The irregularly-spaced data are interpolated onto regular latitude-longitude grids by weighting each station according to its distance and angle from the center of a search radius.
Caesar, J., L. Alexander, and R. Vose, 2006: Large-scale changes in observed daily maximum and minimum temperatures: Creation and analysis of a new gridded data set. Journal of Geophysical Research, 111, https://doi.org/10.1029/2005JD006280.
Install the latest CRAN release via command:
install.packages("adw")The development version can be installed from GitHub (https://github.com/PanfengZhang/adw) using:
install.packages("remotes")
remotes::install_github("PanfengZhang/adw")library(ggplot2)
library(sf)
library(terra)
library(adw)
da <- read.csv("./inst/extdata/henan_temperature.csv")
head(da)
## lon lat value
## 1 113.82 36.07 26.5
## 2 114.40 36.05 27.3
## 3 112.92 35.12 23.5
## 4 114.18 35.62 29.2
## 5 112.63 35.08 23.6
## 6 113.08 35.15 24.5
urlmap <- "https://geo.datav.aliyun.com/areas_v3/bound/410000.json"
hmap <- read_sf(urlmap) |> st_cast('MULTILINESTRING')
ggplot() +
geom_sf(data = hmap) +
geom_point(data = da, aes(x = lon, y = lat, colour = value),
pch = 17, size = 2.5) +
scale_colour_fermenter(palette = "YlOrRd",
direction = 1,
breaks = seq(from = 25, to = 32, by = 1),
limits = c(0, 100),
name = expression("\u00B0C")) +
ggtitle("Irregularly-spaced data points (temperature)") +
theme_bw() +
theme(axis.title = element_blank(),
legend.key.width = unit(0.5,"cm"),
legend.key.height = unit(1.5, "cm"),
plot.title = element_text(hjust = 0.5, size = 11))
The irregularly-spaced data are interpolated onto regular latitude-longitude grids.
Usuage 1. The parameter *exten**t* in the adw function is a *SpatVecto**r* object, and the coordinate reference system of the object is WGS1984 (EPSG: 4326).
hmap_terra <- terra::vect(urlmap)
ds <- adw(da, extent = hmap_terra, gridsize = 0.1, cdd = 1e5)
head(ds)
## lon lat value
## 1 115.3105 31.43345 33.13984
## 2 114.7105 31.53345 32.54283
## 3 114.8105 31.53345 32.83359
## 4 114.9105 31.53345 33.02109
## 5 115.0105 31.53345 33.07372
## 6 115.3105 31.53345 33.12438
ggplot() +
geom_raster(data = ds, aes(x = lon, y = lat, fill = value)) +
geom_sf(data = hmap) +
scale_fill_fermenter(palette = "YlOrRd",
direction = 1,
breaks = seq(from = 25, to = 32, by = 1),
limits = c(0, 100),
name = expression("\u00B0C"),
na.value = "white") +
ggtitle("Angular distance weighting interpolation") +
theme_bw() +
theme(axis.title = element_blank(),
legend.key.width = unit(0.5,"cm"),
legend.key.height = unit(1.5, "cm"),
plot.title = element_text(hjust = 0.5, size = 11))
It can be seen that the interpolated grid values outside the polygon has been removed.
Usuage 2. The parameter *exten**t* is a numeric vector of length 4 in the order [xmin, xmax, ymin, ymax].
ds <- adw(da, extent = c(110.36, 116.65, 31.38, 36.37), gridsize = 0.1, cdd = 1e5)
head(ds)
## lon lat value
## 1 110.41 31.43 NA
## 2 110.51 31.43 NA
## 3 110.61 31.43 NA
## 4 110.71 31.43 NA
## 5 110.81 31.43 NA
## 6 110.91 31.43 NA
ggplot() +
geom_raster(data = ds, aes(x = lon, y = lat, fill = value)) +
geom_sf(data = hmap) +
scale_fill_fermenter(palette = "YlOrRd",
direction = 1,
breaks = seq(from = 25, to = 32, by = 1),
limits = c(0, 100),
name = expression("\u00B0C"),
na.value = "white") +
ggtitle("Angular distance weighting interpolation") +
theme_bw() +
theme(axis.title = element_blank(),
legend.key.width = unit(0.5,"cm"),
legend.key.height = unit(1.5, "cm"),
plot.title = element_text(hjust = 0.5, size = 11))
There are some interpolated values outside the polygon boundary, and these values can be removed by the method of mask, which will not be repeated here.