Question

我有一个名为“seoul032823”的81个观察的每小时PM10数据集。您可以从Here下载。我在这个数据集上进行了普通克里金法，并得到了克里金预测的空间图。我还可以在国家地图上显示观察数据点。但我不能在国家地图上重叠克里格空间预测图。

我想做什么：我想在韩国地图（不是整个韩国）上重叠我的空间预测地图。我感兴趣的领域是北纬37.2N到37.7N＆amp;经度126.6E至127.2E。这意味着我需要从韩国地图中裁剪这个区域并在此处重叠预测图。我还需要根据浓度值显示原始观测数据点，这些点将遵循空间地图的颜色。例如，我想要这种类型的地图：

我的R代码用于克里金法，并在韩国地图上显示数据点：

library(sp)
library(gstat)
library(automap)
library(rgdal)
library(e1071)
library(dplyr)
library(lattice)

seoul032823 <- read.csv ("seoul032823.csv")

#plotting the pm10 data on Korea Map
library(ggplot2)
library(raster)

seoul032823 <- read.csv ("seoul032823.csv")
skorea<- getData("GADM", country= "KOR", level=1)
plot(skorea)

skorea<- fortify(skorea)
ggplot()+
  geom_map(data= skorea, map= skorea, aes(x=long,y=lat,map_id=id,group=group),
           fill=NA, colour="black") +
  geom_point(data=seoul032823, aes(x=LON, y=LAT), 
             colour= "red", alpha=0.7,na.rm=T) +
  #scale_size(range=c(2,4))+
  labs(title= "PM10 Concentration in Seoul Area at South Korea",
       x="Longitude", y= "Latitude", size="PM10(microgm/m3)")+
  theme(title= element_text(hjust = 0.5,vjust = 1,face= c("bold")))

# Reprojection
coordinates(seoul032823) <- ~LON+LAT
proj4string(seoul032823) <- "+proj=longlat +datum=WGS84" 
seoul032823 <- spTransform(seoul032823, CRS("+proj=utm +north +zone=52 +datum=WGS84"))

#Creating the grid for Kriging
LON.range <- range(as.integer(seoul032823@coords[,1 ])) + c(0,1)
LAT.range <- range(as.integer(seoul032823@coords[,2 ]))
seoul032823.grid <- expand.grid(LON = seq(from = LON.range[1], to = LON.range[2], by = 1500),
                                LAT = seq(from = LAT.range[1], to = LAT.range[2], by = 1500))
plot(seoul032823.grid)
points(seoul032823, pch= 16,col="red")
coordinates(seoul032823.grid)<- ~LON+LAT
gridded(seoul032823.grid)<- T
plot(seoul032823.grid)
points(seoul032823, pch= 16,col="red")

# kriging spatial prediction map
seoul032823_OK<- autoKrige(formula = PM10~1,input_data = seoul032823, new_data = seoul032823.grid )
pts.s <- list("sp.points", seoul032823, col = "red", pch = 16)
automapPlot(seoul032823_OK$krige_output, "var1.pred", asp = 1,
            sp.layout = list(pts.s), main = " Kriging Prediction")

我使用automap套餐进行克里金，ggplot2用于绘制韩国地图。

Answer 1

我对空间分析不太熟悉，因此投影可能存在问题。

首先，根据answer引用Zev Ross，ggplot2可以更好地处理data.frames与空间对象。知道这一点，我们就可以从您的kriged空间对象seoul032823_OK中提取克里金预测。其余的相对简单。您可能必须修复经度/纬度轴标记并确保最终输出的尺寸正确。（如果你这样做，我可以编辑/追加答案以包括这些额外的步骤。）

# Reprojection of skorea into same coordinates as sp objects
# Not sure if this is appropriate
coordinates(skorea) <- ~long+lat  #{sp} Convert to sp object
proj4string(skorea) <- "+proj=longlat +datum=WGS84" #{sp} set projection attributes
#{sp} Transform to new coordinate reference system
skorea <- spTransform(skorea, CRS("+proj=utm +north +zone=52 +datum=WGS84")) 

#Convert spatial objects into data.frames for ggplot2
myPoints <- data.frame(seoul032823)
myKorea <- data.frame(skorea)
#Extract the kriging output data into a dataframe.  This is the MAIN PART!
myKrige <- data.frame(seoul032823_OK$krige_output@coords, 
                      pred = seoul032823_OK$krige_output@data$var1.pred)   
head(myKrige, 3)  #Preview the data
#     LON     LAT     pred
#1 290853 4120600 167.8167
#2 292353 4120600 167.5182
#3 293853 4120600 167.1047

#OP's original plot code, adapted here to include kriging data as geom_tile
ggplot()+ theme_minimal() +
  geom_tile(data = myKrige, aes(x= LON, y= LAT, fill = pred)) +
  scale_fill_gradient2(name=bquote(atop("PM10", mu*g~m^-3)), 
                       high="red", mid= "plum3", low="blue", 
                       space="Lab", midpoint = median(myKrige$pred))  + 
  geom_map(data= myKorea, map= myKorea, aes(x=long,y=lat,map_id=id,group=group),
           fill=NA, colour="black") +
  geom_point(data=myPoints, aes(x=LON, y=LAT, fill=PM10), 
             shape=21, alpha=1,na.rm=T, size=3) +
  coord_cartesian(xlim= LON.range, ylim= LAT.range) +
  #scale_size(range=c(2,4))+
  labs(title= "PM10 Concentration in Seoul Area at South Korea",
       x="Longitude", y= "Latitude")+
  theme(title= element_text(hjust = 0.5,vjust = 1,face= c("bold")))

编辑 OP询问了映射到相同色阶的点，而不是fill="yellow"中美学之外定义的geom_point()。在视觉上，这不会添加任何东西，因为点与kriged背景融为一体，但代码是按要求添加的。

Edit2：如果您希望绘图位于原始纬度和经度坐标中，则需要将不同的图层转换为相同的坐标系。但是这种转换可能会导致不规则的网格不适用于geom_tile。 Solution 1：stat_summary_2d对不规则网格中的数据进行分区和平均，或Solution 2：绘制大方点。

#Reproject the krige data
myKrige1 <- myKrige
coordinates(myKrige1) <- ~LON+LAT 
proj4string(myKrige1) <-"+proj=utm +north +zone=52 +datum=WGS84" 
myKrige_new <- spTransform(myKrige1, CRS("+proj=longlat")) 
myKrige_new <-  data.frame(myKrige_new@coords, pred = myKrige_new@data$pred) 
LON.range.new <- range(myKrige_new$LON) 
LAT.range.new <- range(myKrige_new$LAT)

#Original seoul data have correct lat/lon data
seoul <- read.csv ("seoul032823.csv")   #Reload seoul032823 data

#Original skorea data transformed the same was as myKrige_new
skorea1 <- getData("GADM", country= "KOR", level=1)
#Convert SpatialPolygonsDataFrame to dataframe (deprecated.  see `broom`)
skorea1 <- fortify(skorea1)  
coordinates(skorea1) <- ~long+lat  #{sp} Convert to sp object
proj4string(skorea1) <- "+proj=longlat +datum=WGS84" #{sp} set projection attributes 1
#{sp} Transform to new coordinate reference system
myKorea1 <- spTransform(skorea1, CRS("+proj=longlat")) 
myKorea1 <- data.frame(myKorea1)  #Convert spatial object to data.frame for ggplot

ggplot()+ theme_minimal() +
  #SOLUTION 1:
  stat_summary_2d(data=myKrige_new, aes(x = LON, y = LAT, z = pred),
                  binwidth = c(0.02,0.02)) +
  #SOLUTION 2: Uncomment the line(s) below:
  #geom_point(data = myKrige_new, aes(x= LON, y= LAT, fill = pred),
  #           shape=22, size=8, colour=NA) + 
  scale_fill_gradient2(name=bquote(atop("PM10", mu*g~m^-3)), 
                       high="red", mid= "plum3", low="blue", 
                       space="Lab", midpoint = median(myKrige_new$pred)) + 
  geom_map(data= myKorea1, map= myKorea1, aes(x=long,y=lat,map_id=id,group=group),
           fill=NA, colour="black") +
  geom_point(data= seoul, aes(x=LON, y=LAT, fill=PM10), 
             shape=21, alpha=1,na.rm=T, size=3) +
  coord_cartesian(xlim= LON.range.new, ylim= LAT.range.new) +
  #scale_size(range=c(2,4))+
  labs(title= "PM10 Concentration in Seoul Area at South Korea",
       x="Longitude", y= "Latitude")+
  theme(title= element_text(hjust = 0.5,vjust = 1,face= c("bold")))

如何在R的国家地图的特定区域上重叠克里金空间预测图？

1 个答案: