我有一个包含超过 50 000 个值的数据框(见下文),每个值都与一个位置(纬度、经度)相关联。我想计算 5° 纬度 x 5° 经度网格的每个单元格的平均值,以创建热图。最终目标是在测深图上绘制此网格。
我看过类似这样的问题 Average values of a point dataset to a grid dataset .但我无法用自己的数据复制这些示例。遗憾的是,我停留在创建网格的第一步。
我的数据是这样的:
library(sp)
library(proj4)
coordinates(data) <- c("lon", "lat")
proj4string(data) <- CRS("+init=epsg:4326") #defined CRS to WGS 84
df<- data.frame(data)
> head(df)
lon lat value
1 -48.1673562 57.71791 822.9
2 -48.7430053 57.83568 1302.3
3 -48.5662663 57.82087 1508.0
4 -48.3252052 58.29815 224.0
5 -47.1716772 58.42417 38.0
6 -46.4098311 58.67651 431.2
7 -45.8071218 58.70022 365.6
8 -45.5558936 58.46975 50.0
理想情况下,我想使用 ggplot2(见下文)在 marmap 包的 map 上绘制网格:
library(marmap)
library(ggplot2)
atlantic <- getNOAA.bathy(-80, 40, 0, 90, resolution = 25, keep = TRUE)
atl.df <- fortify(atlantic)
map <- ggplot(atl.df, aes(x=x, y=y)) +
geom_raster(aes(fill=z), data=atl.df) +
geom_contour(aes(z=z),
breaks=0, #contour for continent
colour="black", size=1) +
scale_fill_gradientn(values = scales::rescale(c(-5000, 0, 1, 2400)),
colors = c("steelblue4", "#C7E0FF", "gray40", "white"))
最佳答案
听起来您想将数值变量(纬度和经度)切割成均匀的区间并汇总每个区间内的值。以下对您有用吗?
library(dplyr)
df2 <- df %>%
mutate(lon.group = cut(lon, breaks = seq(floor(min(df$lon)), ceiling(max(df$lon)), by = 5),
labels = seq(floor(min(df$lon)) + 2.5, ceiling(max(df$lon)), by = 5)),
lat.group = cut(lat, breaks = seq(floor(min(df$lat)), ceiling(max(df$lat)), by = 5),
labels = seq(floor(min(df$lat)) + 2.5, ceiling(max(df$lat)), by = 5))) %>%
group_by(lon.group, lat.group) %>%
summarise(value = mean(value), .groups = "drop") %>%
mutate(across(where(is.factor), ~as.numeric(as.character(.x))))
示例数据:
set.seed(444)
n <- 10000
df <- data.frame(lon = runif(n, min = -100, max = -50),
lat = runif(n, min = 30, max = 80),
value = runif(n, min = 0, max = 1000))
> summary(df)
lon lat value
Min. :-99.99 Min. :30.00 Min. : 0.1136
1st Qu.:-87.55 1st Qu.:42.45 1st Qu.: 247.2377
Median :-75.29 Median :55.11 Median : 501.4165
Mean :-75.12 Mean :55.01 Mean : 499.5385
3rd Qu.:-62.69 3rd Qu.:67.63 3rd Qu.: 748.8834
Max. :-50.01 Max. :80.00 Max. : 999.9600
前后数据对比:
gridExtra::grid.arrange(
ggplot(df,
aes(x = lon, y = lat, colour = value)) +
geom_point() +
ggtitle("Original points"),
ggplot(df2,
aes(x = lon.group, y = lat.group, fill = value)) +
geom_raster() +
ggtitle("Summarised grid"),
nrow = 1
)
关于R:如何从网格创建平均值的热图并使用 ggplot 绘制它?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/63820526/