我尝试根据值生成热图。 这是我的数据集,它由三个变量组成:Lat(纬度),Lon(经度)和Value。 https://www.dropbox.com/s/s53xeplywz9jh15/sample_data.csv?dl=0
我查看了相关帖子,发现这很有用: Generating spatial heat map via ggmap in R based on a value
我复制了该帖子中的代码,这里我的代码如下:
# import data and libaries
library(ggplot2)
library(ggmap)
Yunan<-read.csv("C:\\Program Files\\RStudio\\data\\pb_sp\\sample_data.csv", header = TRUE)
# call the map to see point distribution
Yunan_map<-get_map(location="yunan",zoom=6,maptype="terrain",scale=2)
ggmap(Yunan_map)+geom_point(data=Yunan,aes(x=Yunan$Lon,y=Yunan$Lat,fill="red",alpha=0.3,size=0.05,shape=21))+scale_shape_identity()
# 1. generate bins for x, y coordinates (unit=decimal degree)
xbreaks <- seq(floor(min(Yunan$Lat,na.rm=TRUE)), ceiling(max(Yunan$Lat,na.rm=TRUE)), by = 0.5)
ybreaks <- seq(floor(min(Yunan$Lon,na.rm=TRUE)), ceiling(max(Yunan$Lon,na.rm=TRUE)), by = 0.5)
# 2. allocate the data points into the bins
Yunan$latbin <- xbreaks[cut(Yunan$Lat, breaks = xbreaks, labels=F)]
Yunan$longbin <- ybreaks[cut(Yunan$Lon, breaks = ybreaks, labels=F)]
# 3. summarise the data for each bin (use the median)
datamat <- Yunan[, list(Value= median(Value)),
by = c("latbin", "longbin" )]
# 4. Merge the summarised data with all possible x, y coordinate combinations to get
# a value for every bin
datamat <- merge(setDT(expand.grid(latbin = xbreaks, longbin = ybreaks)), datamat,
by = c("latbin", "longbin"), all.x = TRUE, all.y = FALSE)
# 5. Fill up the empty bins 0 to smooth the contour plot
datamat[is.na(Value), ]$Value <- 0
# 6. Plot the contours
ggmap(Yunan_map,extent ="device") +
stat_contour(data = datamat, aes(x = longbin, y = latbin, z = Value,
fill = ..level.., alpha = ..level..), geom = 'polygon', binwidth = 30) +
scale_fill_gradient(name = "Value", low = "green", high = "red") +
guides(alpha = FALSE)
然而,我遇到了两个问题