band_width = 150000, grid = grid)
raster <- create_raster(nc, cell_size = 100000)
kde_estimate_raster <- kde(points, band_width = 150000, grid = raster)